@article{pmid37728641,

title = {Increased task-relevant fMRI responsiveness in comatose cardiac arrest patients is associated with improved neurologic outcomes},

author = {Kiran Dhakal and Eric S Rosenthal and Annelise M Kulpanowski and Jacob A Dodelson and Zihao Wang and Gaston Cudemus-Deseda and Marjorie Villien and Brian L Edlow and Alexander M Presciutti and James L Januzzi and MingMing Ning and W Taylor Kimberly and Edilberto Amorim and M Brandon Westover and William A Copen and Pamela W Schaefer and Joseph T Giacino and David M Greer and Ona Wu},

doi = {10.1177/0271678X231197392},

issn = {1559-7016},

year  = {2024},

date = {2024-01-01},

journal = {J Cereb Blood Flow Metab},

volume = {44},

number = {1},

pages = {50--65},

abstract = {Early prediction of the recovery of consciousness in comatose cardiac arrest patients remains challenging. We prospectively studied task-relevant fMRI responses in 19 comatose cardiac arrest patients and five healthy controls to assess the fMRI's utility for neuroprognostication. Tasks involved instrumental music listening, forward and backward language listening, and motor imagery. Task-specific reference images were created from group-level fMRI responses from the healthy controls. Dice scores measured the overlap of individual subject-level fMRI responses with the reference images. Task-relevant responsiveness index (Rindex) was calculated as the maximum Dice score across the four tasks. Correlation analyses showed that increased Dice scores were significantly associated with arousal recovery () and emergence from the minimally conscious state (EMCS) by one year () for all tasks except motor imagery. Greater Rindex was significantly correlated with improved arousal recovery (P = 0.002) and consciousness (P = 0.001). For patients who survived to discharge (), the Rindex's sensitivity was 75% for predicting EMCS (n = 4). Task-based fMRI holds promise for detecting covert consciousness in comatose cardiac arrest patients, but further studies are needed to confirm these findings. Caution is necessary when interpreting the absence of task-relevant fMRI responses as a surrogate for inevitable poor neurological prognosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38123951,

title = {Understanding Bias in Artificial Intelligence: A Practice Perspective},

author = {Melissa A Davis and Ona Wu and Ichiro Ikuta and John E Jordan and Michele H Johnson and Edward Quigley},

doi = {10.3174/ajnr.A8070},

issn = {1936-959X},

year  = {2023},

date = {2023-12-01},

journal = {AJNR Am J Neuroradiol},

abstract = {In the fall of 2021, several experts in this space delivered a Webinar hosted by the American Society of Neuroradiology (ASNR) Diversity and Inclusion Committee, focused on expanding the understanding of bias in artificial intelligence, with a health equity lens, and provided key concepts for neuroradiologists to approach the evaluation of these tools. In this perspective, we distill key parts of this discussion, including understanding why this topic is important to neuroradiologists and lending insight on how neuroradiologists can develop a framework to assess health equity-related bias in artificial intelligence tools. In addition, we provide examples of clinical workflow implementation of these tools so that we can begin to see how artificial intelligence tools will impact discourse on equitable radiologic care. As continuous learners, we must be engaged in new and rapidly evolving technologies that emerge in our field. The Diversity and Inclusion Committee of the ASNR has addressed this subject matter through its programming content revolving around health equity in neuroradiologic advances.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38081435,

title = {Neuroimmune activation and increased brain aging in chronic pain patients after the COVID-19 pandemic onset},

author = {Ludovica Brusaferri and Zeynab Alshelh and Jack H Schnieders and Angelica Sandström and Mehrbod Mohammadian and Erin J Morrissey and Minhae Kim and Courtney A Chane and Grace C Grmek and Jennifer P Murphy and Julia Bialobrzewski and Alexa DiPietro and Julie Klinke and Yi Zhang and Angel Torrado-Carvajal and Nathaniel Mercaldo and Oluwaseun Akeju and Ona Wu and Bruce R Rosen and Vitaly Napadow and Nouchine Hadjikhani and Marco L Loggia},

doi = {10.1016/j.bbi.2023.12.016},

issn = {1090-2139},

year  = {2023},

date = {2023-12-01},

journal = {Brain Behav Immun},

volume = {116},

pages = {259--266},

abstract = {The COVID-19 pandemic has exerted a global impact on both physical and mental health, and clinical populations have been disproportionally affected. To date, however, the mechanisms underlying the deleterious effects of the pandemic on pre-existing clinical conditions remain unclear. Here we investigated whether the onset of the pandemic was associated with an increase in brain/blood levels of inflammatory markers and MRI-estimated brain age in patients with chronic low back pain (cLBP), irrespective of their infection history. A retrospective cohort study was conducted on 56 adult participants with cLBP (28 'Pre-Pandemic', 28 'Pandemic') using integrated Positron Emission Tomography/ Magnetic Resonance Imaging (PET/MRI) and the radioligand [C]PBR28, which binds to the neuroinflammatory marker 18 kDa Translocator Protein (TSPO). Image data were collected between November 2017 and January 2020 ('Pre-Pandemic' cLBP) or between August 2020 and May 2022 ('Pandemic' cLBP). Compared to the Pre-Pandemic group, the Pandemic patients demonstrated widespread and statistically significant elevations in brain TSPO levels (P =.05, cluster corrected). PET signal elevations in the Pandemic group were also observed when 1) excluding 3 Pandemic subjects with a known history of COVID infection, or 2) using secondary outcome measures (volume of distribution -V- and V ratio - DVR) in a smaller subset of participants. Pandemic subjects also exhibited elevated serum levels of inflammatory markers (IL-16; P <.05) and estimated BA (P <.0001), which were positively correlated with [C]PBR28 SUVR (r's ≥ 0.35; P's < 0.05). The pain interference scores, which were elevated in the Pandemic group (P <.05), were negatively correlated with [C]PBR28 SUVR in the amygdala (r = -0.46; P<.05). This work suggests that the pandemic outbreak may have been accompanied by neuroinflammation and increased brain age in cLBP patients, as measured by multimodal imaging and serum testing. This study underscores the broad impact of the pandemic on human health, which extends beyond the morbidity solely mediated by the virus itself.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37652578,

title = {Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology},

author = {C G Filippi and J M Stein and Z Wang and S Bakas and Y Liu and P D Chang and Y Lui and C Hess and D P Barboriak and A E Flanders and M Wintermark and G Zaharchuk and O Wu},

doi = {10.3174/ajnr.A7963},

issn = {1936-959X},

year  = {2023},

date = {2023-11-01},

journal = {AJNR Am J Neuroradiol},

volume = {44},

number = {11},

pages = {1242--1248},

abstract = {In this review, concepts of algorithmic bias and fairness are defined qualitatively and mathematically. Illustrative examples are given of what can go wrong when unintended bias or unfairness in algorithmic development occurs. The importance of explainability, accountability, and transparency with respect to artificial intelligence algorithm development and clinical deployment is discussed. These are grounded in the concept of "primum no nocere" (first, do no harm). Steps to mitigate unfairness and bias in task definition, data collection, model definition, training, testing, deployment, and feedback are provided. Discussions on the implementation of fairness criteria that maximize benefit and minimize unfairness and harm to neuroradiology patients will be provided, including suggestions for neuroradiologists to consider as artificial intelligence algorithms gain acceptance into neuroradiology practice and become incorporated into routine clinical workflow.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37873758,

title = {Hyperperfusion profiles after recanalization differentially associate with outcomes in a rat ischemic stroke model},

author = {Bart Aa Franx and Geralda Af van Tilborg and Aladdin Taha and Joaquim Bobi and Annette van der Toorn and Caroline L Van Heijningen and Heleen Mm van Beusekom and Ona Wu and Rick M Dijkhuizen and },

doi = {10.1177/0271678X231208993},

issn = {1559-7016},

year  = {2023},

date = {2023-10-01},

journal = {J Cereb Blood Flow Metab},

pages = {271678X231208993},

abstract = {Futile recanalization hampers prognoses of ischemic stroke after successful mechanical thrombectomy, hypothetically through post-recanalization perfusion deficits, onset-to-groin delays and sex effects. Clinically, acute multiparametric imaging studies remain challenging. We assessed possible relationships between these factors and disease outcome after experimental cerebral ischemia-reperfusion, using translational MRI, behavioral testing and multi-model inference analyses. Male and female rats (N = 60) were subjected to 45-/90-min filament-induced transient middle cerebral artery occlusion. Diffusion, T- and perfusion-weighted MRI at occlusion, 0.5 h and four days after recanalization, enabled tracking of tissue fate, and relative regional cerebral blood flow (rrCBF) and -volume (rrCBV). Lesion areas were parcellated into core, salvageable tissue and delayed injury, verified by histology. Recanalization resulted in acute-to-subacute lesion volume reductions, most apparently in females (n = 19). Hyperacute normo-to-hyperperfusion in the post-ischemic lesion augmented towards day four, particularly in males (n = 23). Tissue suffering delayed injury contained higher ratios of hypoperfused voxels early after recanalization. Regressed against acute-to-subacute lesion volume change, increased rrCBF associated with lesion growth, but increased rrCBV with lesion reduction. Similar relationships were detected for behavioral outcome. Post-ischemic hyperperfusion may develop differentially in males and females, and can be beneficial or detrimental to disease outcome, depending on which perfusion parameter is used as explanatory variable.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36892781,

title = {The relationship between mindfulness and enduring somatic threat severity in long-term cardiac arrest survivors},

author = {Alexander M Presciutti and Sarah M Bannon and Jolin B Yamin and Mary M Newman and Robert A Parker and Jonathan Elmer and Ona Wu and Michael W Donnino and Sarah M Perman and Ana-Maria Vranceanu},

doi = {10.1007/s10865-023-00405-x},

issn = {1573-3521},

year  = {2023},

date = {2023-10-01},

journal = {J Behav Med},

volume = {46},

number = {5},

pages = {890--896},

abstract = {BACKGROUND: Cardiac arrest (CA) survivors experience continuous exposures to potential traumas though chronic cognitive, physical and emotional sequelae and enduring somatic threats (ESTs) (i.e., recurring somatic traumatic reminders of the event). Sources of ESTs can include the daily sensation of an implantable cardioverter defibrillator (ICD), ICD-delivered shocks, pain from rescue compressions, fatigue, weakness, and changes in physical function. Mindfulness, defined as non-judgmental present-moment awareness, is a teachable skill that might help CA survivors cope with ESTs. Here we describe the severity of ESTs in a sample of long-term CA survivors and explore the cross-sectional relationship between mindfulness and severity of ESTs.nnMETHODS: We analyzed survey data of long-term CA survivors who were members of the Sudden Cardiac Arrest Foundation (collected 10-11/2020). We assessed ESTs using 4 cardiac threat items from the Anxiety Sensitivity Index-revised (items range from 0 "very little" to 4 "very much") which we summed to create a score reflecting total EST burden (range 0-16). We assessed mindfulness using the Cognitive and Affective Mindfulness Scale-Revised. First, we summarized the distribution of EST scores. Second, we used linear regression to describe the relationship between mindfulness and EST severity adjusting for age, gender, time since arrest, COVID-19-related stress, and loss of income due to COVID.nnRESULTS: We included 145 CA survivors (mean age: 51 years, 52% male, 93.8% white, mean time since arrest: 6 years, 24.1% scored in the upper quarter of EST severity). Greater mindfulness (β: -30, p = 0.002), older age (β: -0.30, p = 0.01) and longer time since CA (β: -0.23, p = 0.005) were associated with lower EST severity. Male sex was also associated with greater EST severity (β: 0.21, p = 0.009).nnCONCLUSION: ESTs are common among CA survivors. Mindfulness may be a protective skill that CA survivors use to cope with ESTs. Future psychosocial interventions for the CA population should consider using mindfulness as a core skill to reduce ESTs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37399040,

title = {Mapping Lesion-Related Epilepsy to a Human Brain Network},

author = {Frederic L W V J Schaper and Janne Nordberg and Alexander L Cohen and Christopher Lin and Joey Hsu and Andreas Horn and Michael A Ferguson and Shan H Siddiqi and William Drew and Louis Soussand and Anderson M Winkler and Marta Simó and Jordi Bruna and Sylvain Rheims and Marc Guenot and Marco Bucci and Lauri Nummenmaa and Julie Staals and Albert J Colon and Linda Ackermans and Ellen J Bubrick and Jurriaan M Peters and Ona Wu and Natalia S Rost and Jordan Grafman and Hal Blumenfeld and Yasin Temel and Rob P W Rouhl and Juho Joutsa and Michael D Fox},

