Lesion Load Research Articles

Adaptation of the Concept of Brain Reserve for the Prediction of Stroke Outcome: Proxies, Neural Mechanisms, and Significance for Research.

The prediction of stroke outcome is challenging due to the high inter-individual variability in stroke patients. We recently suggested the adaptation of the concept of brain reserve (BR) to improve the prediction of stroke outcome. This concept was initially developed alongside the one for the cognitive reserve for neurodegeneration and forms a valuable theoretical framework to capture high inter-individual variability in stroke patients. In the present work, we suggest and discuss (i) BR-proxies-quantitative brain characteristics at the time stroke occurs (e.g., brain volume, hippocampus volume), and (ii) proxies of brain pathology reducing BR (e.g., brain atrophy, severity of white matter hyperintensities), parameters easily available from a routine MRI examination that might improve the prediction of stroke outcome. Though the influence of these parameters on stroke outcome has been partly reported individually, their independent and combined impact is yet to be determined. Conceptually, BR is a continuous measure determining the amount of brain structure available to mitigate and compensate for stroke damage, thus reflecting individual differences in neural resources and a capacity to maintain performance and recover after stroke. We suggest that stroke outcome might be defined as an interaction between BR at the time stroke occurs and lesion load. BR in stroke can potentially be influenced, e.g., by modifying cardiovascular risk factors. In addition to the potential power of the BR concept in a mechanistic understanding of inter-individual variability in stroke outcome and establishing individualized therapeutic approaches, it might help to strengthen the synergy of preventive measures in stroke, neurodegeneration, and healthy aging.

Age-related decline in cerebral oxygen consumption in multiple sclerosis

Cerebral oxygen metabolism is altered in relapsing-remitting multiple sclerosis (RRMS), possibly a result of disease related cerebral atrophy with subsequent decreased oxygen demand. However, MS inflammation can also inhibit brain metabolism. Therefore, we measured cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) using MRI phase contrast mapping and susceptibility-based oximetry in 44 patients with early RRMS and 36 healthy controls. Cerebral atrophy and white matter lesion load were assessed from high-resolution structural MRI. Expanded Disability Status Scale (EDSS) scores were collected from medical records. The CMRO2 was significantly lower in patients (−15%, p = 0.002) and decreased significantly with age in patients relative to the controls (−1.35 µmol/100 g/min/year, p = 0.036). The lower CMRO2 in RRMS was primarily driven by a higher venous oxygen saturation in the sagittal sinus (p = 0.007) and not a reduction in CBF (p = 0.69). There was no difference in cerebral atrophy between the groups, and no correlation between CMRO2 and MS lesion volume or EDSS score. Therefore, the progressive CMRO2 decline observed before the occurrence of significant cerebral atrophy and despite adequate CBF supports emerging evidence of dysfunctional cellular respiration as a potential pathogenic mechanism and therapeutic target in RRMS.

Stratified predictions of upper limb motor outcomes after stroke.

Longitudinal observations of upper limb motor recovery after stroke have suggested that certain subgroups may exhibit distinct recovery patterns. Here we sought to examine whether the predictive ability for post-stroke upper limb motor outcomes could be enhanced by applying conventional stratification strategies. For 60 individuals who suffered the first stroke, upper limb motor impairment was assessed with the upper extremity Fugl-Meyer assessment (UE-FMA) at 2 weeks as a baseline and then 3 months post-stroke. Brain structural damage at baseline was assessed by MRI data-derived markers ranging from traditional lesion size to the lesion load and to the disconnectome. Linear regression models for predicting upper limb motor outcomes (UE-FMA score at 3 months post-stroke) based on baseline upper limb motor impairment (UE-FMA score at 2 weeks post-stroke), brain structural damage, and their combinations were generated, and those with the best predictive performance were determined for individual subgroups stratified according to initial impairment (severe and non-severe), lesion location (cortical and non-cortical), and neurophysiological status (motor evoked potential-positive and motor evoked potential-negative). The best predictions were made by baseline upper limb motor impairment alone for subgroups with less functional impairment (non-severe) or less structural involvement (non-cortical), but by the combination of baseline upper limb motor impairment and brain structural damage for the other subgroups. The predictive models tailored for subgroups determined according to initial impairment and neurophysiological status yielded a smaller overall error than that for the whole group in upper limb motor outcome predictions. The predictive ability for upper limb motor outcomes could be enhanced beyond the one-size-fits-all model for all individuals with stroke by applying specific stratification strategies, with stratification according to initial impairment being the most promising. We expect that predictive models tailored for individual subgroups could lead closer to the personalized prognosis of upper limb motor outcomes after stroke.

