White matter hyperintensity burden and collateral circulation in acute ischemic stroke with large artery occlusion.

OBJECTIVE: This study aimed to investigate the association between white matter hyperintensity (WMH) burden and pial collaterals in acute strokes caused by intracranial large artery occlusion treated with mechanical thrombectomy in the anterior circulation, focusing on stroke subtypes. METHODS: Consecutive patients undergoing mechanical thrombectomy between December 2019 and June 2022 were retrospectively screened. The Fazekas scale assessed WMH burden. Pial collaterals were categorized as either poor (0-2) or good (3-4) based on the Higashida score. A multivariable analysis was used to determine the relationship between WMH burden and pial collaterals. Subgroup analyses delved into associations stratified by stroke subtypes, namely cardioembolism (CE), tandem lesions (TLs), and intracranial atherosclerosis (ICAS). RESULTS: Of the 573 patients included, 274 (47.8%) demonstrated poor pial collaterals. Multivariable regression indicated a strong association between extensive WMH burden (Fazekas score of 3-6) and poor collaterals [adjusted OR 3.04, 95% CI 1.70-5.46, P < 0.001]. Additional independent predictors of poor collaterals encompassed ICAS-related occlusion (aOR 0.26, 95% CI 0.09-0.76, P = 0.014), female sex (aOR 0.63, 95% CI 0.41-0.96, P = 0.031), and baseline Alberta Stroke Program Early Computed Tomography scores (aOR 0.80, 95% CI 0.74-0.88, P < 0.001). Notably, an interaction between extensive WMH burden and stroke subtypes was observed in predicting poor collaterals (P = 0.001), being pronounced for CE (adjusted OR 2.30, 95% CI 1.21-4.37) and TLs (adjusted OR 5.09, 95% CI 2.32-11.16), but was absent in ICAS (adjusted OR 1.24, 95% CI 0.65-2.36). CONCLUSIONS: Among patients treated with mechanical thrombectomy for anterior circulation large artery occlusion, extensive WMH burden correlates with poor pial collaterals in embolic occlusion cases (CE and TLs), but not in ICAS-related occlusion.

Disconnection of Network Hubs Underlying the Executive Function Deficit in Patients with Ischemic Leukoaraiosis.

BACKGROUND: Cognitive impairment is the most common clinical manifestation of ischemic leukoaraiosis (ILA), but the underlying neurobiological pathways have not been well elucidated. Recently, it was thought that ILA is a "disconnection syndrome". Disorganized brain connectome were considered the key neuropathology underlying cognitive deficits in ILA patients. OBJECTIVE: We aimed to detect the disruption of network hubs in ILA patients using a new analytical method called voxel-based eigenvector centrality (EC) mapping. METHODS: Subjects with moderate to severe white matters hyperintensities (Fazekas score ≥3) and healthy controls (HCs) (Fazekas score = 0) were included in the study. The resting-state functional magnetic resonance imaging and the EC mapping approach were performed to explore the alteration of whole-brain network connectivity in ILA patients. RESULTS: Relative to the HCs, the ILA patients exhibited poorer cognitive performance in episodic memory, information processing speed, and executive function (all ps < 0.0125). Additionally, compared with HCs, the ILA patients had lower functional connectivity (i.e., EC values) in the medial parts of default-mode network (i.e., bilateral posterior cingulate gyrus and ventral medial prefrontal cortex [vMPFC]). Intriguingly, the functional connectivity strength at the right vMPFC was positively correlated with executive function deficit in the ILA patients. CONCLUSION: The findings suggested disorganization of the hierarchy of the default-mode regions within the whole-brain network in patients with ILA and advanced our understanding of the neurobiological mechanism underlying executive function deficit in ILA.

Effect of leukoaraiosis on collateral circulation in acute ischemic stroke treated with endovascular therapy: a meta-analysis.