doi = {10.1001/jamaneurol.2023.1988},

issn = {2168-6157},

year  = {2023},

date = {2023-09-01},

journal = {JAMA Neurol},

volume = {80},

number = {9},

pages = {891--902},

abstract = {IMPORTANCE: It remains unclear why lesions in some locations cause epilepsy while others do not. Identifying the brain regions or networks associated with epilepsy by mapping these lesions could inform prognosis and guide interventions.nnOBJECTIVE: To assess whether lesion locations associated with epilepsy map to specific brain regions and networks.nnDESIGN, SETTING, AND PARTICIPANTS: This case-control study used lesion location and lesion network mapping to identify the brain regions and networks associated with epilepsy in a discovery data set of patients with poststroke epilepsy and control patients with stroke. Patients with stroke lesions and epilepsy (n = 76) or no epilepsy (n = 625) were included. Generalizability to other lesion types was assessed using 4 independent cohorts as validation data sets. The total numbers of patients across all datasets (both discovery and validation datasets) were 347 with epilepsy and 1126 without. Therapeutic relevance was assessed using deep brain stimulation sites that improve seizure control. Data were analyzed from September 2018 through December 2022. All shared patient data were analyzed and included; no patients were excluded.nnMAIN OUTCOMES AND MEASURES: Epilepsy or no epilepsy.nnRESULTS: Lesion locations from 76 patients with poststroke epilepsy (39 [51%] male; mean [SD] age, 61.0 [14.6] years; mean [SD] follow-up, 6.7 [2.0] years) and 625 control patients with stroke (366 [59%] male; mean [SD] age, 62.0 [14.1] years; follow-up range, 3-12 months) were included in the discovery data set. Lesions associated with epilepsy occurred in multiple heterogenous locations spanning different lobes and vascular territories. However, these same lesion locations were part of a specific brain network defined by functional connectivity to the basal ganglia and cerebellum. Findings were validated in 4 independent cohorts including 772 patients with brain lesions (271 [35%] with epilepsy; 515 [67%] male; median [IQR] age, 60 [50-70] years; follow-up range, 3-35 years). Lesion connectivity to this brain network was associated with increased risk of epilepsy after stroke (odds ratio [OR], 2.82; 95% CI, 2.02-4.10; P < .001) and across different lesion types (OR, 2.85; 95% CI, 2.23-3.69; P < .001). Deep brain stimulation site connectivity to this same network was associated with improved seizure control (r, 0.63; P < .001) in 30 patients with drug-resistant epilepsy (21 [70%] male; median [IQR] age, 39 [32-46] years; median [IQR] follow-up, 24 [16-30] months).nnCONCLUSIONS AND RELEVANCE: The findings in this study indicate that lesion-related epilepsy mapped to a human brain network, which could help identify patients at risk of epilepsy after a brain lesion and guide brain stimulation therapies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37414565,

title = {Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest},

author = {Edilberto Amorim and Wei-Long Zheng and Jin Jing and Mohammad M Ghassemi and Jong Woo Lee and Ona Wu and Susan T Herman and Trudy Pang and Adithya Sivaraju and Nicolas Gaspard and Lawrence Hirsch and Barry J Ruijter and Marleen C Tjepkema-Cloostermans and Jeannette Hofmeijer and Michel J A M van Putten and M Brandon Westover},

doi = {10.1212/WNL.0000000000207537},

issn = {1526-632X},

year  = {2023},

date = {2023-08-01},

journal = {Neurology},

volume = {101},

number = {9},

pages = {e940--e952},

abstract = {BACKGROUND AND OBJECTIVES: Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest.nnMETHODS: Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months.nnRESULTS: One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery.nnDISCUSSION: Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37282582,

title = {Tau Positron Emission Tomography and Neurocognitive Function Among Former Professional American-Style Football Players},

author = {Maeva Dhaynaut and Rachel Grashow and Marc D Normandin and Ona Wu and Dean Marengi and Douglas P Terry and Justin S Sanchez and Marc G Weisskopf and Frank E Speizer and Herman A Taylor and Nicolas J Guehl and Sudha Seshadri and Alexa Beiser and Daniel H Daneshvar and Keith Johnson and Grant L Iverson and Ross Zafonte and Georges El Fakhri and Aaron L Baggish},

doi = {10.1089/neu.2022.0454},

issn = {1557-9042},

year  = {2023},

date = {2023-08-01},

journal = {J Neurotrauma},

volume = {40},

number = {15-16},

pages = {1614--1624},

abstract = {American-style football (ASF) players experience repetitive head impacts that may result in chronic traumatic encephalopathy neuropathological change (CTE-NC). At present, a definitive diagnosis of CTE-NC requires the identification of localized hyperphosphorylated Tau (p-Tau) after death via immunohistochemistry. Some studies suggest that positron emission tomography (PET) with the radiotracer [F]-Flortaucipir (FTP) may be capable of detecting p-Tau and thus establishing a diagnosis of CTE-NC among living former ASF players. To assess associations between FTP, football exposure, and objective neuropsychological measures among former professional ASF players, we conducted a study that compared former professional ASF players with age-matched male control participants without repetitive head impact exposure. Former ASF players and male controls underwent structural magnetic resonance imaging and PET using FTP for p-Tau and [C]-PiB for amyloid-β. Former players underwent neuropsychological testing. The ASF exposure was quantified as age at first exposure, professional career duration, concussion signs and symptoms burden, and total years of any football play. Neuropsychological testing included measures of memory, executive functioning, and depression symptom severity. P-Tau was quantified as FTP standardized uptake value ratios (SUVR) and [C]-PiB by distribution volume ratios (DVR) using cerebellar grey matter as the reference region. There were no significant differences in [F]-FTP uptake among former ASF players ( = 27, age = 50 ± 7 years) compared with control participants ( = 11, age = 55 ± 4 years), nor did any participant have significant amyloid-β burden. Among ASF participants, there were no associations between objective measures of neurocognitive functioning and [F]-FTP uptake. There was a marginally significant difference, however, between [F]-FTP uptake isolated to the entorhinal cortex among players in age-, position-, and race-adjusted models ( = 0.05) that may represent an area of future investigation. The absence of increased [F]-FTP uptake in brain regions previously implicated in CTE among former professional ASF players compared with controls questions the utility of [F]-FTP PET for clinical evaluation in this population.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37141607,

title = {A Case Report of Reversible Cognitive Decline in a Former Professional American-Style Football Player: Findings from the Football Players Health Study In-Person Assessments},

author = {Inana Dairi and Cheyenne Brown and Heather DiGregorio and Meagan Wasfy and Aaron Baggish and Linda Pitler and William A Copen and Michael Doyle and Ona Wu and Ross Zafonte and Adam S Tenforde},

doi = {10.1249/JSR.0000000000001061},

issn = {1537-8918},

year  = {2023},

date = {2023-05-01},

journal = {Curr Sports Med Rep},

volume = {22},

number = {5},

pages = {154--157},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36440953,

title = {The relevance of rich club regions for functional outcome post-stroke is enhanced in women},

author = {Anna K Bonkhoff and Markus D Schirmer and Martin Bretzner and Sungmin Hong and Robert W Regenhardt and Kathleen L Donahue and Marco J Nardin and Adrian V Dalca and Anne-Katrin Giese and Mark R Etherton and Brandon L Hancock and Steven J T Mocking and Elissa C McIntosh and John Attia and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ramin Zand and Patrick F McArdle and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Ona Wu and Natalia S Rost and },

doi = {10.1002/hbm.26159},

issn = {1097-0193},

year  = {2023},

date = {2023-03-01},

journal = {Hum Brain Mapp},

volume = {44},

number = {4},

pages = {1579--1592},

abstract = {This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS > 2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36443016,

title = {Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke},

author = {Martin Bretzner and Anna K Bonkhoff and Markus D Schirmer and Sungmin Hong and Adrian Dalca and Kathleen Donahue and Anne-Katrin Giese and Mark R Etherton and Pamela M Rist and Marco Nardin and Robert W Regenhardt and Xavier Leclerc and Renaud Lopes and Morgan Gautherot and Clinton Wang and Oscar R Benavente and John W Cole and Amanda Donatti and Christoph Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Patrick F McArdle and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ona Wu and Ramin Zand and Bradford B Worrall and Jane Maguire and Arne G Lindgren and Christina Jern and Polina Golland and Grégory Kuchcinski and Natalia S Rost and },

doi = {10.1212/WNL.0000000000201596},

issn = {1526-632X},

year  = {2023},

date = {2023-02-01},

journal = {Neurology},

volume = {100},

number = {8},

pages = {e822--e833},

abstract = {BACKGROUND AND OBJECTIVES: While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes.nnMETHODS: We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input.nnRESULTS: We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years,  = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all -values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes.nnDISCUSSION: T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37799462,

title = {A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength},

author = {Mark S Shiroishi and Dane Weinert and Steven Y Cen and Bino Varghese and Timothy Dondlinger and Melissa Prah and Jesse Mendoza and Sina Nazemi and Nima Ameli and Negin Amini and Salman Shohas and Shannon Chen and Bavrina Bigjahan and Gabriel Zada and Thomas Chen and Josh Neman-Ebrahim and Eric L Chang and Frances E Chow and Zhaoyang Fan and Wensha Yang and Frank J Attenello and Jason Ye and Paul E Kim and Vishal N Patel and Alexander Lerner and Jay Acharya and Leland S Hu and C Chad Quarles and Jerrold L Boxerman and Ona Wu and Kathleen M Schmainda},

doi = {10.3389/fonc.2023.1156843},

issn = {2234-943X},

year  = {2023},

date = {2023-01-01},

journal = {Front Oncol},

volume = {13},

pages = {1156843},

abstract = {INTRODUCTION: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients.nnMETHODS: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC).nnRESULTS: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV.nnCONCLUSION: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35997023,

title = {Alteplase for Stroke With Unknown Onset Time in Chronic Kidney Disease: A Pooled Analysis of Individual Participant Data},

author = {Kaori Miwa and Masatoshi Koga and Märit Jensen and Manabu Inoue and Sohei Yoshimura and Mayumi Fukuda-Doi and Florent Boutitie and Henry Ma and Peter A Ringleb and Ona Wu and Lee H Schwamm and Steven Warach and Werner Hacke and Stephen M Davis and Geoffrey A Donnan and Christian Gerloff and Götz Thomalla and Kazunori Toyoda and },

doi = {10.1161/STROKEAHA.122.039086},

issn = {1524-4628},

year  = {2022},

date = {2022-11-01},

journal = {Stroke},

volume = {53},

number = {11},

pages = {3295--3303},

abstract = {BACKGROUND: Although chronic kidney disease (CKD) is associated with worse stroke outcomes, data regarding the influence of CKD on intravenous thrombolysis outcomes are scarce. We sought to assess the efficacy and safety of intravenous thrombolysis for acute ischemic stroke with unknown onset time in patients with CKD.nnMETHODS: Patients with an acute stroke of unknown onset time from the EOS trials (Evaluation of Unknown Onset Stroke Thrombolysis) collaboration were evaluated using an individual patient-level database of randomized controlled trials comparing intravenous thrombolysis with placebo/standard treatment. CKD was defined as baseline estimated glomerular filtration rate of <60 ml/min/1.73m Mixed-effect logistic-regression analysis was performed to evaluate treatment effects. A favorable outcome was defined as a modified Rankin Scale score of 0 to 1 at 90 days. Safety outcomes were symptomatic intracranial hemorrhage at 22 to 36 hours and 90-day mortality.nnRESULTS: Baseline data on renal function were available for 688 of 843 patients. Of these, CKD was present in 146 (21%), including 69 of 351 patients receiving alteplase and 77 of 337 patients receiving placebo/standard treatment. Overall, treatment with alteplase was associated with higher odds of favorable outcome, and CKD did not modify the treatment effect (=0.834). A favorable outcome was observed in 31 of 69 (46%) patients with CKD in the alteplase group and in 28 of 77 (36%) patients with CKD in the control group (adjusted odds ratio, 1.19 [95% CI, 0.55-2.58]). Among patients with CKD, symptomatic intracranial hemorrhage occurred in 2 patients (3%) in the alteplase group but in none of the controls (=0.133). At 90 days, death was reported in 3 patients (4%) in the alteplase group compared with 2 patients (3%) in the controls (=0.539).nnCONCLUSIONS: The present analysis indicates that the benefit of alteplase does not differ between stroke patients with unknown onset time with and without CKD, although the statistical power was lacking to confirm the efficacy in subgroups. This study only applies to mild-to-moderate or predialysis CKD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35803717,

