Distribution Of White Matter Hyperintensities Research Articles

The volume and the distribution of premorbid white matter hyperintensities: Impact on post-stroke aphasia.

White matter hyperintensities (WMH) are a radiological manifestation of progressive white matter integrity loss. The total volume and distribution of WMH within the corpus callosum have been associated with pathological cognitive ageing processes but have not been considered in relation to post-stroke aphasia outcomes. We investigated the contribution of both the total volume of WMH, and the extent of WMH lesion load in the corpus callosum to the recovery of language after first-ever stroke. Behavioural and neuroimaging data from individuals (N = 37) with a left-hemisphere stroke were included at the early subacute stage of recovery. Spoken language comprehension and production abilities were assessed using word and sentence-level tasks. Neuroimaging data was used to derive stroke lesion variables (volume and lesion load to language critical regions) and WMH variables (WMH volume and lesion load to three callosal segments). WMH volume did not predict variance in language measures, when considered together with stroke lesion and demographic variables. However, WMH lesion load in the forceps minor segment of the corpus callosum explained variance in early subacute comprehension abilities (t = -2.59, p = .01) together with corrected stroke lesion volume and socio-demographic variables. Premorbid WMH lesions in the forceps minor were negatively associated with early subacute language comprehension after aphasic stroke. This negative impact of callosal WMH on language is consistent with converging evidence from pathological ageing suggesting that callosal WMH disrupt the neural networks supporting a range of cognitive functions.

2 Higher White Matter Hyperintensity Load Adversely Affects Pre-Post Proximal Cognitive Training Performance in Healthy Older Adults

Objective:Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.Participants and Methods:Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.Results:RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.Conclusions:These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

Higher systolic and diastolic blood pressures in recently postmenopausal women are associated with higher white matter hyperintensity volume more than a decade later in the keeps continuation study

AbstractBackgroundWomen have higher rates of hypertension at the time of menopausal transition than men. Although elevated systolic and diastolic blood pressures (SBP and DBP) are risk factors for white matter (WM) injury both in women and men, WM hyperintensities (WMH), a marker of WM injury, are more common in women than in men after the age of 60. Thus, women may be vulnerable to the effects of elevated BP on WM integrity during menopausal transition. We investigated the association of BP in recently postmenopausal women with good cardiovascular health with WMH volume assessed 13 years later.MethodWomen (n = 212; median age = 67; range 58‐72), who were previously enrolled in a multi‐site randomized menopausal hormone therapy trial, Kronos Early Estrogen Prevention Study (KEEPS), participated in the present observational KEEPS Continuation Study. SBP and DBP were measured at KEEPS baseline (median age = 54 years; range 44‐59). Participants who were on antihypertensive medications at KEEPS baseline were excluded from the analysis (n = 34). Approximately 9 years after the end of KEEPS menopausal hormones versus placebo 4‐year interventions, WM integrity was assessed with automated WMH volume measurements from 3D‐FLAIR MRI. Associations of baseline SBP and DBP with logWMH volume measured 13 years later were tested by linear regression analyses. Model 1 was adjusted for age, study site, and total intracranial volume. Model 2 was adjusted for covariates of model 1, triglycerides, low density lipoproteins, and waist/hip ratio.ResultThe median SBP was 116 (range 83‐158) and DBP was 74 (range 56‐98). Higher SBP was associated with greater WMH volume (model 1:p = 0.005; model 2:p = 0.005). Similarly, higher DBP was associated with greater WMH volume (model 1:p = 0.008; model 2:p = 0.006) (Figure 1). Neither menopausal hormone therapies versus placebo, nor having high/low SBP (≥120/<120) modified these associations. Voxel‐based analyses demonstrate the association of BPs with the spatial distribution of WMHs (Figure 2).ConclusionHigher BPs in recently menopausal women were associated with greater WM injury more than a decade later after adjusting for CVD risk factors. Early postmenopausal stage is a critical time for BP control in women, which may reduce the risk of WM injury later in life.