BACKGROUND AND OBJECTIVE: The recruitment of collateral circulation correlates with a balance of the microvasculature. Uncertainty remains to be made about the association of leukoaraiosis with leptomeningeal collaterals. To explore the effect of leukoaraiosis on leptomeningeal collaterals in patients treated with endovascular therapy. METHODS: Observational studies exploring the correlation between leukoaraiosis and leptomeningeal collaterals in large vessel occlusion treated with endovascular therapy were searched from PubMed, EMBASE, and Cochrane Libraries databases. Two independent reviewers retrieved eligible literature, extracted purpose-related data, and utilized the Newcastle-Ottawa Scale to evaluate the risk of bias. A Mantel-Haenszel method was used to calculate the odds ratio (OR). Meta-regression and subgroup analyses were conducted to clarify heterogeneity. RESULTS: Data from 10 studies with 1606 patients were extracted for pooled analysis. Compared to non-severe leukoaraiosis, patients with severe leukoaraiosis showed significant relevance to poor leptomeningeal collaterals (OR, 2.13; 95% confidence interval [1.27-3.57]; P = 0.004). Meta-regression indicated that sample size (coefficient = -0.007299, P = 0.035) and the number of female patients (coefficient = -0.0174709, P = 0.020) were sources of heterogeneity. Furthermore, all of the countries (USA versus France versus China, Q = 3.67, P = 0.159), various assessment scales of leukoaraiosis (the Fazekas scale versus Non-Fazekas scales, Q = 0.77, P = 0.379), and different imaging methods of leukoaraiosis (computed tomography versus magnetic resonance imaging, Q = 2.12, P = 0.146) and leptomeningeal collaterals (computed tomography angiography versus digital subtraction angiography, Q = 1.21, P = 0.271) showed no contribution to the effect size. CONCLUSION: Severe leukoaraiosis is associated with poor leptomeningeal collaterals in patients treated with endovascular therapy. Further studies may focus on whether the finding applies to different stroke subtypes.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography.

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Pre-existing brain damage and association between severity and prior cognitive impairment in ischemic stroke patients.

BACKGROUND: We evaluated whether pre-existing brain damage may explain greater severity in cognitively-impaired patients with ischemic stroke (IS). METHODS: IS patients were retrieved from the population-based registry of Dijon, France. Pre-existing damage (leukoaraiosis, old vascular brain lesions, cortical and central brain atrophy) was assessed on initial CT-scan. Association between prestroke cognitive status defined as no impairment, mild cognitive impairment (MCI), or dementia, and clinical severity at IS onset assessed with the NIHSS score was evaluated using ordinal regression analysis. Mediation analysis was performed to assess pre-existing brain lesions as mediators of the relationship between cognitive status and severity. RESULTS: Among the 916 included patients (mean age 76.8 ± 15.0 years, 54.3% women), those with pre-existing MCI (n = 115, median NIHSS [IQR]: 6 [2-15]) or dementia (n = 147, median NIHSS: 6 [3-15]) had a greater severity than patients without (n = 654, median NIHSS: 3 [1-9]) in univariate analysis (OR=1.69; 95% CI: 1.18-2.42, p = 0.004, and OR=2.06; 95% CI: 1.49-2.84, p < 0.001, respectively). Old cortical lesion (OR=1.53, p = 0.002), central atrophy (OR=1.41, p = 0.005), cortical atrophy (OR=1.90, p < 0.001) and moderate (OR=1.41, p = 0.005) or severe (OR=1.84, p = 0.002) leukoaraiosis were also associated with greater severity. After adjustments, pre-existing MCI (OR=1.52; 95% CI: 1.03-2.26, p = 0.037) or dementia (OR=1.94; 95% CI: 1.32-2.86, p = 0.001) remained associated with higher severity at IS onset, independently of confounding factors including imaging variables. Association between cognitive impairment and severity was not mediated by pre-existing visible brain damages. CONCLUSION: Impaired brain ischemic tolerance in IS patients with prior cognitive impairment could involve other mechanisms than pre-existing visible brain damage.

White matter hyperintensity presence, quantity, and location exhibits no association with motor and non-motor manifestations of PD.