title = {Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome},

author = {Anna K Bonkhoff and Sungmin Hong and Martin Bretzner and Markus D Schirmer and Robert W Regenhardt and E Murat Arsava and Kathleen Donahue and Marco Nardin and Adrian Dalca and Anne-Katrin Giese and Mark R Etherton and Brandon L Hancock and Steven J T Mocking and Elissa McIntosh and John Attia and Oscar Benavente and John W Cole and Amanda Donatti and Christoph Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven Kittner and Robin Lemmens and Christopher Levi and Caitrin W McDonough and James Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Martin Soederholm and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ramin Zand and Patrick McArdle and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Polina Golland and Danilo Bzdok and Ona Wu and Natalia S Rost},

doi = {10.1212/WNL.0000000000200926},

issn = {1526-632X},

year  = {2022},

date = {2022-09-01},

journal = {Neurology},

volume = {99},

number = {13},

pages = {e1364--e1379},

abstract = {BACKGROUND AND OBJECTIVES: To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.nnMETHODS: MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.nnRESULTS: A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location.nnDISCUSSION: Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35576861,

title = {Migraine-Associated Common Genetic Variants Confer Greater Risk of Posterior vs. Anterior Circulation Ischemic Stroke☆},

author = {P Frid and H Xu and B D Mitchell and M Drake and J Wasselius and B Gaynor and K Ryan and A K Giese and M Schirmer and K L Donahue and R Irie and M J R J Bouts and E C McIntosh and S J T Mocking and A V Dalca and E Giralt-Steinhauer and L Holmegaard and K Jood and J Roquer and J W Cole and P F McArdle and J P Broderick and J Jimenez-Conde and C Jern and B M Kissela and D O Kleindorfer and R Lemmens and J F Meschia and J Rosand and T Rundek and R L Sacco and R Schmidt and P Sharma and A Slowik and V Thijs and D Woo and B B Worrall and S J Kittner and J Petersson and P Golland and O Wu and N S Rost and A Lindgren},

doi = {10.1016/j.jstrokecerebrovasdis.2022.106546},

issn = {1532-8511},

year  = {2022},

date = {2022-08-01},

journal = {J Stroke Cerebrovasc Dis},

volume = {31},

number = {8},

pages = {106546},

abstract = {OBJECTIVE: To examine potential genetic relationships between migraine and the two distinct phenotypes posterior circulation ischemic stroke (PCiS) and anterior circulation ischemic stroke (ACiS), we generated migraine polygenic risk scores (PRSs) and compared these between PCiS and ACiS, and separately vs. non-stroke control subjects.nnMETHODS: Acute ischemic stroke cases were classified as PCiS or ACiS based on lesion location on diffusion-weighted MRI. Exclusion criteria were lesions in both vascular territories or uncertain territory; supratentorial PCiS with ipsilateral fetal posterior cerebral artery; and cases with atrial fibrillation. We generated migraine PRS for three migraine phenotypes (any migraine; migraine without aura; migraine with aura) using publicly available GWAS data and compared mean PRSs separately for PCiS and ACiS vs. non-stroke control subjects, and between each stroke phenotype.nnRESULTS: Our primary analyses included 464 PCiS and 1079 ACiS patients with genetic European ancestry. Compared to non-stroke control subjects (n=15396), PRSs of any migraine were associated with increased risk of PCiS (p=0.01-0.03) and decreased risk of ACiS (p=0.010-0.039). Migraine without aura PRSs were significantly associated with PCiS (p=0.008-0.028), but not with ACiS. When comparing PCiS vs. ACiS directly, migraine PRSs were higher in PCiS vs. ACiS for any migraine (p=0.001-0.010) and migraine without aura (p=0.032-0.048). Migraine with aura PRS did not show a differential association in our analyses.nnCONCLUSIONS: Our results suggest a stronger genetic overlap between unspecified migraine and migraine without aura with PCiS compared to ACiS. Possible shared mechanisms include dysregulation of cerebral vessel endothelial function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34962860,

title = {Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning},

author = {Wei-Long Zheng and Edilberto Amorim and Jin Jing and Ona Wu and Mohammad Ghassemi and Jong Woo Lee and Adithya Sivaraju and Trudy Pang and Susan T Herman and Nicolas Gaspard and Barry J Ruijter and Marleen C Tjepkema-Cloostermans and Jeannette Hofmeijer and Michel J A M van Putten and M Brandon Westover},

doi = {10.1109/TBME.2021.3139007},

issn = {1558-2531},

year  = {2022},

date = {2022-05-01},

urldate = {2022-05-01},

journal = {IEEE Trans Biomed Eng},

volume = {69},

number = {5},

pages = {1813--1825},

abstract = {OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information.nnMETHODS: We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation.nnRESULTS: The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04).nnCONCLUSIONS AND SIGNIFICANCE: These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34962860b,

title = {Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning},

author = {Wei-Long Zheng and Edilberto Amorim and Jin Jing and Ona Wu and Mohammad Ghassemi and Jong Woo Lee and Adithya Sivaraju and Trudy Pang and Susan T Herman and Nicolas Gaspard and Barry J Ruijter and Marleen C Tjepkema-Cloostermans and Jeannette Hofmeijer and Michel J A M van Putten and M Brandon Westover},

doi = {10.1109/TBME.2021.3139007},

issn = {1558-2531},

year  = {2022},

date = {2022-05-01},

journal = {IEEE Trans Biomed Eng},

volume = {69},

number = {5},

pages = {1813--1825},

abstract = {OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches largely rely on snapshots of the EEG, without taking advantage of temporal information.nnMETHODS: We present a recurrent deep neural network with the goal of capturing temporal dynamics from longitudinal EEG data to predict long-term neurological outcomes. We utilized a large international dataset of continuous EEG recordings from 1,038 cardiac arrest patients from seven hospitals in Europe and the US. Poor outcome was defined as a Cerebral Performance Category (CPC) score of 3-5, and good outcome as CPC score 0-2 at 3 to 6-months after cardiac arrest. Model performance is evaluated using 5-fold cross validation.nnRESULTS: The proposed approach provides predictions which improve over time, beginning from an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% CI: 0.72-0.81) at 12 hours, and reaching 0.88 (95% CI: 0.85-0.91) by 66 h after cardiac arrest. At 66 h, (sensitivity, specificity) points of interest on the ROC curve for predicting poor outcomes were (32,99)%, (55,95)%, and (62,90)%, (99,23)%, (95,47)%, and (90,62)%; whereas for predicting good outcome, the corresponding operating points were (17,99)%, (47,95)%, (62,90)%, (99,19)%, (95,48)%, (70,90)%. Moreover, the model provides predicted probabilities that closely match the observed frequencies of good and poor outcomes (calibration error 0.04).nnCONCLUSIONS AND SIGNIFICANCE: These findings suggest that accounting for EEG trend information can substantially improve prediction of neurologic outcomes for patients with coma following cardiac arrest.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35149137,

title = {Severe cerebral edema in substance-related cardiac arrest patients},

author = {Annelise M Kulpanowski and William A Copen and Brandon L Hancock and Eric S Rosenthal and David A Schoenfeld and Jacob A Dodelson and Brian L Edlow and W Taylor Kimberly and Edilberto Amorim and M Brandon Westover and Ming Ming Ning and Pamela W Schaefer and Rajeev Malhotra and Joseph T Giacino and David M Greer and Ona Wu},

doi = {10.1016/j.resuscitation.2022.01.033},

issn = {1873-1570},

year  = {2022},

date = {2022-04-01},

urldate = {2022-04-01},

journal = {Resuscitation},

volume = {173},

pages = {103--111},

abstract = {BACKGROUND: Studies of neurologic outcomes have found conflicting results regarding differences between patients with substance-related cardiac arrests (SRCA) and non-SRCA. We investigate the effects of SRCA on severe cerebral edema development, a neuroimaging intermediate endpoint for neurologic injury.nnMETHODS: 327 out-of-hospital comatose cardiac arrest patients were retrospectively analyzed. Demographics and baseline clinical characteristics were examined. SRCA categorization was based on admission toxicology screens. Severe cerebral edema classification was based on radiology reports. Poor clinical outcomes were defined as discharge Cerebral Performance Category scores > 3.nnRESULTS: SRCA patients (N = 86) were younger (P < 0.001), and more likely to have non-shockable rhythms (P < 0.001), be unwitnessed (P < 0.001), lower Glasgow Coma Scale scores (P < 0.001), absent brainstem reflexes (P < 0.05) and develop severe cerebral edema (P < 0.001) than non-SRCA patients (N = 241). Multivariable analyses found younger age (P < 0.001), female sex (P = 0.008), non-shockable rhythm (P = 0.01) and SRCA (P = 0.05) to be predictors of severe cerebral edema development. Older age (P < 0.001), non-shockable rhythm (P = 0.02), severe cerebral edema (P < 0.001), and absent pupillary light reflexes (P = 0.004) were predictors of poor outcomes. SRCA patients had higher proportion of brain deaths (P < 0.001) compared to non-SRCA patients.nnCONCLUSIONS: SRCA results in higher rates of severe cerebral edema development and brain death. The absence of statistically significant differences in discharge outcomes or survival between SRCA and non-SRCA patients may be related to the higher rate of withdrawal of life-sustaining treatment (WLST) in the non-SRCA group. Future neuroprognostic studies may opt to include neuroimaging markers as intermediate measures of neurologic injury which are not influenced by WLST decisions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36090258,

title = {Deep profiling of multiple ischemic lesions in a large, multi-center cohort: Frequency, spatial distribution, and associations to clinical characteristics},

author = {Anna K Bonkhoff and Teresa Ullberg and Martin Bretzner and Sungmin Hong and Markus D Schirmer and Robert W Regenhardt and Kathleen L Donahue and Marco J Nardin and Adrian V Dalca and Anne-Katrin Giese and Mark R Etherton and Brandon L Hancock and Steven J T Mocking and Elissa C McIntosh and John Attia and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Daniel Woo and Ramin Zand and Patrick F McArdle and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Ona Wu and Petrea Frid and Natalia S Rost and Johan Wasselius},

doi = {10.3389/fnins.2022.994458},

issn = {1662-4548},

year  = {2022},

date = {2022-01-01},

journal = {Front Neurosci},

volume = {16},

pages = {994458},

abstract = {BACKGROUND PURPOSE: A substantial number of patients with acute ischemic stroke (AIS) experience multiple acute lesions (MAL). We here aimed to scrutinize MAL in a large radiologically deep-phenotyped cohort.nnMATERIALS AND METHODS: Analyses relied upon imaging and clinical data from the international MRI-GENIE study. Imaging data comprised both Fluid-attenuated inversion recovery (FLAIR) for white matter hyperintensity (WMH) burden estimation and diffusion-weighted imaging (DWI) sequences for the assessment of acute stroke lesions. The initial step featured the systematic evaluation of occurrences of MAL within one and several vascular supply territories. Associations between MAL and important imaging and clinical characteristics were subsequently determined. The interaction effect between single and multiple lesion status and lesion volume was estimated by means of Bayesian hierarchical regression modeling for both stroke severity and functional outcome.nnRESULTS: We analyzed 2,466 patients (age = 63.4 ± 14.8, 39% women), 49.7% of which presented with a single lesion. Another 37.4% experienced MAL in a single vascular territory, while 12.9% featured lesions in multiple vascular territories. Within most territories, MAL occurred as frequently as single lesions (ratio ∼1:1). Only the brainstem region comprised fewer patients with MAL (ratio 1:4). Patients with MAL presented with a significantly higher lesion volume and acute NIHSS (7.7 vs. 1.7 ml and 4 vs. 3,  < 0.001). In contrast, patients with a single lesion were characterized by a significantly higher WMH burden (6.1 vs. 5.3 ml,   = 0.048). Functional outcome did not differ significantly between patients with single versus multiple lesions. Bayesian analyses suggested that the association between lesion volume and stroke severity between single and multiple lesions was the same in case of anterior circulation stroke. In case of posterior circulation stroke, lesion volume was linked to a higher NIHSS only among those with MAL.nnCONCLUSION: Multiple lesions, especially those within one vascular territory, occurred more frequently than previously reported. Overall, multiple lesions were distinctly linked to a higher acute stroke severity, a higher total DWI lesion volume and a lower WMH lesion volume. In posterior circulation stroke, lesion volume was linked to a higher stroke severity in multiple lesions only.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35282166,