White matter hyperintensities burden in the frontal regions is positively correlated to the freezing of gait in Parkinson's disease.

Previous studies have reported that white matter hyperintensities (WMHs) are associated with freezing of gait (FOG), but it is not clear whether their distribution areas have correlations with FOG in Parkinson's disease (PD) and the potential influencing factors about WMHs. Two hundred and forty-six patients with PD who underwent brain MRI were included. Participants were divided into PD with FOG (n = 111) and PD without FOG (n = 135) groups. Scheltens score was used to assess the WMHs burden in the areas of deep white matter hyperintensities (DWMHs), periventricular hyperintensities (PVHs), basal ganglia hyperintensities (BGHs), and infratentorial foci of hyperintensities (ITF). Whole brain WMHs volume was evaluated by automatic segmentation. Binary logistic regression was used to evaluate relationships between WMHs and FOG. The common cerebrovascular risk factors that may affect WMHs were evaluated by mediation analysis. There were no statistical differences between PD with and without FOG groups in whole brain WMHs volume, total Scheltens score, BGHs, and ITF. Binary logistic regression showed that the total scores of DWMHs (OR = 1.094; 95% CI, 1.001, 1.195; p = 0.047), sum scores of PVHs and DWMHs (OR = 1.080; 95% CI, 1.003, 1.164; p = 0.042), especially the DWMHs in frontal (OR = 1.263; 95% CI, 1.060, 1.505 p = 0.009), and PVHs in frontal caps (OR = 2.699; 95% CI, 1.337, 5.450; p = 0.006) were associated with FOG. Age, hypertension, and serum alkaline phosphatase (ALP) are positively correlated with scores of DWMHs in frontal and PVHs in frontal caps. These results indicate that WMHs distribution areas especially in the frontal of DWMHs and PVHs play a role in PD patients with FOG.

Distinct imaging features of cerebral small vessel disease are related to rare NOTCH3 variants (S36.002)

<h3>Objective:</h3> To investigate the longitudinal imaging features of cerebral small vessel disease (SVD) in relation to rare <i>NOTCH3</i> variants, including spatial patterns, dynamic patterns, and the interaction between the cortical atrophy and white matter lesions. <h3>Background:</h3> Previous studies reported that rare <i>NOTCH3</i> variants were identified in over 10% of the general population and the carriers have a susceptibility to heavy SVD burden. The correlating imaging characteristics deserve in-depth investigation to uncover the important genetic predisposition in age-related SVD in the general population. <h3>Design/Methods:</h3> Rare <i>NOTCH3</i> variants were identified through Whole-Exome Sequencing. The White matter hyperintensities (WMH) volume and WMH probability maps were assessed through quantitative segmentation. Brain structural volumes and vertex-wise cortex maps were obtained from the longitudinal FreeSurfer analysis suite. Between-group differences were compared through data statistical analysis of global measurements, and voxel/vertex-wise analysis of WMH maps or cortex maps. <h3>Results:</h3> A total of 1054 patients were included in the baseline analysis (13.56% rare <i>NOTCH3</i> variant carriers), while 661 included in the longitudinal analysis (13.76% rare <i>NOTCH3</i> variant carriers). We found that rare <i>NOTCH3</i> variant carriers had heavier WMH burden (1.65 vs 0.85ml, P=0.025) and more presence of lacunes (23.78% vs 14.84, P=0.010). More importantly, rare <i>NOTCH3</i> variant carriers had a distinct WMH distribution and progression pattern in periventricular areas. These features appeared more prominent in the EGFr-involving subgroup. Also, we found that rare <i>NOTCH3</i> variant carriers showed susceptibility to worse cortical atrophy (β=−0.004, SE=0.002, adjusted for age and sex). Of most interest, the progressing of frontal brain atrophy is related to WMH progression, which indicated the role of rare <i>NOTCH3</i> variant in age-related SVD and a structural network disconnection phenomenon. <h3>Conclusions:</h3> Our findings posed a distinct MRI profile of age-related SVD in rare <i>NOTCH3</i> variant carriers and shed new light on the pathogenic mechanisms of rare <i>NOTCH3</i> SNPs. <b>Disclosure:</b> Zi-Yue Liu has nothing to disclose. Feifei Zhai has nothing to disclose. Jing-Yi Liu has nothing to disclose. Yi-Jun Zhou has nothing to disclose. Mei-jun Shu has nothing to disclose. Xiaohong Huang has nothing to disclose. Fei Han has nothing to disclose. Mingli Li has nothing to disclose. Lixin Zhou has nothing to disclose. Jun Ni has nothing to disclose. Ming Yao has nothing to disclose. Shuyang Zhang has nothing to disclose. Liying Cui has nothing to disclose. Zhengyu Jin has nothing to disclose. Yi-Cheng Zhu has nothing to disclose.

