Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke.

Objective: 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. Methods: 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 via 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. Results: The expected WMH volume was estimated with respect to known VRFs. The uWMH burden was associated with a long-term functional outcome (ß = 0.104, p < 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), p < 0.01 and OR = 0.61, 95% CI: (0.42, 0.87), p < 0.01, respectively]. Conclusion: 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.

Free Water in White Matter Differentiates MCI and AD From Control Subjects.

Recent evidence shows that neuroinflammation plays a role in many neurological diseases including mild cognitive impairment (MCI) and Alzheimer's disease (AD), and that free water (FW) modeling from clinically acquired diffusion MRI (DTI-like acquisitions) can be sensitive to this phenomenon. This FW index measures the fraction of the diffusion signal explained by isotropically unconstrained water, as estimated from a bi-tensor model. In this study, we developed a simple but powerful whole-brain FW measure designed for easy translation to clinical settings and potential use as a priori outcome measure in clinical trials. These simple FW measures use a "safe" white matter (WM) mask without gray matter (GM)/CSF partial volume contamination (WM safe) near ventricles and sulci. We investigated if FW inside the WM safe mask, including and excluding areas of white matter damage such as white matter hyperintensities (WMHs) as shown on T2 FLAIR, computed across the whole white matter could be indicative of diagnostic grouping along the AD continuum. After careful quality control, 81 cognitively normal controls (NC), 103 subjects with MCI and 42 with AD were selected from the ADNIGO and ADNI2 databases. We show that MCI and AD have significantly higher FW measures even after removing all partial volume contamination. We also show, for the first time, that when WMHs are removed from the masks, the significant results are maintained, which demonstrates that the FW measures are not just a byproduct of WMHs. Our new and simple FW measures can be used to increase our understanding of the role of inflammation-associated edema in AD and may aid in the differentiation of healthy subjects from MCI and AD patients.

Specific nutrient patterns are associated with higher structural brain integrity in dementia-free older adults.

Optimal nutrition may play a beneficial role in maintaining a healthy brain. However, the relationship between nutrient intake and brain integrity is largely unknown. We investigated the association of specific nutrient dietary patterns with structural characteristics of the brain. Within the population-based Swedish National study on Aging and Care-Kungsholmen (SNAC-K), a cross-sectional study of 417 dementia-free participants aged ≥60 years who underwent structural magnetic resonance imaging (MRI) scans during 2001-2003, was carried-out. Data on dietary intake were collected using a food frequency questionnaire, from which intake of 21 nutrients was estimated. By principal component analysis, five nutrient patterns were extracted: (1) NP1 was characterized by fiber, vitamin C, E, ß-carotene, and folate [Fiber&Antioxidants], (2) NP2 by eicosapentaenoic (EPA, 20:5 ω-3) and docosahexaenoic (DHA, 22:6 ω-3) polyunsaturated fatty acids (PUFAs), proteins, cholesterol, vitamin B3, B12, and D [long chain (LC) ω-3PUFAs&Proteins], (3) NP3 by α-linoleic (18:2 ω-6) and α-linolenic (18:3 ω-3) PUFAs, monounsaturated fatty acids (MUFAs), and vitamin E [MUFAs&ω-3,6PUFAs], (4) NP4 by saturated fatty acids (SFAs), trans fats, MUFAs, and cholesterol [SFAs&Trans fats], (5) NP5 by B-vitamins, retinol, and proteins [B-Vitamins&Retinol]. Nutrient patterns scores were tertiled with the lowest tertile as reference, and were related to total brain volume (TBV) and white matter hyperintensities volume (WMHV) using linear regression models adjusting for potential confounders. In the multi-adjusted model, compared to the lowest intake for each pattern, the highest intake of NP1 (ß = 11.11, P = 0.009), NP2 (ß = 7.47, P = 0.052), and NP3 (ß = 10.54, P = 0.005) was associated with larger TBV whereas NP5 was related to smaller TBV (ß = -12.82, P = 0.001). The highest intake of NP1 was associated with lower WMHV (ß = -0.32, P = 0.049), whereas NP4 was associated with greater WMHV (ß = 0.31, P = 0.036). In sum, our results suggest that the identified brain-health specific nutrient combinations characterized by higher intake of fruit, vegetables, legumes, olive and seed oils, fish, lean red meat, poultry and low in milk and dairy products, cream, butter, processed meat and offal, were strongly associated with greater brain integrity among older adults.

Global White Matter Hypoperfusion on CT Predicts Larger Infarcts and Hemorrhagic Transformation after Acute Ischemia.

INTRODUCTION: Presence of white matter hyperintensity (WMH) on MRI is a marker of cerebral small vessel disease and is associated with increased small vessel stroke and increased risk of hemorrhagic transformation (HT) after thrombolysis. AIM: We sought to determine whether white matter hypoperfusion (WMHP) on perfusion CT (CTP) was related to WMH, and if WMHP predisposed to acute lacunar stroke subtype and HT after thrombolysis. METHODS: Acute ischemic stroke patients within 12 h of symptom onset at 2 centers were prospectively recruited between 2011 and 2013 for the International Stroke Perfusion Imaging Registry. Participants routinely underwent baseline CT imaging, including CTP, and follow-up imaging with MRI at 24 h. RESULTS: Of 229 ischemic stroke patients, 108 were Caucasians and 121 Chinese. In the contralateral white matter, patients with acute lacunar stroke had lower cerebral blood flow (CBF) and cerebral blood volume (CBV), compared to those with other stroke subtypes (P = 0.041). There were 46 patients with HT, and WMHP was associated with increased risk of HT (R(2) = 0.417, P = 0.002). Compared to previously reported predictors of HT, WMHP performed better than infarct core volume (R(2) = 0.341, P = 0.034), very low CBV volume (R(2) = 0.249, P = 0.026), and severely delayed perfusion (Tmax>14 second R(2) = 0.372, P = 0.011). Patients with WMHP also had larger acute infarcts and increased infarct growth compared to those without WMHP (mean 28 mL vs. 13 mL P < 0.001). CONCLUSION: White matter hypoperfusion remote to the acutely ischemic region on CTP is a marker of small vessel disease and was associated with increased HT, larger acute infarct cores, and greater infarct growth.