title = {Sex-specific lesion pattern of functional outcomes after stroke},

author = {Anna K Bonkhoff and Martin Bretzner and Sungmin Hong and Markus D Schirmer and Alexander Cohen and Robert W Regenhardt and Kathleen L Donahue and Marco J Nardin and Adrian V Dalca and Anne-Katrin Giese and Mark R Etherton and Brandon L Hancock and Steven J T Mocking and Elissa C McIntosh and John Attia and Oscar R Benavente and Stephen Bevan and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Martin Söderholm and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ramin Zand and Patrick F McArdle and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Michael D Fox and Danilo Bzdok and Ona Wu and Natalia S Rost and },

doi = {10.1093/braincomms/fcac020},

issn = {2632-1297},

year  = {2022},

date = {2022-01-01},

journal = {Brain Commun},

volume = {4},

number = {2},

pages = {fcac020},

abstract = {Stroke represents a considerable burden of disease for both men and women. However, a growing body of literature suggests clinically relevant sex differences in the underlying causes, presentations and outcomes of acute ischaemic stroke. In a recent study, we reported sex divergences in lesion topographies: specific to women, acute stroke severity was linked to lesions in the left-hemispheric posterior circulation. We here determined whether these sex-specific brain manifestations also affect long-term outcomes. We relied on 822 acute ischaemic patients [age: 64.7 (15.0) years, 39% women] originating from the multi-centre MRI-GENIE study to model unfavourable outcomes (modified Rankin Scale >2) based on acute neuroimaging data in a Bayesian hierarchical framework. Lesions encompassing bilateral subcortical nuclei and left-lateralized regions in proximity to the insula explained outcomes across men and women (area under the curve = 0.81). A pattern of left-hemispheric posterior circulation brain regions, combining left hippocampus, precuneus, fusiform and lingual gyrus, occipital pole and latero-occipital cortex, showed a substantially higher relevance in explaining functional outcomes in women compared to men [mean difference of Bayesian posterior distributions (men - women) = -0.295 (90% highest posterior density interval = -0.556 to -0.068)]. Once validated in prospective studies, our findings may motivate a sex-specific approach to clinical stroke management and hold the promise of enhancing outcomes on a population level.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34699925,

title = {Predicting neurological outcome in comatose patients after cardiac arrest with multiscale deep neural networks},

author = {Wei-Long Zheng and Edilberto Amorim and Jin Jing and Wendong Ge and Shenda Hong and Ona Wu and Mohammad Ghassemi and Jong Woo Lee and Adithya Sivaraju and Trudy Pang and Susan T Herman and Nicolas Gaspard and Barry J Ruijter and Jimeng Sun and Marleen C Tjepkema-Cloostermans and Jeannette Hofmeijer and Michel J A M van Putten and M Brandon Westover},

doi = {10.1016/j.resuscitation.2021.10.034},

issn = {1873-1570},

year  = {2021},

date = {2021-12-01},

journal = {Resuscitation},

volume = {169},

pages = {86--94},

abstract = {OBJECTIVE: Electroencephalography (EEG) is an important tool for neurological outcome prediction after cardiac arrest. However, the complexity of continuous EEG data limits timely and accurate interpretation by clinicians. We develop a deep neural network (DNN) model to leverage complex EEG trends for early and accurate assessment of cardiac arrest coma recovery likelihood.nnMETHODS: We developed a multiscale DNN combining convolutional neural networks (CNN) and recurrent neural networks (long short-term memory [LSTM]) using EEG and demographic information (age, gender, shockable rhythm) from a multicenter cohort of 1,038 cardiac arrest patients. The CNN learns EEG feature representations while the multiscale LSTM captures short-term and long-term EEG dynamics on multiple time scales. Poor outcome is defined as a Cerebral Performance Category (CPC) score of 3-5 and good outcome as CPC score 1-2 at 3-6 months after cardiac arrest. Performance is evaluated using area under the receiver operating characteristic curve (AUC) and calibration error.nnRESULTS: Model performance increased with EEG duration, with AUC increasing from 0.83 (95% Confidence Interval [CI] 0.79-0.87 at 12h to 0.91 (95%CI 0.88-0.93) at 66h. Sensitivity of good and poor outcome prediction was 77% and 75% at a specificity of 90%, respectively. Sensitivity of poor outcome was 50% at a specificity of 99%. Predicted probability was well matched to the observation frequency of poor outcomes, with a calibration error of 0.11 [0.09-0.14].nnCONCLUSIONS: These results demonstrate that incorporating EEG evolution over time improves the accuracy of neurologic outcome prediction for patients with coma after cardiac arrest.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34464927,

title = {Adapting Clinical Practice of Thrombolysis for Acute Ischemic Stroke Beyond 4.5 Hours: A Review of the Literature},

author = {Alexis N Simpkins and Pouya Tahsili-Fahadan and Natalie Buchwald and Justin De Prey and Amreen Farooqui and Luke A Mugge and Tamra Ranasinghe and Alexander J Senetar and Franklin D Echevarria and Muhammad M Alvi and Ona Wu},

doi = {10.1016/j.jstrokecerebrovasdis.2021.106059},

issn = {1532-8511},

year  = {2021},

date = {2021-11-01},

journal = {J Stroke Cerebrovasc Dis},

volume = {30},

number = {11},

pages = {106059},

abstract = {Several clinical trials have demonstrated that advanced neuroimaging can select patients for recanalization therapy in an extended time window. The favorable functional outcomes and safety profile of these studies have led to the incorporation of neuroimaging in endovascular treatment guidelines, and most recently, also extended to decision making on thrombolysis. Two randomized clinical trials have demonstrated that patients who are not amenable to endovascular thrombectomy within 4.5 hours from symptoms discovery or beyond 4.5 hours from the last-known-well time may also be safely treated with intravenous thrombolysis and have a clinical benefit above the risk of safety concerns. With the growing aging population, increased stroke incidence in the young, and the impact of evolving medical practice, healthcare and stroke systems of care need to adapt continuously to provide evidence-based care efficiently. Therefore, understanding and incorporating appropriate screening strategies is critical for the prompt recognition of potentially eligible patients for extended-window intravenous thrombolysis. Here we review the clinical trial evidence for thrombolysis for acute ischemic stroke in the extended time window and provide a review of new enrolling clinical trials that include thrombolysis intervention beyond the 4.5 hour window.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34730044,

title = {Global white matter structural integrity mediates the effect of age on ischemic stroke outcomes},

author = {Mark R Etherton and Markus D Schirmer and Maria Clara Zanon Zotin and Pamela M Rist and Gregoire Boulouis and Arne Lauer and Ona Wu and Natalia S Rost},

doi = {10.1177/17474930211055906},

issn = {1747-4949},

year  = {2021},

date = {2021-11-01},

journal = {Int J Stroke},

pages = {17474930211055906},

abstract = {BACKGROUND: The relationship of global white matter microstructural integrity and ischemic stroke outcomes is not well understood.nnAIMS: To investigate the relationship of global white matter microstructural integrity with clinical variables and functional outcomes after acute ischemic stroke.nnMETHODS: A retrospective analysis of neuroimaging data from 300 acute ischemic stroke patients with magnetic resonance imaging brain obtained within 48 hours of stroke onset and long-term functional outcomes (modified Rankin, mRS) was performed. Peak width of skeletonized mean diffusivity (PSMD), as a measure of global white matter microstructural injury, was calculated in the hemisphere contralateral to the acute infarct. Multivariable linear and logistic regression analyses were performed to identify variables associated with PSMD and excellent functional outcome (mRS < 2) at 90 days, respectively. Mediation analysis was then pursued to characterize how PSMD mediates the effect of age on acute ischemic stroke functional outcomes.nnRESULTS: White matter hyperintensity volume, age, pre-stroke disability, and normal-appearing white matter mean diffusivity were independently associated with increased PSMD. In logistic regression analysis, increased infarct volume and PSMD were independent predictors of excellent functional outcome. Additionally, the effect of age on functional outcomes was indirectly mediated by PSMD ( < 0.001).nnCONCLUSIONS: As a marker of global white matter microstructural injury, increased PSMD mediates the effect of increased age to contribute to poor acute ischemic stroke functional outcomes. PSMD could serve as a putative radiographic marker of brain age for stroke outcomes prognostication.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34078897,

title = {Outcome after acute ischemic stroke is linked to sex-specific lesion patterns},

author = {Anna K Bonkhoff and Markus D Schirmer and Martin Bretzner and Sungmin Hong and Robert W Regenhardt and Mikael Brudfors and Kathleen L Donahue and Marco J Nardin and Adrian V Dalca and Anne-Katrin Giese and Mark R Etherton and Brandon L Hancock and Steven J T Mocking and Elissa C McIntosh and John Attia and Oscar R Benavente and Stephen Bevan and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Martin Söderholm and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ramin Zand and Patrick F McArdle and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Danilo Bzdok and Ona Wu and  and Natalia S Rost},

doi = {10.1038/s41467-021-23492-3},

issn = {2041-1723},

year  = {2021},

date = {2021-06-01},

journal = {Nat Commun},

volume = {12},

number = {1},

pages = {3289},

abstract = {Acute ischemic stroke affects men and women differently. In particular, women are often reported to experience higher acute stroke severity than men. We derived a low-dimensional representation of anatomical stroke lesions and designed a Bayesian hierarchical modeling framework tailored to estimate possible sex differences in lesion patterns linked to acute stroke severity (National Institute of Health Stroke Scale). This framework was developed in 555 patients (38% female). Findings were validated in an independent cohort (n = 503, 41% female). Here, we show brain lesions in regions subserving motor and language functions help explain stroke severity in both men and women, however more widespread lesion patterns are relevant in female patients. Higher stroke severity in women, but not men, is associated with left hemisphere lesions in the vicinity of the posterior circulation. Our results suggest there are sex-specific functional cerebral asymmetries that may be important for future investigations of sex-stratified approaches to management of acute ischemic stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33650754,

title = {Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke},

author = {Anna K Bonkhoff and Markus D Schirmer and Martin Bretzner and Mark Etherton and Kathleen Donahue and Carissa Tuozzo and Marco Nardin and Anne-Katrin Giese and Ona Wu and Vince D Calhoun and Christian Grefkes and Natalia S Rost},

doi = {10.1002/hbm.25366},

issn = {1097-0193},

year  = {2021},

date = {2021-05-01},

journal = {Hum Brain Mapp},

volume = {42},

number = {7},

pages = {2278--2291},

abstract = {The aim of the current study was to explore the whole-brain dynamic functional connectivity patterns in acute ischemic stroke (AIS) patients and their relation to short and long-term stroke severity. We investigated resting-state functional MRI-based dynamic functional connectivity of 41 AIS patients two to five days after symptom onset. Re-occurring dynamic connectivity configurations were obtained using a sliding window approach and k-means clustering. We evaluated differences in dynamic patterns between three NIHSS-stroke severity defined groups (mildly, moderately, and severely affected patients). Furthermore, we built Bayesian hierarchical models to evaluate the predictive capacity of dynamic connectivity and examine the interrelation with clinical measures, such as white matter hyperintensity lesions. Finally, we established correlation analyses between dynamic connectivity and AIS severity as well as 90-day neurological recovery (ΔNIHSS). We identified three distinct dynamic connectivity configurations acutely post-stroke. More severely affected patients spent significantly more time in a configuration that was characterized by particularly strong connectivity and isolated processing of functional brain domains (three-level ANOVA: p < .05, post hoc t tests: p < .05, FDR-corrected). Configuration-specific time estimates possessed predictive capacity of stroke severity in addition to the one of clinical measures. Recovery, as indexed by the realized change of the NIHSS over time, was significantly linked to the dynamic connectivity between bilateral intraparietal lobule and left angular gyrus (Pearson's r = -.68, p = .003, FDR-corrected). Our findings demonstrate transiently increased isolated information processing in multiple functional domains in case of severe AIS. Dynamic connectivity involving default mode network components significantly correlated with recovery in the first 3 months poststroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31847795,