Comparison of Incidental Findings of Brain Magnetic Resonance Imaging of Schizophrenia Patients, First-Episode Psychosis Patients and Healthy Controls.

It has been emphasized for a long time that neurodevelopmental and neurodegenerative processes play an important role in the etiology of schizophrenia. In this study, brain magnetic resonance imaging (MRI) of 97 patients with schizophrenia (SCH), 42 first-episode psychosis (FEP) patients, and 70 healthy controls (HC) were analyzed, and abnormal findings on brain MRI were recorded. Participant's age, gender, and brain MRI findings were recorded retrospectively. Fazekas grades evaluated the distribution of white matter hyperintensities in the brain. The mean ages of FEP, SCH, and HC were 24.8±6.3, 36.9±11.5, and 36±10.5, respectively. Generalized cerebral atrophy was higher in SCH and HC than in FEP groups, and frontoparietal atrophy was higher in the SCH group than in HC and FEP groups (p<0.001). The percentage of Fazekas Grade-1 was higher in the SCH group than HC and FEP groups (p=0.006). Additionally, the cavum veli interpositi (CVI) rate was higher in FEP and SCH groups than in the HC group (p=0.042). Although there was no significant age difference between the SCH and HC groups, the higher prevalence of generalized cerebral atrophy in the SCH group may indicate the neurodegenerative process of schizophrenia. The fact that CVI, a congenital brain anomaly, was detected more frequently in the FEP and SCH groups may suggest that schizophrenia may be associated with neurodevelopmental process.

Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts

IntroductionThe spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as “unusual”, but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. MethodsIndividual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. ResultsWMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DiscussionAggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

White Matter Lesions Predominantly Located in Deep White Matter Represent Embolic Etiology Rather Than Small Vessel Disease

We investigated the correlation between the deep distribution of white matter hyperintensity (WMH) (dWMH: WMH in deep and corticomedullary areas, with minimal periventricular WMH) and a positive agitated saline contrast echocardiography result. We retrospectively recruited participants with comprehensive dementia evaluations, an agitated saline study, and brain imaging. The participants were classified into two groups according to WMH-distributions: dWMH and dpWMH (mainly periventricular WMH with or without deep WMH.) We hypothesized that dWMH is more likely associated with embolism, whereas dpWMH is associated with small-vessel diseases. We compared the clinical characteristics, WMH-distributions, and positive rate of agitated saline studies between the two groups. Among 90 participants, 27 and 12 met the dWMH and dpWMH criteria, respectively. The dWMH-group was younger (62.2±7.5 vs. 78.9±7.3, p<0.001) and had a lower prevalence of hypertension (29.6% vs. 75%, p=0.008), diabetes mellitus (3.7% vs. 25%, p=0.043), and hyperlipidemia (33.3% vs. 83.3%, p=0.043) than the dpWMH-group. Regarding deep white matter lesions, the number of small lesions (<3 mm) was higher in the dWMH-group(10.9±9.7) than in the dpWMH-group (3.1±6.4) (p=0.008), and WMH was predominantly distributed in the border-zones and corticomedullary areas. Most importantly, the positive agitated saline study rate was higher in the dWMH-group than in the dpWMH-group (81.5% vs. 33.3%, p=0.003). The dWMH-group with younger participants had fewer cardiovascular risk factors, showed more border-zone-distributions, and had a higher agitated saline test positivity rate than the dpWMH-group, indicating that corticomedullary or deep WMH-distribution with minimal periventricular WMH suggests embolic etiologies.