INTRODUCTION: Nonspecific areas of brain white matter hyperintensity (WMH) are commonly found in the elderly. Some studies have shown that the presence, quantity, and location of WMHs may be associated with the development of cognitive and motor decline in patients with Parkinson's disease (PD), but the results remain controversial. This study aimed to evaluate the relationship of WMH to motor and non-motor symptoms, including dysautonomia and rapid eye movement sleep behavior disorder (RBD), in patients with PD. METHODS: Brain magnetic resonance images were acquired from 120 patients diagnosed with PD and analyzed for WMH classification and quantification. Motor symptoms were quantified using sub-scores of the Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS)-III. Dysautonomia was evaluated by autonomic reactivity tests, and polysomnography was used for the diagnosis of RBD. RESULTS: Age, total value of the MDS-UPDRS-III tremor sub-score, and the presence of dysautonomia were found to be linearly positively associated. Specifically, the duration of PD was positively associated with rigidity, bradykinesia, axial symptoms, prevalence of dysautonomia, and RBD sub-scores. However, in the multivariate analysis adjusted for variables of interest, no statistical significance was found for any of the models. CONCLUSION: The presence, quantity, and location of WMH were not associated with the analyzed motor and non-motor manifestations of PD.

Parietal and occipital leukoaraiosis due to cerebral ischaemic lesions decrease the driving safety performance of healthy older adults.

Leukoaraiosis, a common ischaemic lesion diagnosed using magnetic resonance imaging (MRI), can influence driving safety performance (DSP). Most older drivers with leukoaraiosis are unaware of their affliction. Japan is a super-aged country, where preventing accidents caused by older drivers is an urgent national issue. We investigated the subcortical and periventricular leukoaraiosis regions that were most involved in DSP decline. The driving skills of 101 drivers (49 men, 52 women; mean age, 77.88 ± 3.77 years) without dementia were assessed by official driving instructors, using actual vehicles on a closed-circuit course. Parietal and occipital (but not frontal or temporal) leukoaraiosis volumes were significantly correlated with decreased DSP scores regardless of age, especially when turning right at intersections, which needs more attention than turning left because left-side driving is legally enforced in Japan. Occipital leukoaraiosis was also involved via a decline in dynamic visual cognitive function. MRI-based assessment of leukoaraiosis volume and localisation may enable the identification of older drivers prone to DSP deterioration. Risk factors for leukoaraiosis include smoking and lifestyle-related diseases such as hypertension. Thus, brain healthcare in patients with MRI-diagnosed leukoaraiosis may be particularly useful for the risk management of traffic accidents caused by the elderly in Japan.

White matter hyperintensity load is associated with premature brain aging.

BACKGROUND: Brain age is an MRI-derived estimate of brain tissue loss that has a similar pattern to aging-related atrophy. White matter hyperintensities (WMHs) are neuroimaging markers of small vessel disease and may represent subtle signs of brain compromise. We tested the hypothesis that WMHs are independently associated with premature brain age in an original aging cohort. METHODS: Brain age was calculated using machine-learning on whole-brain tissue estimates from T1-weighted images using the BrainAgeR analysis pipeline in 166 healthy adult participants. WMHs were manually delineated on FLAIR images. WMH load was defined as the cumulative volume of WMHs. A positive difference between estimated brain age and chronological age (BrainGAP) was used as a measure of premature brain aging. Then, partial Pearson correlations between BrainGAP and volume of WMHs were calculated (accounting for chronological age). RESULTS: Brain and chronological age were strongly correlated (r(163)=0.932, p<0.001). There was significant negative correlation between BrainGAP scores and chronological age (r(163)=-0.244, p<0.001) indicating that younger participants had higher BrainGAP (premature brain aging). Chronological age also showed a positive correlation with WMH load (r(163)=0.506, p<0.001) indicating older participants had increased WMH load. Controlling for chronological age, there was a statistically significant relationship between premature brain aging and WMHs load (r(163)=0.216, p=0.003). Each additional year in brain age beyond chronological age corresponded to an additional 1.1mm3 in WMH load. CONCLUSIONS: WMHs are an independent factor associated with premature brain aging. This finding underscores the impact of white matter disease on global brain integrity and progressive age-like brain atrophy.