title = {Normal-appearing white matter microstructural injury is associated with white matter hyperintensity burden in acute ischemic stroke},

author = {Mark R Etherton and Ona Wu and Anne-Katrin Giese and Natalia S Rost},

doi = {10.1177/1747493019895707},

issn = {1747-4949},

year  = {2021},

date = {2021-02-01},

journal = {Int J Stroke},

volume = {16},

number = {2},

pages = {184--191},

abstract = {BACKGROUND: White matter hyperintensity of presumed vascular origin is a risk factor for poor stroke outcomes. In patients with acute ischemic stroke, however, the in vivo mechanisms of white matter microstructural injury are less clear.nnAIMS: To characterize the directional diffusivity components in normal-appearing white matter and white matter hyperintensity in acute ischemic stroke patients.nnMETHODS: A retrospective analysis was performed on a cohort of patients with acute ischemic stroke and brain magnetic resonance imaging with diffusion tensor imaging sequences acquired within 48 h of admission. White matter hyperintensity volume was measured in a semi-automated manner. Median fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values were calculated within normal-appearing white matter and white matter hyperintensity in the hemisphere contralateral to the acute infarct. Linear regression analysis was performed to evaluate predictors of white matter hyperintensity volume and normal-appearing white matter diffusivity metrics.nnRESULTS: In 319 patients, mean age was 64.9 ± 15.9 years. White matter hyperintensity volume was 6.33 cm (interquartile range 3.0-12.6 cm). Axial and radial diffusivity were significantly increased in white matter hyperintensity compared to normal-appearing white matter. In multivariable linear regression, age (β = 0.20,  = 0.003) and normal-appearing white matter axial diffusivity (β = 37.9,  < 0.001) were independently associated with white matter hyperintensity volume. Subsequent analysis demonstrated that increasing age (β = 0.004,  < 0.001) and admission diastolic blood pressure (β = 0.001,  = 0.02) were independent predictors of normal-appearing white matter axial diffusivity in multivariable linear regression.nnCONCLUSIONS: Normal-appearing white matter axial diffusivity increases with age and is an independent predictor of white matter hyperintensity volume in acute ischemic stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34566844,

title = {Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke},

author = {Sungmin Hong and Anne-Katrin Giese and Markus D Schirmer and Anna K Bonkhoff and Martin Bretzner and Pamela Rist and Adrian V Dalca and Robert W Regenhardt and Mark R Etherton and Kathleen L Donahue and Marco Nardin and Steven J T Mocking and Elissa C McIntosh and John Attia and Oscar R Benavente and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Jaume Roquer and Steven J Kittner and Robin Lemmens and Christopher R Levi and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Christian Enzinger and Pankaj Sharma and Agnieszka Slowik and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ramin Zand and Patrick F McArdle and Bradford B Worrall and Ona Wu and Christina Jern and Arne G Lindgren and Jane Maguire and Liisa Tomppo and Polina Golland and Natalia S Rost and },

doi = {10.3389/fneur.2021.700616},

issn = {1664-2295},

year  = {2021},

date = {2021-01-01},

journal = {Front Neurol},

volume = {12},

pages = {700616},

abstract = { To personalize the prognostication of post-stroke outcome using MRI-detected cerebrovascular pathology, we sought to investigate the association between the excessive white matter hyperintensity (WMH) burden unaccounted for by the traditional stroke risk profile of individual patients and their long-term functional outcomes after a stroke.  We included 890 patients who survived after an acute ischemic stroke from the MRI-Genetics Interface Exploration (MRI-GENIE) study, for whom data on vascular risk factors (VRFs), including age, sex, atrial fibrillation, diabetes mellitus, hypertension, coronary artery disease, smoking, prior stroke history, as well as acute stroke severity, 3- to-6-month modified Rankin Scale score (mRS), WMH, and brain volumes, were available. We defined the unaccounted WMH (uWMH) burden  modeling of expected WMH burden based on the VRF profile of each individual patient. The association of uWMH and mRS score was analyzed by linear regression analysis. The odds ratios of patients who achieved full functional independence (mRS < 2) in between trichotomized uWMH burden groups were calculated by pair-wise comparisons.  The expected WMH volume was estimated with respect to known VRFs. The uWMH burden was associated with a long-term functional outcome (β = 0.104,  < 0.01). Excessive uWMH burden significantly reduced the odds of achieving full functional independence after a stroke compared to the low and average uWMH burden [OR = 0.4, 95% CI: (0.25, 0.63),  < 0.01 and OR = 0.61, 95% CI: (0.42, 0.87),  < 0.01, respectively].  The excessive amount of uWMH burden unaccounted for by the traditional VRF profile was associated with worse post-stroke functional outcomes. Further studies are needed to evaluate a lifetime brain injury reflected in WMH unrelated to the VRF profile of a patient as an important factor for stroke recovery and a plausible indicator of brain health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34321995,

title = {MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes},

author = {Martin Bretzner and Anna K Bonkhoff and Markus D Schirmer and Sungmin Hong and Adrian V Dalca and Kathleen L Donahue and Anne-Katrin Giese and Mark R Etherton and Pamela M Rist and Marco Nardin and Razvan Marinescu and Clinton Wang and Robert W Regenhardt and Xavier Leclerc and Renaud Lopes and Oscar R Benavente and John W Cole and Amanda Donatti and Christoph J Griessenauer and Laura Heitsch and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and Christopher R Levi and Patrick F McArdle and Caitrin W McDonough and James F Meschia and Chia-Ling Phuah and Arndt Rolfs and Stefan Ropele and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Alessandro Sousa and Tara M Stanne and Daniel Strbian and Turgut Tatlisumak and Vincent Thijs and Achala Vagal and Johan Wasselius and Daniel Woo and Ona Wu and Ramin Zand and Bradford B Worrall and Jane M Maguire and Arne Lindgren and Christina Jern and Polina Golland and Grégory Kuchcinski and Natalia S Rost},

doi = {10.3389/fnins.2021.691244},

issn = {1662-4548},

year  = {2021},

date = {2021-01-01},

journal = {Front Neurosci},

volume = {15},

pages = {691244},

abstract = {OBJECTIVE: Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes.nnMETHODS: We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA).nnRESULTS: Radiomic features were predictive of WMH burden (  = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected -values     < 0.001, -value   = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes.nnCONCLUSION: Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients' brain health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33176180,

title = {Intravenous alteplase for stroke with unknown time of onset guided by advanced imaging: systematic review and meta-analysis of individual patient data},

author = {Götz Thomalla and Florent Boutitie and Henry Ma and Masatoshi Koga and Peter Ringleb and Lee H Schwamm and Ona Wu and Martin Bendszus and Christopher F Bladin and Bruce C V Campbell and Bastian Cheng and Leonid Churilov and Martin Ebinger and Matthias Endres and Jochen B Fiebach and Mayumi Fukuda-Doi and Manabu Inoue and Timothy J Kleinig and Lawrence L Latour and Robin Lemmens and Christopher R Levi and Didier Leys and Kaori Miwa and Carlos A Molina and Keith W Muir and Norbert Nighoghossian and Mark W Parsons and Salvador Pedraza and Peter D Schellinger and Stefan Schwab and Claus Z Simonsen and Shlee S Song and Vincent Thijs and Danilo Toni and Chung Y Hsu and Nils Wahlgren and Haruko Yamamoto and Nawaf Yassi and Sohei Yoshimura and Steven Warach and Werner Hacke and Kazunori Toyoda and Geoffrey A Donnan and Stephen M Davis and Christian Gerloff and },

doi = {10.1016/S0140-6736(20)32163-2},

issn = {1474-547X},

year  = {2020},

date = {2020-11-01},

journal = {Lancet},

volume = {396},

number = {10262},

pages = {1574--1584},

abstract = {BACKGROUND: Patients who have had a stroke with unknown time of onset have been previously excluded from thrombolysis. We aimed to establish whether intravenous alteplase is safe and effective in such patients when salvageable tissue has been identified with imaging biomarkers.nnMETHODS: We did a systematic review and meta-analysis of individual patient data for trials published before Sept 21, 2020. Randomised trials of intravenous alteplase versus standard of care or placebo in adults with stroke with unknown time of onset with perfusion-diffusion MRI, perfusion CT, or MRI with diffusion weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch were eligible. The primary outcome was favourable functional outcome (score of 0-1 on the modified Rankin Scale [mRS]) at 90 days indicating no disability using an unconditional mixed-effect logistic-regression model fitted to estimate the treatment effect. Secondary outcomes were mRS shift towards a better functional outcome and independent outcome (mRS 0-2) at 90 days. Safety outcomes included death, severe disability or death (mRS score 4-6), and symptomatic intracranial haemorrhage. This study is registered with PROSPERO, CRD42020166903.nnFINDINGS: Of 249 identified abstracts, four trials met our eligibility criteria for inclusion: WAKE-UP, EXTEND, THAWS, and ECASS-4. The four trials provided individual patient data for 843 individuals, of whom 429 (51%) were assigned to alteplase and 414 (49%) to placebo or standard care. A favourable outcome occurred in 199 (47%) of 420 patients with alteplase and in 160 (39%) of 409 patients among controls (adjusted odds ratio [OR] 1·49 [95% CI 1·10-2·03]; p=0·011), with low heterogeneity across studies (I=27%). Alteplase was associated with a significant shift towards better functional outcome (adjusted common OR 1·38 [95% CI 1·05-1·80]; p=0·019), and a higher odds of independent outcome (adjusted OR 1·50 [1·06-2·12]; p=0·022). In the alteplase group, 90 (21%) patients were severely disabled or died (mRS score 4-6), compared with 102 (25%) patients in the control group (adjusted OR 0·76 [0·52-1·11]; p=0·15). 27 (6%) patients died in the alteplase group and 14 (3%) patients died among controls (adjusted OR 2·06 [1·03-4·09]; p=0·040). The prevalence of symptomatic intracranial haemorrhage was higher in the alteplase group than among controls (11 [3%] vs two [<1%], adjusted OR 5·58 [1·22-25·50]; p=0·024).nnINTERPRETATION: In patients who have had a stroke with unknown time of onset with a DWI-FLAIR or perfusion mismatch, intravenous alteplase resulted in better functional outcome at 90 days than placebo or standard care. A net benefit was observed for all functional outcomes despite an increased risk of symptomatic intracranial haemorrhage. Although there were more deaths with alteplase than placebo, there were fewer cases of severe disability or death.nnFUNDING: None.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32339896,

title = {Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation},

author = {Florian Dubost and Marleen de Bruijne and Marco Nardin and Adrian V Dalca and Kathleen L Donahue and Anne-Katrin Giese and Mark R Etherton and Ona Wu and Marius de Groot and Wiro Niessen and Meike Vernooij and Natalia S Rost and Markus D Schirmer},