Tract-based white matter hyperintensity patterns in patients with systemic lupus erythematosus using an unsupervised machine learning approach.

Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies.

Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.

White matter hyperintensities in former American football players.

The presentation, risk factors, and etiologies of white matter hyperintensities (WMH) in people exposed to repetitive head impacts are unknown. We examined the burden and distribution of WMH, and their association with years of play, age of first exposure, and clinical function in former American football players. A total of 149 former football players and 53 asymptomatic unexposed participants (all men, 45-74 years) completed fluid-attenuated inversion recovery magnetic resonance imaging, neuropsychological testing, and self-report neuropsychiatric measures. Lesion Segmentation Toolbox estimated WMH. Analyses were performed in the total sample and stratified by age 60. In older but not younger participants, former football players had greater total, frontal, temporal, and parietal log-WMH compared to asymptomatic unexposed men. In older but not younger former football players, greater log-WMH was associated with younger age of first exposure to football and worse executive function. In older former football players, WMH may have unique presentations, risk factors, and etiologies. Older but not younger former football players had greater total, frontal, temporal, and parietal lobe white matter hyperintensities (WMH) compared to same-age asymptomatic unexposed men. Younger age of first exposure to football was associated with greater WMH in older but not younger former American football players. In former football players, greater WMH was associated with worse executive function and verbal memory.

Regional white matter hyperintensities in posterior cortical atrophy and logopenic progressive aphasia

White matter hyperintensities (WMH) are markers of cerebral small vessel disease and are associated with higher risk of typical amnestic Alzheimer's disease (tAD). Little is known about the frequency and distribution of WMH in atypical variants of AD, including logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). We investigated WMHs in 75 LPA, 39 PCA, and 50 tAD patients and associations with age, beta-amyloid PET burden, and cognition. PCA had greater subcortical WMHs in right occipital, parietal, and temporal lobes compared to LPA, and greater parieto-occipital subcortical and occipital periventricular WMHs than tAD. LPA had greater subcortical WMHs in left parietal lobe and deep white matter WMHs than PCA, and greater fronto-occipital subcortical and occipital periventricular WMHs than tAD. Total WMH increased with increasing age but was not related to beta-amyloid burden. Greater WMH was associated with visuoperceptual performance in LPA and PCA after correcting for atrophy. WMH topography differs across AD variants. Further work is needed to determine whether they reflect cerebrovascular disease or regionally specific neurodegenerative changes.

Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels (‘bullseye’ parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.

Development and validation of cerebral white matter hyperintensity probability map of elderly Koreans

AbstractBackgroundAlthough previously constructed white matter hyperintensity (WMH) probability maps of healthy older adults exist, they have several limitations in representing the distribution of WMH in healthy older adults, especially Asian older adults. We developed and validated a WMH probability map (WPM) of healthy older Koreans and examined the age‐associated differences of WMH.MethodWe constructed WPM using development dataset that consisted of high‐resolution 3D fluid‐attenuated inversion recovery images of 5 age groups (60–64 years, 65–69 years, 70–74 years, 75–79 years, and 80+ years). Each age group included 30 age‐matched men and women each. We tested the validity of the WPM by comparing WMH ages estimated by the WPM and the chronological ages of 30 healthy controls, 30 hypertension patients, and 30 stroke patients.ResultOlder age groups showed a higher volume of WMH in both hemispheres (p &lt; 0.001). About 90% of the WMH were located in periventricular space in all age groups. With advancing age, the peak of the distance histogram from the ventricular wall of the periventricular WMH shifted away from the ventricular wall, while that of deep WMH shifted toward the ventricular wall. The estimated WMH ages were comparable to the chronological ages in the healthy controls, while being higher than the chronological ages in hypertension and stroke patients.ConclusionThe WPM may serve as a standard atlas in research on WMH of older adults, especially Asians.