Chronic cerebral infarctions and white matter lesions link to long-term survival after a first ischemic event: A cohort study.

BACKGROUND AND PURPOSE: To investigate the association of different phenotypes, count, and locations of chronic covert brain infarctions (CBI) with long-term mortality in patients with first-ever manifest acute ischemic stroke (AIS) or transient ischemic attack (TIA). Additionally, to analyze their potential interaction with white matter hyperintensities (WMH) and predictive value in addition to established mortality scores. METHODS: Single-center cohort study including consecutive patients with first-ever AIS or TIA with available MRI imaging from January 2015 to December 2017. Blinded raters adjudicated CBI phenotypes and WMH (age-related white matter changes score) according to established definitions. We compared Cox regression models including prespecified established predictors of mortality using Harrell's C and likelihood ratio tests. RESULTS: A total of 2236 patients (median [interquartile range] age: 71 [59-80] years, 43% female, National Institutes of Health Stroke Scale: 2 [1-6], median follow-up: 1436 days, 21% death during follow-up) were included. Increasing WMH (per point adjusted Hazard Ratio [aHR] = 1.29 [1.14-1.45]), but not CBI (aHR = 1.21 [0.99-1.49]), were independently associated with mortality. Neither CBI phenotype, count, nor location was associated with mortality and there was no multiplicative interaction between CBI and WMH (p > .1). As compared to patients without CBI or WMH, patients with moderate or severe WMH and additional CBI had the highest hazards of death (aHR = 1.62 [1.23-2.13]). The Cox regression model including CBI and WMH had a small but significant increment in Harrell's C when compared to the model including 14 clinical variables (0.831 vs. 0.827, p < .001). DISCUSSION: WMH represent a strong surrogate biomarker of long-term mortality in first-ever manifest AIS or TIA patients. CBI phenotypes, count, and location seem less relevant. Incorporation of CBI and WMH slightly improves predictive capacity of established risk scores.

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome.

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. METHODS: 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, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts. RESULTS: 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. DISCUSSION: 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.

Quantitative Analysis of White Matter Hyperintensity: Comparison of Magnetic Resonance Imaging Image Analysis Software.

OBJECTIVE: White matter hyperintensity (WMH), defined as abnormal signals on magnetic resonance imaging (MRI), is an important clinical indicator of aging and dementia. Although MRI image analysis software can automatically detect WMH, the quantitative accuracy of periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH) is unknown. MATERIALS AND METHODS: This study was a sub-analysis of MRI data from an ongoing hospital-based prospective cohort study (the Gimlet study). Between March 2016 and March 2017, we enrolled patients who visited our memory clinic and agreed to undergo medical assessments of cognitive function and fecal examination to study the gut microbiome. Participants with a history of stroke were excluded. WMH was independently quantitatively analyzed using two MRI imaging analysis software modalities: SNIPER and FUSION. Intraclass correlation coefficients and the mean difference in volume were calculated and compared between modalities. RESULTS: The data of 87 patients (49 women, mean age 74.8 ± 7.9 years) were analyzed. Both total WMH and DWMH volumes obtained using FUSION were greater (p < 0.001), and PVH volume was smaller (p < 0.001) than those obtained using SNIPER. Intraclass correlation coefficients for the lesion measurements of WMH, PVH, and DWMH between the different software were 0.726 (p < 0.001), 0.673 (p < 0.001), and 0.048 (p = 0.231), respectively. CONCLUSIONS: There were significant differences in the quantitative data of WMH between the two MRI imaging analysis software modalities. Thus, care should be taken for quantitative assessments of WMH.

Tract-specific white matter microstructural alterations in subjects with schizophrenia and unaffected first-degree relatives.