doi = {10.1016/j.media.2020.101698},

issn = {1361-8423},

year  = {2020},

date = {2020-07-01},

journal = {Med Image Anal},

volume = {63},

pages = {101698},

abstract = {Registration is a core component of many imaging pipelines. In case of clinical scans, with lower resolution and sometimes substantial motion artifacts, registration can produce poor results. Visual assessment of registration quality in large clinical datasets is inefficient. In this work, we propose to automatically assess the quality of registration to an atlas in clinical FLAIR MRI scans of the brain. The method consists of automatically segmenting the ventricles of a given scan using a neural network, and comparing the segmentation to the atlas ventricles propagated to image space. We used the proposed method to improve clinical image registration to a general atlas by computing multiple registrations - one directly to the general atlas and others via different age-specific atlases - and then selecting the registration that yielded the highest ventricle overlap. Finally, as an example application of the complete pipeline, a voxelwise map of white matter hyperintensity burden was computed using only the scans with registration quality above a predefined threshold. Methods were evaluated in a single-site dataset of more than 1000 scans, as well as a multi-center dataset comprising 142 clinical scans from 12 sites. The automated ventricle segmentation reached a Dice coefficient with manual annotations of 0.89 in the single-site dataset, and 0.83 in the multi-center dataset. Registration via age-specific atlases could improve ventricle overlap compared to a direct registration to the general atlas (Dice similarity coefficient increase up to 0.15). Experiments also showed that selecting scans with the registration quality assessment method could improve the quality of average maps of white matter hyperintensity burden, instead of using all scans for the computation of the white matter hyperintensity map. In this work, we demonstrated the utility of an automated tool for assessing image registration quality in clinical scans. This image quality assessment step could ultimately assist in the translation of automated neuroimaging pipelines to the clinic.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32493718,

title = {White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype},

author = {Anne-Katrin Giese and Markus D Schirmer and Adrian V Dalca and Ramesh Sridharan and Kathleen L Donahue and Marco Nardin and Robert Irie and Elissa C McIntosh and Steven J T Mocking and Huichun Xu and John W Cole and Eva Giralt-Steinhauer and Jordi Jimenez-Conde and Christina Jern and Dawn O Kleindorfer and Robin Lemmens and Johan Wasselius and Arne Lindgren and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Vincent Thijs and Bradford B Worrall and Daniel Woo and Steven J Kittner and Patrick F McArdle and Braxton D Mitchell and Jonathan Rosand and James F Meschia and Ona Wu and Polina Golland and Natalia S Rost and },

doi = {10.1212/WNL.0000000000009728},

issn = {1526-632X},

year  = {2020},

date = {2020-07-01},

journal = {Neurology},

volume = {95},

number = {1},

pages = {e79--e88},

abstract = {OBJECTIVE: To examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS).nnMETHODS: For the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool-based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes.nnRESULTS: Patients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all  < 0.001). Median WMHv in all patients with AIS was 5.86 cm (interquartile range 2.18-14.61 cm) and differed significantly across CCS subtypes ( < 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all  < 0.001), and diabetes mellitus ( = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes ( < 0.001).nnCONCLUSION: In this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32370856,

title = {Brain Volume: An Important Determinant of Functional Outcome After Acute Ischemic Stroke},

author = {Markus D Schirmer and Kathleen L Donahue and Marco J Nardin and Adrian V Dalca and Anne-Katrin Giese and Mark R Etherton and Steven J T Mocking and Elissa C McIntosh and John W Cole and Lukas Holmegaard and Katarina Jood and Jordi Jimenez-Conde and Steven J Kittner and Robin Lemmens and James F Meschia and Jonathan Rosand and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Tara M Stanne and Achala Vagal and Johan Wasselius and Daniel Woo and Stephen Bevan and Laura Heitsch and Chia-Ling Phuah and Daniel Strbian and Turgut Tatlisumak and Christopher R Levi and John Attia and Patrick F McArdle and Bradford B Worrall and Ona Wu and Christina Jern and Arne Lindgren and Jane Maguire and Vincent Thijs and Natalia S Rost and },

doi = {10.1016/j.mayocp.2020.01.027},

issn = {1942-5546},

year  = {2020},

date = {2020-05-01},

journal = {Mayo Clin Proc},

volume = {95},

number = {5},

pages = {955--965},

abstract = {OBJECTIVE: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS).nnPATIENTS AND METHODS: This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission.nnRESULTS: Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes.nnCONCLUSION: Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32132644,

title = {Identifying Severe Stroke Patients Likely to Benefit From Thrombectomy Despite Delays of up to a Day},

author = {R Gilberto González and Gisele Sampaio Silva and Julian He and Saloomeh Sadaghiani and Ona Wu and Aneesh B Singhal},

doi = {10.1038/s41598-020-60933-3},

issn = {2045-2322},

year  = {2020},

date = {2020-03-01},

journal = {Sci Rep},

volume = {10},

number = {1},

pages = {4008},

abstract = {Selected patients with large vessel occlusions (LVO) can benefit from thrombectomy up to 24 hours after onset. Identifying patients who might benefit from late intervention after transfer from community hospitals to thrombectomy-capable centers would be valuable. We searched for presentation biomarkers to identify such patients. Frequent MR imaging over 2 days of 38 untreated LVO patients revealed logarithmic growth of the ischemic infarct core. In 24 patients with terminal internal carotid artery or the proximal middle cerebral artery occlusions we found that an infarct core growth rate (IGR) <4.1 ml/hr and initial infarct core volumes (ICV) <19.9 ml had accuracies >89% for identifying patients who would still have a core of <50 ml 24 hours after stroke onset, a core size that should predict favorable outcomes with thrombectomy. Published reports indicate that up to half of all LVO stroke patients have an IGR <4.1 ml/hr. Other potentially useful biomarkers include the NIHSS and the perfusion measurements MTT and Tmax. We conclude that many LVO patients have a stroke physiology that is favorable for late intervention, and that there are biomarkers that can accurately identify them at early time points as suitable for transfer for intervention.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32670186,

title = {Diffusion-Weighted Imaging, MR Angiography, and Baseline Data in a Systematic Multicenter Analysis of 3,301 MRI Scans of Ischemic Stroke Patients-Neuroradiological Review Within the MRI-GENIE Study},

author = {Mattias Drake and Petrea Frid and Björn M Hansen and Ona Wu and Anne-Katrin Giese and Markus D Schirmer and Kathleen Donahue and Lisa Cloonan and Robert E Irie and Mark J R J Bouts and Elissa C McIntosh and Steven J T Mocking and Adrian V Dalca and Ramesh Sridharan and Huichun Xu and Eva Giralt-Steinhauer and Lukas Holmegaard and Katarina Jood and Jaume Roquer and John W Cole and Patrick F McArdle and Joseph P Broderick and Jordi Jiménez-Conde and Christina Jern and Brett M Kissela and Dawn O Kleindorfer and Robin Lemmens and James F Meschia and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Vincent Thijs and Daniel Woo and Bradford B Worrall and Steven J Kittner and Braxton D Mitchell and Jonathan Rosand and Polina Golland and Arne Lindgren and Natalia S Rost and Johan Wassélius},

doi = {10.3389/fneur.2020.00577},

issn = {1664-2295},

year  = {2020},

date = {2020-01-01},

journal = {Front Neurol},

volume = {11},

pages = {577},

abstract = { Magnetic resonance imaging (MRI) serves as a cornerstone in defining stroke phenotype and etiological subtype through examination of ischemic stroke lesion appearance and is therefore an essential tool in linking genetic traits and stroke. Building on baseline MRI examinations from the centralized and structured radiological assessments of ischemic stroke patients in the Stroke Genetics Network, the results of the MRI-Genetics Interface Exploration (MRI-GENIE) study are described in this work.  The MRI-GENIE study included patients with symptoms caused by ischemic stroke ( = 3,301) from 12 international centers. We established and used a structured reporting protocol for all assessments. Two neuroradiologists, using a blinded evaluation protocol, independently reviewed the baseline diffusion-weighted images (DWIs) and magnetic resonance angiography images to determine acute lesion and vascular occlusion characteristics.  In this systematic multicenter radiological analysis of clinical MRI from 3,301 acute ischemic stroke patients according to a structured prespecified protocol, we identified that anterior circulation infarcts were most prevalent (67.4%), that infarcts in the middle cerebral artery (MCA) territory were the most common, and that the majority of large artery occlusions 0 to 48 h from ictus were in the MCA territory. Multiple acute lesions in one or several vascular territories were common (11%). Of 2,238 patients with unilateral DWI lesions, 52.6% had left-sided infarct lateralization ( = 0.013 for χ test).  This large-scale analysis of a multicenter MRI-based cohort of AIS patients presents a unique imaging framework facilitating the relationship between imaging and genetics for advancing the knowledge of genetic traits linked to ischemic stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33193055,

title = {White Matter Hyperintensity Burden Is Associated With Hippocampal Subfield Volume in Stroke},

author = {Mark R Etherton and Panagiotis Fotiadis and Anne-Katrin Giese and Juan E Iglesias and Ona Wu and Natalia S Rost},

doi = {10.3389/fneur.2020.588883},

issn = {1664-2295},

year  = {2020},

date = {2020-01-01},

journal = {Front Neurol},

volume = {11},

pages = {588883},

abstract = {White matter hyperintensities of presumed vascular origin (WMH) are a prevalent form of cerebral small-vessel disease and an important risk factor for post-stroke cognitive dysfunction. Despite this prevalence, it is not well understood how WMH contributes to post-stroke cognitive dysfunction. Preliminary findings suggest that increasing WMH volume is associated with total hippocampal volume in chronic stroke patients. The hippocampus, however, is a complex structure with distinct subfields that have varying roles in the function of the hippocampal circuitry and unique anatomical projections to different brain regions. For these reasons, an investigation into the relationship between WMH and hippocampal subfield volume may further delineate how WMH predispose to post-stroke cognitive dysfunction. In a prospective study of acute ischemic stroke patients with moderate/severe WMH burden, we assessed the relationship between quantitative WMH burden and hippocampal subfield volumes. Patients underwent a 3T MRI brain within 2-5 days of stroke onset. Total WMH volume was calculated in a semi-automated manner. Mean cortical thickness and hippocampal volumes were measured in the contralesional hemisphere. Total and subfield hippocampal volumes were measured using an automated, high-resolution,  computational atlas. Linear regression analyses were performed for predictors of total and subfield hippocampal volumes. Forty patients with acute ischemic stroke and moderate/severe white matter hyperintensity burden were included in this analysis. Median WMH volume was 9.0 cm. Adjusting for intracranial volume and stroke laterality, age (β = -3.7,  < 0.001), hypertension (β = -44.7,  = 0.04), WMH volume (β = -0.89,  = 0.049), and mean cortical thickness (β = 286.2,  = 0.006) were associated with total hippocampal volume. In multivariable analysis, age (β = -3.3,  < 0.001) and cortical thickness (β = 205.2,  = 0.028) remained independently associated with total hippocampal volume. In linear regression for predictors of hippocampal subfield volume, increasing WMH volume was associated with decreased hippocampal-amygdala transition area volume (β = -0.04,  = 0.001). These finding suggest that in ischemic stroke patients, increased WMH burden is associated with selective hippocampal subfield degeneration in the hippocampal-amygdala transition area.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32030203,

title = {Sex-specific differences in white matter microvascular integrity after ischaemic stroke},

author = {Mark R Etherton and Ona Wu and Pedro Cougo and Svetlana Lorenzano and Hua Li and Lisa Cloonan and Mark J R J Bouts and Arne Lauer and Ken Arai and Eng H Lo and Steve K Feske and Karen L Furie and Natalia S Rost},

doi = {10.1136/svn-2019-000268},

issn = {2059-8696},

year  = {2019},

date = {2019-12-01},

journal = {Stroke Vasc Neurol},

volume = {4},

number = {4},

pages = {198--205},

abstract = {BACKGROUND AND PURPOSE: Functional outcomes after ischaemic stroke are worse in women, despite adjusting for differences in comorbidities and treatment approaches. White matter microvascular integrity represents one risk factor for poor long-term functional outcomes after ischaemic stroke. The aim of the study is to characterise sex-specific differences in microvascular integrity in individuals with acute ischaemic stroke.nnMETHODS: A retrospective analysis of subjects with acute ischaemic stroke and brain MRI with diffusion-weighted (DWI) and dynamic-susceptibility contrast-enhanced (DSC) perfusion-weighted imaging obtained within 9 hours of last known well was performed. In the hemisphere contralateral to the acute infarct, normal-appearing white matter (NAWM) microvascular integrity was measured using the  coefficient and apparent diffusion coefficient (ADC) values. Regression analyses for predictors of  coefficient, DWI volume and good outcome (90-day modified Rankin scale (mRS) score <2) were performed.nnRESULTS: 105 men and 79 women met inclusion criteria for analysis. Despite no difference in age, women had increased NAWM  coefficient (1027.4 vs 692.7×10/s; p=0.006). In women, atrial fibrillation (β=583.6; p=0.04) and increasing NAWM ADC (β=4.4; p=0.02) were associated with increased NAWM  coefficient. In multivariable regression analysis, the  coefficient was an independent predictor of DWI volume in women (β=0.007; p=0.01) but not men.nnCONCLUSIONS: In women with acute ischaemic stroke, increased NAWM  coefficient is associated with increased infarct volume and chronic white matter structural integrity. Prospective studies investigating sex-specific differences in white matter microvascular integrity are needed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30693424,