Alzheimer's disease and cerebrovascular disease biomarkers in older adults with mild cognitive impairment or major depressive disorder

AbstractBackgroundMild Cognitive Impairment (MCI) and Major Depressive Disorder (MDD) are independently associated with increased risk of dementia. Cerebrospinal fluid (CSF) and neuroimaging biomarkers can help to elucidate the etiology of cognitive impairment. We compared CSF biomarker profiles of Alzheimer’s disease (AD) and white matter hyperintensities (WMH) across three groups: MCI, MDD, or comorbid MCI+MDD.MethodWe measured CSF total tau, p‐tau, amyloid‐β42, using a sandwich ELISA method (Innotest, Fujirebio), and calculated p‐tau/amyloid‐β42 ratio in 31 participants diagnosed with MCI (N=13), MDD (N=7), or both MCI and MDD (N=11) enrolled in the Preventing Alzheimer’s dementia with cognitive remediation plus transcranial direct current stimulation in mild cognitive impairment and depression (PACt‐MD) study. All diagnoses were made in accordance with NIA‐AA and DSM 5 criteria. Participants with p‐tau &gt; 68 pg/mL and ATI &lt; 0.8 were considered AD (+). WMH were quantified on T2‐weighted magnetic resonance images in 27 of the participants. We compared CSF AD biomarkers across diagnostic groups. We then compared cognitive performance and WMH in those with AD (+) versus AD (‐) CSF biomarkers.Result9/31 participants exhibited AD (+) CSF: 7/13 with MCI and 2/11 with MCI+MDD. Participants with AD (+) CSF showed more impairment in verbal memory, working memory, language, and overall cognition than those with AD (‐) CSF (p=0.02, p=0.04, p=0.04, and p=0.03, respectively). 26/27 (96%) participants exhibited moderate to severe WMH irrespective of diagnosis or AD biomarker status.ConclusionFew participants in our sample with MDD had an AD (+) CSF biomarker profile, despite a neurocognitive profile of MCI. All participants with AD (‐) CSF had moderate to severe WMH, including those with MDD alone. Further investigation should determine whether volume or distribution of WMH contribute to cognitive impairment or depression in MCI patients who have an AD (‐) CSF biomarker profile.

White matter hyperintensities in autopsy-confirmed frontotemporal lobar degeneration and Alzheimer\u2019s disease

BackgroundWe aimed to systematically describe the burden and distribution of white matter hyperintensities (WMH) and investigate correlations with neuropsychiatric symptoms in pathologically proven Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD).MethodsAutopsy-confirmed cases were identified from the Sunnybrook Dementia Study, including 15 cases of AD and 58 cases of FTLD (22 FTLD-TDP cases; 10 FTLD-Tau [Pick’s] cases; 11 FTLD-Tau Corticobasal Degeneration cases; and 15 FTLD-Tau Progressive Supranuclear Palsy cases). Healthy matched controls (n = 35) were included for comparison purposes. Data analyses included ANCOVA to compare the burden of WMH on antemortem brain MRI between groups, adjusted linear regression models to identify associations between WMH burden and neuropsychiatric symptoms, and image-guided pathology review of selected areas of WMH from each pathologic group.ResultsBurden and regional distribution of WMH differed significantly between neuropathological groups (F5,77 = 2.67, P’ = 0.029), with the FTLD-TDP group having the highest mean volume globally (8032 ± 8889 mm3) and in frontal regions (4897 ± 6163 mm3). The AD group had the highest mean volume in occipital regions (468 ± 420 mm3). Total score on the Neuropsychiatric Inventory correlated with bilateral frontal WMH volume (β = 0.330, P = 0.006), depression correlated with bilateral occipital WMH volume (β = 0.401, P < 0.001), and apathy correlated with bilateral frontal WMH volume (β = 0.311, P = 0.009), all corrected for the false discovery rate. Image-guided neuropathological assessment of selected cases with the highest burden of WMH in each pathologic group revealed presence of severe gliosis, myelin pallor, and axonal loss, but with no distinguishing features indicative of the underlying proteinopathy.ConclusionsThese findings suggest that WMH are associated with neuropsychiatric manifestations in AD and FTLD and that WMH burden and regional distribution in neurodegenerative disorders differ according to the underlying neuropathological processes.

