BACKGROUND: The relationship of global white matter microstructural integrity and ischemic stroke outcomes is not well understood. AIMS: To investigate the relationship of global white matter microstructural integrity with clinical variables and functional outcomes after acute ischemic stroke. METHODS: 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. RESULTS: 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 (P < 0.001). CONCLUSIONS: 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.

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.

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.

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.

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales.

The purpose of this project was to evaluate white matter degeneration and its impact on hippocampal structural connectivity in patients with amnestic mild cognitive impairment, non-amnestic mild cognitive impairment and Alzheimer's disease. We estimated white matter fractional anisotropy, mean diffusivity and hippocampal structural connectivity in two independent cohorts. The ADNI cohort included 108 subjects [25 cognitively normal, 21 amnestic mild cognitive impairment, 47 non-amnestic mild cognitive impairment and 15 Alzheimer's disease]. A second cohort included 34 subjects [15 cognitively normal and 19 amnestic mild cognitive impairment] recruited in Montreal. All subjects underwent clinical and neuropsychological assessment in addition to diffusion and T1 MRI. Individual fractional anisotropy and mean diffusivity maps were generated using FSL-DTIfit. In addition, hippocampal structural connectivity maps expressing the probability of connectivity between the hippocampus and cortex were generated using a pipeline based on FSL-probtrackX. Voxel-based group comparison statistics of fractional anisotropy, mean diffusivity and hippocampal structural connectivity were estimated using Tract-Based Spatial Statistics. The proportion of abnormal to total white matter volume was estimated using the total volume of the white matter skeleton. We found that in both cohorts, amnestic mild cognitive impairment patients had 27-29% white matter volume showing higher mean diffusivity but no significant fractional anisotropy abnormalities. No fractional anisotropy or mean diffusivity differences were observed between non-amnestic mild cognitive impairment patients and cognitively normal subjects. Alzheimer's disease patients had 66.3% of normalized white matter volume with increased mean diffusivity and 54.3% of the white matter had reduced fractional anisotropy. Reduced structural connectivity was found in the hippocampal connections to temporal, inferior parietal, posterior cingulate and frontal regions only in the Alzheimer's group. The severity of white matter degeneration appears to be higher in advanced clinical stages, supporting the construct that these abnormalities are part of the pathophysiological processes of Alzheimer's disease.

Leukoaraiosis, a radiographic marker of cerebral small vessel disease detected on T2-weighted brain magnetic resonance imaging (MRI) as white matter hyperintensity (WMH), is a key contributor to the risk and severity of acute cerebral ischemia. Prior investigations have emphasized the pathophysiology of WMH development and progression; however, more recently, an association between WMH burden and functional outcomes after stroke has emerged. There is growing evidence that WMH represents macroscopic injury to the white matter and that the extent of WMH burden on MRI influences functional recovery in multiple domains following acute ischemic stroke (AIS). In this review, we discuss the current understanding of WMH pathogenesis and its impact on AIS and functional recovery.

OBJECTIVE: To evaluate the local effect of small asymptomatic infarctions detected by diffusion-weighted imaging (DWI) on white matter microstructure using longitudinal structural and diffusion tensor imaging (DTI). METHODS: Nine acute to subacute DWI lesions were identified in 6 subjects with probable cerebral amyloid angiopathy who had undergone high-resolution MRI both before and after DWI lesion detection. Regions of interest (ROIs) corresponding to the site of the DWI lesion (lesion ROI) and corresponding site in the nonlesioned contralateral hemisphere (control ROI) were coregistered to the pre- and postlesional scans. DTI tractography was additionally performed to reconstruct the white matter tracts containing the ROIs. DTI parameters (fractional anisotropy [FA], mean diffusivity [MD]) were quantified within each ROI, the 6-mm lesion-containing tract segments, and the entire lesion-containing tract bundle. Lesion/control FA and MD ratios were compared across time points. RESULTS: The postlesional scans (performed a mean 7.1 ± 4.7 months after DWI lesion detection) demonstrated a decrease in median FA lesion/control ROI ratio (1.08 to 0.93, p = 0.038) and increase in median MD lesion/control ROI ratio (0.97 to 1.17, p = 0.015) relative to the prelesional scans. There were no visible changes on postlesional high-resolution T1-weighted and fluid-attenuated inversion recovery images in 4 of 9 lesion ROIs and small (2-5 mm) T1 hypointensities in the remaining 5. No postlesional changes in FA or MD ratios were detected in the 6-mm lesion-containing tract segments or full tract bundles. CONCLUSIONS: Asymptomatic DWI lesions produce chronic local microstructural injury. The cumulative effects of these widely distributed lesions may directly contribute to small-vessel-related vascular cognitive impairment.

OBJECTIVE: To characterize the effect of white matter microstructural integrity on cerebral tissue and long-term functional outcomes after acute ischemic stroke (AIS). METHODS: Consecutive AIS patients with brain MRI acquired within 48 hours of symptom onset and 90-day modified Rankin Scale (mRS) score were included. Acute infarct volume on diffusion-weighted imaging (DWIv) and white matter hyperintensity volume (WMHv) on T2 fluid-attenuated inversion recovery MRI were measured. Median fractional anisotropy (FA), mean diffusivity, radial diffusivity, and axial diffusivity values were calculated within normal-appearing white matter (NAWM) in the hemisphere contralateral to the acute lesion. Regression models were used to assess the association between diffusivity metrics and acute cerebral tissue and long-term functional outcomes in AIS. Level of significance was set at p < 0.05 for all analyses. RESULTS: Among 305 AIS patients with DWIv and mRS score, mean age was 64.4 ± 15.9 years, and 183 participants (60%) were male. Median NIH Stroke Scale (NIHSS) score was 3 (interquartile range [IQR] 1-8), and median normalized WMHv was 6.19 cm3 (IQR 3.0-12.6 cm3). Admission stroke severity (β = 0.16, p < 0.0001) and small vessel stroke subtype (β = -1.53, p < 0.0001), but not diffusivity metrics, were independently associated with DWIv. However, median FA in contralesional NAWM was independently associated with mRS score (β = -9.74, p = 0.02), along with age, female sex, NIHSS score, and DWIv. CONCLUSIONS: FA decrease in NAWM contralateral to the acute infarct is associated with worse mRS category at 90 days after stroke. These data suggest that white matter integrity may contribute to functional recovery after stroke.