title = {White Matter Integrity and Early Outcomes After Acute Ischemic Stroke},

author = {Mark R Etherton and Ona Wu and Anne-Katrin Giese and Arne Lauer and Gregoire Boulouis and Brittany Mills and Lisa Cloonan and Kathleen L Donahue and William Copen and Pamela Schaefer and Natalia S Rost},

doi = {10.1007/s12975-019-0689-4},

issn = {1868-601X},

year  = {2019},

date = {2019-12-01},

journal = {Transl Stroke Res},

volume = {10},

number = {6},

pages = {630--638},

abstract = {Chronic white matter structural injury is a risk factor for poor long-term outcomes after acute ischemic stroke (AIS). However, it is unclear how white matter structural injury predisposes to poor outcomes after AIS. To explore this question, in 42 AIS patients with moderate to severe white matter hyperintensity (WMH) burden, we characterized WMH and normal-appearing white matter (NAWM) diffusivity anisotropy metrics in the hemisphere contralateral to acute ischemia in relation to ischemic tissue and early functional outcomes. All patients underwent brain MRI with dynamic susceptibility contrast perfusion and diffusion tensor imaging within 12 h and at day 3-5 post stroke. Early neurological outcomes were measured as the change in NIH Stroke Scale score from admission to day 3-5 post stroke. Target mismatch profile, percent mismatch lost, infarct growth, and rates of good perfusion were measured to assess ischemic tissue outcomes. NAWM mean diffusivity was significantly lower in the group with early neurological improvement (ENI, 0.79 vs. 0.82 × 10, mm/s; P = 0.02). In multivariable logistic regression, NAWM mean diffusivity was an independent radiographic predictor of ENI (β = - 17.6, P = 0.037). Median infarct growth was 118% (IQR 26.8-221.9%) despite good reperfusion being observed in 65.6% of the cohort. NAWM and WMH diffusivity metrics were not associated with target mismatch profile, percent mismatch lost, or infarct growth. Our results suggest that, in AIS patients, white matter structural integrity is associated with poor early neurological outcomes independent of ischemic tissue outcomes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31510905,

title = {Brain Connectivity Measures Improve Modeling of Functional Outcome After Acute Ischemic Stroke},

author = {Sofia Ira Ktena and Markus D Schirmer and Mark R Etherton and Anne-Katrin Giese and Carissa Tuozzo and Brittany B Mills and Daniel Rueckert and Ona Wu and Natalia S Rost},

doi = {10.1161/STROKEAHA.119.025738},

issn = {1524-4628},

year  = {2019},

date = {2019-10-01},

journal = {Stroke},

volume = {50},

number = {10},

pages = {2761--2767},

abstract = {Background and Purpose- The ability to model long-term functional outcomes after acute ischemic stroke represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brain's connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club organization, a high capacity backbone system of brain function. Methods- In a hospital-based cohort of 41 acute ischemic stroke patients, we investigated the effect of acute infarcts on the brain's prestroke rich club backbone and poststroke functional connectomes with respect to poststroke outcome. Functional connectomes were created using 3 anatomic atlases, and characteristic path-length () was calculated for each connectome. The number of rich club regions affected were manually determined using each patient's diffusion weighted image. We investigated differences in  with respect to outcome (modified Rankin Scale score; 90 days) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including number of rich club regions and  in outcome models, using linear regression and assessing the explained variance (R). Results- Of 41 patients (mean age [range]: 70 [45-89] years), 61% were male. Lower  was generally associated with better outcome. Including number of rich club regions in the backward selection models of outcome, R increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and modified Rankin Scale score. Conclusions- In this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of poststroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31484715,

title = {Disruption of the ascending arousal network in acute traumatic disorders of consciousness},

author = {Samuel B Snider and Yelena G Bodien and Marta Bianciardi and Emery N Brown and Ona Wu and Brian L Edlow},

doi = {10.1212/WNL.0000000000008163},

issn = {1526-632X},

year  = {2019},

date = {2019-09-01},

journal = {Neurology},

volume = {93},

number = {13},

pages = {e1281--e1287},

abstract = {OBJECTIVE: To determine whether ascending arousal network (AAn) connectivity is reduced in patients presenting with traumatic coma.nnMETHODS: We performed high-angular-resolution diffusion imaging in 16 patients with acute severe traumatic brain injury who were comatose on admission and in 16 matched controls. We used probabilistic tractography to measure the connectivity probability (CP) of AAn axonal pathways linking the brainstem tegmentum to the hypothalamus, thalamus, and basal forebrain. To assess the spatial specificity of CP differences between patients and controls, we also measured CP within 4 subcortical pathways outside the AAn.nnRESULTS: Compared to controls, patients showed a reduction in AAn pathways connecting the brainstem tegmentum to a region of interest encompassing the hypothalamus, thalamus, and basal forebrain. When each pathway was examined individually, brainstem-hypothalamus and brainstem-thalamus CPs, but not brainstem-forebrain CP, were significantly reduced in patients. Only 1 subcortical pathway outside the AAn showed reduced CP in patients.nnCONCLUSIONS: We provide initial evidence for the reduced integrity of axonal pathways linking the brainstem tegmentum to the hypothalamus and thalamus in patients presenting with traumatic coma. Our findings support current conceptual models of coma as being caused by subcortical AAn injury. AAn connectivity mapping provides an opportunity to advance the study of human coma and consciousness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31455665,

title = {Early molecular oxidative stress biomarkers of ischemic penumbra in acute stroke},

author = {Svetlana Lorenzano and Natalia S Rost and Muhib Khan and Hua Li and Leonardo M Batista and Aurauma Chutinet and Rebecca E Green and Tijy K Thankachan and Brenda Thornell and Alona Muzikansky and Ken Arai and Angel T Som and Loc-Duyen D Pham and Ona Wu and Gordon J Harris and Eng H Lo and Jeffrey B Blumberg and Paul E Milbury and Steven K Feske and Karen L Furie},

doi = {10.1212/WNL.0000000000008158},

issn = {1526-632X},

year  = {2019},

date = {2019-09-01},

journal = {Neurology},

volume = {93},

number = {13},

pages = {e1288--e1298},

abstract = {OBJECTIVES: To assess whether plasma biomarkers of oxidative stress predict diffusion-perfusion mismatch in patients with acute ischemic stroke (AIS).nnMETHODS: We measured plasma levels of oxidative stress biomarkers such as F2-isoprostanes (F2-isoPs), total and perchloric acid Oxygen Radical Absorbance Capacity (ORAC and ORAC), urinary levels of 8-oxo-7,8-dihydro-2'-deoxyguoanosine, and inflammatory and tissue-damage biomarkers (high-sensitivity C-reactive protein, matrix metalloproteinase-2 and -9) in a prospective study of patients with AIS presenting within 9 hours of symptom onset. Diffusion-weighted (DWI) and perfusion-weighted (PWI) MRI sequences were analyzed with a semiautomated volumetric method. Mismatch was defined as baseline mean transit time volume minus DWI volume. A percent mismatch cutoff of >20% was considered clinically significant. A stricter definition of mismatch was also used. Mismatch salvage was the region free of overlap by final infarction.nnRESULTS: Mismatch >20% was present in 153 of 216 (70.8%) patients (mean [±SD] age 69.2 ± 14.3 years, 41.2% women). Patients with mismatch >20% were more likely to have higher baseline plasma levels of ORAC ( = 0.020) and F2-isoPs ( = 0.145). Multivariate binary logistic regression demonstrated that lnF2-isoP (odds ratio [OR] 2.44, 95% confidence interval [CI] 1.19-4.98,  = 0.014) and lnORAC (OR 4.18, 95% CI 1.41-12.41,  = 0.010) were independent predictors of >20% PWI-DWI mismatch and the stricter mismatch definition, respectively. lnORAC significantly predicted mismatch salvage volume (>20% mismatch  = 0.010, stricter mismatch definition  = 0.003).nnCONCLUSIONS: Elevated hyperacute plasma levels of F2-isoP and ORAC are associated with radiographic evidence of mismatch and mismatch salvage in patients with AIS. If validated, these findings may add to our understanding of the role of oxidative stress in cerebral tissue fate during acute ischemia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31177973,

title = {Big Data Approaches to Phenotyping Acute Ischemic Stroke Using Automated Lesion Segmentation of Multi-Center Magnetic Resonance Imaging Data},

author = {Ona Wu and Stefan Winzeck and Anne-Katrin Giese and Brandon L Hancock and Mark R Etherton and Mark J R J Bouts and Kathleen Donahue and Markus D Schirmer and Robert E Irie and Steven J T Mocking and Elissa C McIntosh and Raquel Bezerra and Konstantinos Kamnitsas and Petrea Frid and Johan Wasselius and John W Cole and Huichun Xu and Lukas Holmegaard and Jordi Jiménez-Conde and Robin Lemmens and Eric Lorentzen and Patrick F McArdle and James F Meschia and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Tara M Stanne and Vincent Thijs and Achala Vagal and Daniel Woo and Stephen Bevan and Steven J Kittner and Braxton D Mitchell and Jonathan Rosand and Bradford B Worrall and Christina Jern and Arne G Lindgren and Jane Maguire and Natalia S Rost},

doi = {10.1161/STROKEAHA.119.025373},

issn = {1524-4628},

year  = {2019},

date = {2019-07-01},

journal = {Stroke},

volume = {50},

number = {7},

pages = {1734--1741},

abstract = {Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm (0.9-16.6 cm). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31147354,

title = {Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI},

author = {S Winzeck and S J T Mocking and R Bezerra and M J R J Bouts and E C McIntosh and I Diwan and P Garg and A Chutinet and W T Kimberly and W A Copen and P W Schaefer and H Ay and A B Singhal and K Kamnitsas and B Glocker and A G Sorensen and O Wu},

doi = {10.3174/ajnr.A6077},

issn = {1936-959X},

year  = {2019},

date = {2019-06-01},

journal = {AJNR Am J Neuroradiol},

volume = {40},

number = {6},

pages = {938--945},

abstract = {BACKGROUND AND PURPOSE: Accurate automated infarct segmentation is needed for acute ischemic stroke studies relying on infarct volumes as an imaging phenotype or biomarker that require large numbers of subjects. This study investigated whether an ensemble of convolutional neural networks trained on multiparametric DWI maps outperforms single networks trained on solo DWI parametric maps.nnMATERIALS AND METHODS: Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. To assess the generalizability of the approach, we applied the best-performing model to an independent Evaluation Cohort of 151 subjects. Agreement between manual and automated segmentations for identifying patients with large lesion volumes was calculated across multiple thresholds (21, 31, 51, and 70 cm).nnRESULTS: An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks ( < .001). Automated volumes correlated with manually measured volumes (Spearman ρ = 0.91,  < .001) for the independent cohort. For the task of identifying patients with large lesion volumes, agreement between manual outlines and automated outlines was high (Cohen κ, 0.86-0.90;  < .001).nnCONCLUSIONS: Acute infarcts are more accurately segmented using ensembles of convolutional neural networks trained with multiparametric maps than by using a single model trained with a solo map. Automated lesion segmentation has high agreement with manual techniques for identifying patients with large lesion volumes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30935810,

title = {Reduced Ischemic Lesion Growth with Heparin in Acute Ischemic Stroke},

author = {Eva A Rocha and Ruijun Ji and Hakan Ay and Zixiao Li and Ethem Murat Arsava and Gisele S Silva and Alma Gregory Sorensen and Ona Wu and Aneesh B Singhal},