Risk factors analysis according to regional distribution of white matter hyperintensities in a stroke cohort

The spectrum of distribution of white matter hyperintensities (WMH) may reflect different functional, histopathological, and etiological features. We examined the relationships between cerebrovascular risk factors (CVRF) and different patterns of WMH in MRI using a qualitative visual scale in ischemic stroke (IS) patients. We assembled clinical data and imaging findings from patients of two independent cohorts with recent IS. MRI scans were evaluated using a modified visual scale from Fazekas, Wahlund, and Van Swieten. WMH distributions were analyzed separately in periventricular (PV-WMH) and deep (D-WMH) white matter, basal ganglia (BG-WMH), and brainstem (B-WMH). Presence of confluence of PV-WMH and D-WMH and anterior-versus-posterior WMH predominance were also evaluated. Statistical analysis was performed with SPSS software. We included 618 patients, with a mean age of 72 years (standard deviation [SD] 11 years). The most frequent WMH pattern was D-WMH (73%). In a multivariable analysis, hypertension was associated with PV-WMH (odds ratio [OR] 1.79, 95% confidence interval [CI] 1.29-2.50, p = 0.001) and BG-WMH (OR 2.13, 95% CI 1.19-3.83, p = 0.012). Diabetes mellitus was significantly related to PV-WMH (OR 1.69, 95% CI 1.24-2.30, p = 0.001), D-WMH (OR 1.46, 95% CI 1.07-1.49, p = 0.017), and confluence patterns of D-WMH and PV-WMH (OR 1.62, 95% CI 1.07-2.47, p = 0.024). Hyperlipidemia was found to be independently related to brainstem distribution (OR 1.70, 95% CI 1.08-2.69, p = 0.022). Different CVRF profiles were significantly related to specific WMH spatial distribution patterns in a large IS cohort. • An observational study of WMH in a large IS cohort was assessed by a modified visual evaluation. • Different CVRF profiles were significantly related to specific WMH spatial distribution patterns. • Distinct WMH anatomical patterns could be related to different pathophysiological mechanisms.

Greater white matter hyperintensities and the association with executive function in suicide attempters with late-life depression

Late-life depression (LLD) is associated with greater risk of suicide and white matter hyperintensities (WMH), which are also found in suicide attempters regardless of age. Greater periventricular WMH are related to worse cognitive function. We investigated the spatial distribution of WMH in suicide attempters with LLD and its association with cognitive function. We recruited 114 participants with LLD (34 with history of suicide attempt and 80 without) and 47 older adult controls (individuals without LLD or history of suicide attempt). WMH were quantified by an automated segmentation algorithm and were classified into different regions. Suicide attempters with LLD had significantly higher global WMH (F3, 150 = 2.856, p = 0.039) and periventricular WMH (F3, 150 = 3.635, p = 0.014) compared to other groups. Suicide attempters with high WMH had significantly lower executive function, which could be an underlying mechanism for cognitive decline in older adults with suicidality.

Lacunar Stroke Lesion Extent and Location and White Matter Hyperintensities Evolution 1 Year Post-lacunar Stroke.