White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.

Cognitive profile in idiopathic autonomic failure: relation with white matter hyperintensities and neurofilament levels.

OBJECTIVE: To disclose the nature of cognitive deficits in a cohort of patients with idiopathic autonomic failure (IAF) by exploring the relation among cognitive functions, cardiovascular autonomic failure (AF) and clinical progression to another α-synucleinopathy (phenoconversion). METHODS: We retrospectively identified all patients with a clinical diagnosis of IAF who underwent a comprehensive neuropsychological evaluation, clinical examination and cardiovascular autonomic tests from the IAF-BO cohort. Brain magnetic resonance imaging (MRI) studies and cerebrospinal fluid (CSF) analysis, including neurofilament light chain (NfL), Alzheimer disease core biomarkers, and α-synuclein seeding activity were further evaluated when available. Correlations among cognitive functions, clinical features, cardiovascular AF, cerebral white matter hyperintensities (WMH) load, and CSF biomarkers were estimated using Spearman correlation coefficient. RESULTS: Thirteen out of 30 (43%) patients with IAF displayed cognitive deficits (CI) mainly concerning executive functioning. Seven out of 30 (23%) met the criteria for mild cognitive impairment (MCI). The diagnosis of CI and MCI was not associated with phenoconversion or autonomic function parameters, including duration and severity of neurogenic orthostatic hypotension, presence and severity of supine hypertension, and nocturnal dipper profile. Twenty patients underwent a brain MRI and CSF analysis. MCI was related to WMH load (r = 0.549) and NfL levels (r = 0.656), while autonomic function parameters were not associated with either WMH or NfL levels. INTERPRETATION: Cardiovascular AF and phenoconversion, underlying the spreading of neurodegeneration to the central nervous system, were not independent drivers of cognitive dysfunction in IAF. We identified WMH load and NfL levels as potential biomarkers of the neural network disruption associated with cognitive impairment in patients with IAF.

APOE4 and Confluent White Matter Hyperintensities Have a Synergistic Effect on Episodic Memory Impairment in Prodromal Dementia.

BACKGROUND: White matter hyperintensities (WMH) are a known risk factor for cognitive decline. While the ɛ4 allele of apolipoprotein E gene (APOE4) is another risk factor for cognitive decline, it remains unclear how APOE4 affects the relationship between WMH and cognitive decline, specifically in the prodromal stage of dementia. OBJECTIVE: To determine how APOE4 moderates the relationship between WMH and cognition in prodromal dementia. METHODS: Two-hundred-sixteen participants with prodromal dementia underwent magnetic resonance imaging (MRI), neuropsychological testing (global and domain wise), cardiovascular risk factor assessments, and APOE genotyping. Visual ratings for WMH as well as total and lobar WMH volumes were quantified. Moderation analysis was performed to determine the influence of APOE4 on the relationship between WMH and performance on global and domain-specific cognitive measures. The role of confluent and non-confluent WMH on cognition was additionally studied using logistic regression. RESULTS: APOE4 carriers (n = 49) had poorer memory and higher global WMH (10.01 mL versus 6.23 mL, p = 0.04), temporal WMH (1.17 mL versus 0.58 mL, p = 0.01), and occipital WMH (0.38mL versus 0.22 mL, p = 0.02) compared to APOE4 non-carriers (n = 167). Moderation analysis revealed that APOE4 positivity strengthened the relationship between higher global as well as lobar WMH burden and poorer episodic memory. Furthermore, APOE4 carriers with confluent WMH were 4.81 times more likely to have impaired episodic memory compared to non-confluent WMH and non-APOE carriers. CONCLUSION: The impact of WMH on memory may be strongest among APOE4 carriers. Clinicians targeting WMH would need to consider the APOE4 allele and WMH severity status to strategize cognitive interventions.

Associations of white matter hyperintensities with networks of gray matter blood flow and volume in midlife adults: A coronary artery risk development in young adults magnetic resonance imaging substudy.