doi = {10.1016/j.jstrokecerebrovasdis.2019.03.016},

issn = {1532-8511},

year  = {2019},

date = {2019-06-01},

journal = {J Stroke Cerebrovasc Dis},

volume = {28},

number = {6},

pages = {1500--1508},

abstract = {OBJECTIVE: The role of heparin in acute ischemic stroke is controversial. We investigated the effect of heparin on ischemic lesion growth.nnMETHODS: Data were analyzed on nonthrombolyzed ischemic stroke patients in whom diffusion-weighted imaging (DWI)/perfusion-weighted imaging (PWI) MRI was performed less than 12 hours of last known well and showed a PWI-DWI lesion mismatch, and who underwent follow-up neuroimaging at least 4 days after admission. Lesion growth was assessed by (1) absolute lesion growth and (2) percentage mismatch lost (PML). Univariate and multivariate regression analysis, and propensity score matching, were used to determine the effects of heparin on ischemic lesion growth.nnRESULTS: Of the 113 patients meeting study criteria, 59 received heparin within 24 hours. Heparin use was associated with ∼5-fold reductions in PML (3.5% versus 19.2%, P = .002) and absolute lesion growth (4.7 versus 20.5 mL, P = .009). In multivariate regression models, heparin independently predicted reduced PML (P = .04) and absolute lesion growth (P = .04) in the entire cohort, and in multiple subgroups (patients with and without proximal artery occlusion; DWI volume greater than 5 mL; cardio-embolic mechanism; DEFUSE-3 target mismatch). In propensity score matching analysis where patients were matched by admission NIHSS, DWI volume and proximal artery occlusion, heparin remained an independent predictor of PML (P = .048) and tended to predict absolute lesion growth (P = .06). Heparin treatment did not predict functional outcome at discharge or 90 days.nnCONCLUSION: Early heparin treatment in acute ischemic stroke patients with PWI-DWI mismatch attenuates ischemic lesion growth. Clinical trials with careful patient selection are warranted to investigate the potential ischemic protective effects of heparin.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30269881,

title = {Effective Reserve: A Latent Variable to Improve Outcome Prediction in Stroke},

author = {Markus D Schirmer and Mark R Etherton Md PhD and Adrian V Dalca PhD and Anne-Katrin Giese Md and Lisa Cloonan MSc and Ona Wu PhD and Polina Golland PhD and Natalia S Rost Md Mph Faan},

doi = {10.1016/j.jstrokecerebrovasdis.2018.09.003},

issn = {1532-8511},

year  = {2019},

date = {2019-01-01},

journal = {J Stroke Cerebrovasc Dis},

volume = {28},

number = {1},

pages = {63--69},

abstract = {Prediction of functional outcome after stroke based on initial presentation remains an open challenge, suggesting that an important aspect is missing from these prediction models. There exists the notion of a protective mechanism called brain reserve, which may be utilized to understand variations in disease outcome. In this work, we expand the concept of brain reserve (effective reserve) to improve prediction models of functional outcome after acute ischemic stroke (AIS). Consecutive AIS patients with acute brain magnetic resonance imaging (<48 hours) were eligible for this study. White matter hyperintensity and acute infarct volume were determined on T2 fluid attenuated inversion recovery and diffusion weighted images, respectively. Modified Rankin Scale scores were obtained at 90days poststroke. Effective reserve was defined as a latent variable using structural equation modeling by including age, systolic blood pressure, and intracranial volume measurements. Of 453 AIS patients (mean age 66.6 ± 14.7 years), 36% were male and 311 hypertensive. There was inverse association between effective reserve and 90-day modified Rankin Scale scores (path coefficient -0.18 ± 0.01, P < .01). Compared to a model without effective reserve, correlation between predicted and observed modified Rankin Scale scores improved in the effective-reserve-based model (Spearman's ρ 0.29 ± 0.18 versus 0.15 ± 0.17, P < .001). Furthermore, hypertensive patients exhibited lower effective reserve (P < 10). Using effective reserve in prediction models of stroke outcome is feasible and leads to better model performance. Furthermore, higher effective reserve is associated with more favorable functional poststoke outcome and might correspond to an overall better vascular health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31551913,

title = {Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke},

author = {Markus D Schirmer and Sofia Ira Ktena and Marco J Nardin and Kathleen L Donahue and Anne-Katrin Giese and Mark R Etherton and Ona Wu and Natalia S Rost},

doi = {10.3389/fneur.2019.00956},

issn = {1664-2295},

year  = {2019},

date = {2019-01-01},

journal = {Front Neurol},

volume = {10},

pages = {956},

abstract = { To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS).  Consecutive AIS patients ( = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression.  Of 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (OR 1.08, 95%CI 1.06-1.11; OR 1.05, 95%CI 1.03-1.07) and age (OR 1.03, 95%CI 1.01-1.05; OR 1.05, 95%CI 1.03-1.07).  In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30941083,

title = {Spatial Signature of White Matter Hyperintensities in Stroke Patients},

author = {Markus D Schirmer and Anne-Katrin Giese and Panagiotis Fotiadis and Mark R Etherton and Lisa Cloonan and Anand Viswanathan and Steven M Greenberg and Ona Wu and Natalia S Rost},

doi = {10.3389/fneur.2019.00208},

issn = {1664-2295},

year  = {2019},

date = {2019-01-01},

journal = {Front Neurol},

volume = {10},

pages = {208},

abstract = { White matter hyperintensity (WMH) is a common phenotype across a variety of neurological diseases, particularly prevalent in stroke patients; however, vascular territory dependent variation in WMH burden has not yet been identified. Here, we sought to investigate the spatial specificity of WMH burden in patients with acute ischemic stroke (AIS).  We created a novel age-appropriate high-resolution brain template and anatomically delineated the cerebral vascular territories. We used WMH masks derived from the clinical T2 Fluid Attenuated Inverse Recovery (FLAIR) MRI scans and spatial normalization of the template to discriminate between WMH volume within each subject's anterior cerebral artery (ACA), middle cerebral artery (MCA), and posterior cerebral artery (PCA) territories. Linear regression modeling including age, sex, common vascular risk factors, and TOAST stroke subtypes was used to assess for spatial specificity of WMH volume (WMHv) in a cohort of 882 AIS patients.  Mean age of this cohort was 65.23 ± 14.79 years, 61.7% were male, 63.6% were hypertensive, 35.8% never smoked. Mean WMHv was 11.58c ± 13.49 cc. There were significant differences in territory-specific, relative to global, WMH burden. In contrast to PCA territory, age (0.018 ± 0.002,  < 0.001) and small-vessel stroke subtype (0.212 ± 0.098,  < 0.001) were associated with relative increase of WMH burden within the anterior (ACA and MCA) territories, whereas male sex (-0.275 ± 0.067,  < 0.001) was associated with a relative decrease in WMHv.  Our data establish the spatial specificity of WMH distribution in relation to vascular territory and risk factor exposure in AIS patients and offer new insights into the underlying pathology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31033742,

title = {Traumatic Microbleeds in the Hippocampus and Corpus Callosum Predict Duration of Posttraumatic Amnesia},

author = {Nicole L Mazwi and Saef Izzy and Can Ozan Tan and Sergi Martinez and Mel B Glenn and Joseph T Giacino and Ona Wu and Ross Zafonte and Brian L Edlow},

doi = {10.1097/HTR.0000000000000479},

issn = {1550-509X},

year  = {2019},

date = {2019-01-01},

journal = {J Head Trauma Rehabil},

volume = {34},

number = {6},

pages = {E10--E18},

abstract = {OBJECTIVE: Radiologic predictors of posttraumatic amnesia (PTA) duration are lacking. We hypothesized that the number and distribution of traumatic microbleeds (TMBs) detected by gradient recalled echo (GRE) magnetic resonance imaging (MRI) predicts PTA duration.nnSETTING: Academic, tertiary medical center.nnPARTICIPANTS: Adults with traumatic brain injury (TBI).nnDESIGN: We identified 65 TBI patients with acute GRE MRI. PTA duration was determined with the Galveston Orientation and Amnesia Test, Orientation Log, or chart review. TMBs were identified within memory regions (hippocampus, corpus callosum, fornix, thalamus, and temporal lobe) and control regions (internal capsule and global). Regression tree analysis was performed to identify radiologic predictors of PTA duration, controlling for clinical PTA predictors.nnMAIN MEASURES: TMB distribution, PTA duration.nnRESULTS: Sixteen patients (25%) had complicated mild, 4 (6%) had moderate, and 45 (69%) had severe TBI. Median PTA duration was 43 days (range, 0-240 days). In univariate analysis, PTA duration correlated with TMBs in the corpus callosum (R = 0.29, P = .02) and admission Glasgow Coma Scale (GCS) score (R = -0.34, P = .01). In multivariate regression analysis, admission GCS score was the only significant contributor to PTA duration. However, in regression tree analysis, hippocampal TMBs, callosal TMBs, age, and admission GCS score explained 26% of PTA duration variance and distinguished a subgroup with prolonged PTA.nnCONCLUSIONS: Hippocampal and callosal TMBs are potential radiologic predictors of PTA duration.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31200151,

title = {White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts - The MRI-GENIE study},

author = {Markus D Schirmer and Adrian V Dalca and Ramesh Sridharan and Anne-Katrin Giese and Kathleen L Donahue and Marco J Nardin and Steven J T Mocking and Elissa C McIntosh and Petrea Frid and Johan Wasselius and John W Cole and Lukas Holmegaard and Christina Jern and Jordi Jimenez-Conde and Robin Lemmens and Arne G Lindgren and James F Meschia and Jaume Roquer and Tatjana Rundek and Ralph L Sacco and Reinhold Schmidt and Pankaj Sharma and Agnieszka Slowik and Vincent Thijs and Daniel Woo and Achala Vagal and Huichun Xu and Steven J Kittner and Patrick F McArdle and Braxton D Mitchell and Jonathan Rosand and Bradford B Worrall and Ona Wu and Polina Golland and Natalia S Rost and },

doi = {10.1016/j.nicl.2019.101884},

issn = {2213-1582},

year  = {2019},

date = {2019-01-01},

journal = {Neuroimage Clin},

volume = {23},

pages = {101884},

abstract = {White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29871771,

title = {Functional networks reemerge during recovery of consciousness after acute severe traumatic brain injury},

author = {Zachary D Threlkeld and Yelena G Bodien and Eric S Rosenthal and Joseph T Giacino and Alfonso Nieto-Castanon and Ona Wu and Susan Whitfield-Gabrieli and Brian L Edlow},

doi = {10.1016/j.cortex.2018.05.004},

issn = {1973-8102},

year  = {2018},

date = {2018-09-01},

journal = {Cortex},

volume = {106},

pages = {299--308},

abstract = {Integrity of the default mode network (DMN) is believed to be essential for human consciousness. However, the effects of acute severe traumatic brain injury (TBI) on DMN functional connectivity are poorly understood. Furthermore, the temporal dynamics of DMN reemergence during recovery of consciousness have not been studied longitudinally in patients with acute severe TBI. We performed resting-state functional magnetic resonance imaging (rs-fMRI) to measure DMN connectivity in 17 patients admitted to the intensive care unit (ICU) with acute severe TBI and in 16 healthy control subjects. Eight patients returned for follow-up rs-fMRI and behavioral assessment six months post-injury. At each time point, we analyzed DMN connectivity by measuring intra-network correlations (i.e. positive correlations between DMN nodes) and inter-network anticorrelations (i.e. negative correlations between the DMN and other resting-state networks). All patients were comatose upon arrival to the ICU and had a disorder of consciousness (DoC) at the time of acute rs-fMRI (9.2 ± 4.6 days post-injury): 2 coma, 4 unresponsive wakefulness syndrome, 7 minimally conscious state, and 4 post-traumatic confusional state. We found that, while DMN anticorrelations were absent in patients with acute DoC, patients who recovered from coma to a minimally conscious or confusional state while in the ICU showed partially preserved DMN correlations. Patients who remained in coma or unresponsive wakefulness syndrome in the ICU showed no DMN correlations. All eight patients assessed longitudinally recovered beyond the confusional state by 6 months post-injury and showed normal DMN correlations and anticorrelations, indistinguishable from those of healthy subjects. Collectively, these findings suggest that recovery of consciousness after acute severe TBI is associated with partial preservation of DMN correlations in the ICU, followed by long-term normalization of DMN correlations and anticorrelations. Both intra-network DMN correlations and inter-network DMN anticorrelations may be necessary for full recovery of consciousness after acute severe TBI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}