Lacunar strokes are a common type of ischemic stroke. They are associated with long-term disability, but the factors affecting the dynamic of the infarcted lesion and the brain imaging features associated with them, reflective of small vessel disease (SVD) severity, are still largely unknown. We investigated whether the distribution, volume and 1-year evolution of white matter hyperintensities (WMH), one of these SVD features, relate to the extent and location of these infarcts, accounting for vascular risk factors. We used imaging and clinical data from all patients [n = 118, mean age 64.9 (SD 11.75) years old] who presented to a regional hospital with a lacunar stroke syndrome within the years 2010 and 2013 and consented to participate in a study of stroke mechanisms. All patients had a brain MRI scan at presentation, and 88 had another scan 12 months after. Acute lesions (i.e., recent small subcortical infarcts, RSSI) were identified in 79 patients and lacunes in 77. Number of lacunes was associated with baseline WMH volume (B = 0.370, SE = 0.0939, P = 0.000174). RSSI volume was not associated with baseline WMH volume (B = 3.250, SE = 2.117, P = 0.129), but predicted WMH volume change (B = 2.944, SE = 0.913, P = 0.00184). RSSI location was associated with the spatial distribution of WMH and the pattern of 1-year WMH evolution. Patients with the RSSI in the centrum semiovale (n = 33) had significantly higher baseline volumes of WMH, recent and old infarcts, than patients with the RSSI located elsewhere [median 33.69, IQR (14.37 50.87) ml, 0.001 ≤ P ≤ 0.044]. But patients with the RSSI in the internal/external capsule/lentiform nucleus experienced higher increase of WMH volume after a year [n = 21, median (IQR) from 18 (11.70 31.54) ml to 27.41 (15.84 40.45) ml]. Voxel-wise analyses of WMH distribution in patients grouped per RSSI location revealed group differences increased in the presence of vascular risk factors, especially hypertension and recent or current smoking habit. In our sample of patients presenting to the clinic with lacunar strokes, lacunar strokes extent influenced WMH volume fate; and RSSI location and WMH spatial distribution and dynamics were intertwined, with differential patterns emerging in the presence of vascular risk factors. These results, if confirmed in wider samples, open potential avenues in stroke rehabilitation to be explored further.

Abstract P431: White-Matter Disease Burden and Cerebral Microbleeds After Extracorporeal Membrane Oxygenation Support

Introduction: Cerebral microbleeds (CMBs) have been increasingly reported in patients receiving extracorporeal membrane oxygenation (ECMO) support. Both, CMBs and cerebral white-matter disease (WMD) are thought to be a result of microvascular lipo-hyalinosis; as commonly seen in an aging brain. The pathogenesis of microbleeds after ECMO, has not yet been definitively established. We sought to examine the relationship between cerebral WMD burden and microbleeds after ECMO-support at a single tertiary referral academic hospital with high volumes of ECMO patients. Methods: All patients receiving venovenous (vv) and venoarterial (va) ECMO between January 2013 to January 2018 were retrospectively examined. The distribution of white matter hyperintensities was quantified using the Walhund age-related white matter changes (ARWMC) scale and correlated with the presence of cerebral microbleeds on brain MRI studies with Susceptibility Weighted Imaging (SWI) performed shortly after cessation of ECMO. Results: A total of 307 ECMO patients were reviewed, among whom 44 patients (vv:va= 13:31; male:female= 29:15) received at-least one MRI-brain study with SWI sequences after ECMO decannulation. The median duration of ECMO support was 4 days (range 1-25 days), with median duration from decannulation-to-MRI being 11.5 days (range 3-724 days). Microbleeds were present in 77.3% (n=34) patients, with 38.2% (n=13), 14.7% (n=5), and 47.1% (n=16) having mild (&lt;10), moderate (10-30) and severe (&gt;30) CMBs respectively. The median Walhund ARWMC score was 1 (range 0-22). Age and sex adjusted Walhund scores were not found predictive of CMB presence (p=0.578 [0.90-1.19]). Of 44 patients with at-least one post-ECMO MRI, 10 patients had a follow-up MRI scan at a median duration of 4 months (range 0.22-55 months); all of whom had unchanged CMB burden. At 10-month median clinical follow-up (range 0-76 months), none of the 34 patients with CMBs on initial MRI-study had presented with an intracranial hemorrhage. Conclusion: Development of CMBs after ECMO support is independent of microvascular lipo-hyalinosis, as estimated from cerebral white-matter disease burden. This requires further study in a larger sample-size.