White matter hyperintensities (WMHs) are emblematic of cerebral small vessel disease, yet effects on the brain have not been well characterized at midlife. Here, we investigated whether WMH volume is associated with brain network alterations in midlife adults. Two hundred and fifty-four participants from the Coronary Artery Risk Development in Young Adults study were selected and stratified by WMH burden into Lo-WMH (mean age = 50 ± 3.5 years) and Hi-WMH (mean age = 51 ± 3.7 years) groups of equal size. We constructed group-level covariance networks based on cerebral blood flow (CBF) and gray matter volume (GMV) maps across 74 gray matter regions. Through consensus clustering, we found that both CBF and GMV covariance networks partitioned into modules that were largely consistent between groups. Next, CBF and GMV covariance network topologies were compared between Lo- and Hi-WMH groups at global (clustering coefficient, characteristic path length, global efficiency) and regional (degree, betweenness centrality, local efficiency) levels. At the global level, there were no between-group differences in either CBF or GMV covariance networks. In contrast, we found between-group differences in the regional degree, betweenness centrality, and local efficiency of several brain regions in both CBF and GMV covariance networks. Overall, CBF and GMV covariance analyses provide evidence that WMH-related network alterations are present at midlife.

Cerebral and cerebellar white matter tract alterations in patients with Pantothenate Kinase-Associated Neurodegeneration (PKAN).

BACKGROUND: To examine structural connectivity of white matter tracts in patients with Pantothenate Kinase-Associated Neurodegeneration (PKAN) dystonia and identify those ones which correlate negatively to severity of symptoms. METHODS: In a group of 41 patients suffering from PKAN dystonia and an age- and gender-matched control group, white matter tractography was carried out, based on diffusion tensor imaging magnetic resonance data. Postprocessing included assessment of Quantitative Anisotropy (QA) using q-space diffeomorphic reconstruction in order to reduce influence of iron accumulation in globus pallidus of patients. RESULTS: Whole brain tractography presented significantly reduced QA values in patients (0.282 ± 0.056, as compared to controls (0.325 ± 0.046, p < 0.001). 9 fiber clusters of tracts correlated negatively to the dystonia score of patients: the middle cerebellar peduncle and the tracts of both cerebellar hemispheres as well as corpus callosum, forceps minor, the superior cortico-striate tracts and the superior thalamic radiations of both cerebral hemispheres (False Discovery Rate FDR = 0.041). CONCLUSION: The finding of a reduced global structural connectivity within the white matter and of negative correlation of motor system-related tracts, mainly those between the basal ganglia, cortical areas and the cerebellum, fits well to the concept of a general functional disturbance of the motor system in PKAN.

Associations between white matter hyperintensities, striatal dopamine loss, and cognition in drug-naïve Parkinson's disease.

INTRODUCTION: This study investigated the relationship between white matter hyperintensities (WMHs), nigrostriatal dopamine deficits, and cognitive decline in patients with drug-naïve early-stage Parkinson's disease (PD). METHOD: This cross-sectional study enrolled 309 non-demented patients with de novo PD who underwent [18F] N-(3-fluoropropyl)-2ß-carbonethoxy-3ß-(4-iodophenyl) nortropane positron emission tomography, brain magnetic resonance imaging, and a detailed neuropsychological test at baseline. We quantified dopamine transporter (DAT) availability in each striatal sub-region and applied the Scheltens scale to assess the severity of periventricular and deep WMHs. The relationships between WMHs, DAT availability, and cognition in PD were assessed using multivariate linear regression and mediation analyses while adjusting for age at parkinsonian symptom onset, sex, disease duration, and vascular risk factors. RESULTS: The severities of periventricular and frontal WMHs were associated with striatal DAT availability. Periventricular WMHs affected the level of cognitive performance in all cognitive domains, while frontal WMHs affected the attention/working memory and frontal/executive function domains. The effects of WMHs on attention/working memory and frontal/executive dysfunction were mostly direct with minimal mediating effects through striatal DAT availability. Meanwhile, striatal DAT availability fully mediated the association between WMHs and cognitive impairment in the visuospatial and memory function domains. CONCLUSION: This study demonstrated the different effects of WMHs on cognitive impairment depending on the cognitive domains in PD. These findings suggest a close link between comorbid WMHs, striatal dopamine depletion, and cognition in patients with PD.

Validation of an automatic tool for the rapid measurement of brain atrophy and white matter hyperintensity: QyScore®.

OBJECTIVES: QyScore® is an imaging analysis tool certified in Europe (CE marked) and the US (FDA cleared) for the automatic volumetry of grey and white matter (GM and WM respectively), hippocampus (HP), amygdala (AM), and white matter hyperintensity (WMH). Here we compare QyScore® performances with the consensus of expert neuroradiologists. METHODS: Dice similarity coefficient (DSC) and the relative volume difference (RVD) for GM, WM volumes were calculated on 50 3DT1 images. DSC and the F1 metrics were calculated for WMH on 130 3DT1 and FLAIR images. For each index, we identified thresholds of reliability based on current literature review results. We hypothesized that DSC/F1 scores obtained using QyScore® markers would be higher than the threshold. In contrast, RVD scores would be lower. Regression analysis and Bland-Altman plots were obtained to evaluate QyScore® performance in comparison to the consensus of three expert neuroradiologists. RESULTS: The lower bound of the DSC/F1 confidence intervals was higher than the threshold for the GM, WM, HP, AM, and WMH, and the higher bounds of the RVD confidence interval were below the threshold for the WM, GM, HP, and AM. QyScore®, compared with the consensus of three expert neuroradiologists, provides reliable performance for the automatic segmentation of the GM and WM volumes, and HP and AM volumes, as well as WMH volumes. CONCLUSIONS: QyScore® represents a reliable medical device in comparison with the consensus of expert neuroradiologists. Therefore, QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases. KEY POINTS: • QyScore® provides reliable automatic segmentation of brain structures in comparison with the consensus of three expert neuroradiologists. • QyScore® automatic segmentation could be performed on MRI images using different vendors and protocols of acquisition. In addition, the fast segmentation process saves time over manual and semi-automatic methods. • QyScore® could be implemented in clinical trials and clinical routine to support the diagnosis and longitudinal monitoring of neurological diseases.

Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation.

White matter hyperintensities (WMHs) are frequently observed on structural neuroimaging of elderly populations and are associated with cognitive decline and increased risk of dementia. Many existing WMH segmentation algorithms produce suboptimal results in populations with vascular lesions or brain atrophy, or require parameter tuning and are computationally expensive. Additionally, most algorithms do not generate a confidence estimate of segmentation quality, limiting their interpretation. MRI-based segmentation methods are often sensitive to acquisition protocols, scanners, noise-level, and image contrast, failing to generalize to other populations and out-of-distribution datasets. Given these concerns, we propose a novel Bayesian 3D convolutional neural network with a U-Net architecture that automatically segments WMH, provides uncertainty estimates of the segmentation output for quality control, and is robust to changes in acquisition protocols. We also provide a second model to differentiate deep and periventricular WMH. Four hundred thirty-two subjects were recruited to train the CNNs from four multisite imaging studies. A separate test set of 158 subjects was used for evaluation, including an unseen multisite study. We compared our model to two established state-of-the-art techniques (BIANCA and DeepMedic), highlighting its accuracy and efficiency. Our Bayesian 3D U-Net achieved the highest Dice similarity coefficient of 0.89 ± 0.08 and the lowest modified Hausdorff distance of 2.98 ± 4.40 mm. We further validated our models highlighting their robustness on "clinical adversarial cases" simulating data with low signal-to-noise ratio, low resolution, and different contrast (stemming from MRI sequences with different parameters). Our pipeline and models are available at: https://hypermapp3r.readthedocs.io.

White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation.

BACKGROUND: Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets. METHODS: To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data. RESULTS: The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics. CONCLUSIONS: Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.