Enlarged choroid plexus in multiple sclerosis is associated with increased lesion load and atrophy in white matter but not gray matter atrophy

BackgroundEnlargement of the choroid plexus (CP) is reported to associate with inflammatory activity and contribute to brain atrophy in patients with multiple sclerosis (pwMS). However, a recent study in healthy volunteers (HVTs) has suggested that CP enlargement can be attributed to ventriculomegaly. ObjectivesTo clarify the pathological significance of the enlargement of CP in multiple sclerosis (MS). MethodsA total of 102 pwMS (89 with relapsing-remitting MS and 13 with secondary progressive MS) and 41 HVTs were cross-sectionally evaluated using brain volumetry. The CP volume was compared between disease groups and investigated for the relationships with other brain regional volumes. ResultsCP volume was significantly larger in pwMS than in HVTs in the univariate analysis, but not in multivariable analysis. Meanwhile, the CP and lateral ventricle (LV) volumes were significantly correlated. CP enlargement was significantly associated with increased lesion load and cerebral white matter (WM) atrophy, even after adjusting for LV volume. In contrast, multivariable analyses revealed that LV enlargement, but not CP enlargement, was associated with total gray matter (GM) atrophy. ConclusionCP enlargement was closely associated with LV enlargement. After adjusting for LV volume, CP enlargement in pwMS was associated with increased lesion load and WM atrophy but not GM atrophy.

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.

Data-driven biomarkers better associate with stroke motor outcomes than theory-based biomarkers.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have associated motor outcomes with the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to model chronic motor outcomes after stroke and compares the accuracy of these associations to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients from the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Stroke Recovery Working Group. Using the explained variance metric to measure the strength of the association between chronic motor outcomes and imaging biomarkers, we compared theory-based biomarkers, like lesion load to known motor tracts, to three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had stronger associations with chronic motor outcomes accuracy than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R 2 = 0.210, P < 0.001), performing significantly better than the theory-based biomarkers of lesion load of the corticospinal tract (R 2 = 0.132, P < 0.001) and of multiple descending motor tracts (R 2 = 0.180, P < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R 2 = 0.200, P < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R 2 = 0.167, P < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved the strength of associations for theory-based and data-driven biomarkers. Combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R 2 = 0.241, P < 0.001. Overall, these results demonstrate that out-of-sample associations between chronic motor outcomes and data-driven imaging features, particularly when lesion data is represented in terms of structural disconnection, are stronger than associations between chronic motor outcomes and theory-based biomarkers. However, combining both theory-based and data-driven models provides the most robust associations.

White matter disconnection impacts proprioception post-stroke.

Proprioceptive impairments occur in approximately 50-64% of people following stroke. While much is known about the grey matter structures underlying proprioception, our understanding of the white matter correlates of proprioceptive impairments is less well developed. It is recognised that behavioural impairments post-stroke are often the result of disconnection between wide-scale brain networks, however the disconnectome associated with proprioception post-stroke is unknown. In the current study, white matter disconnection was assessed in relation to performance on a robotic arm position matching (APM) task. Neuroimaging and robotic assessments of proprioception were collected for 203 stroke survivors, approximately 2-weeks post-stroke. The robotic assessment was performed in a KINARM Exoskeleton robotic device and consisted of a nine-target APM task. First, the relationship between white matter tract lesion load and performance on the APM task was assessed. Next, differences in the disconnectome between participants with and without impairments on the APM task were examined. Greater lesion load to the superior longitudinal fasciculus (SLF II and III), arcuate fasciculus (all segments) and fronto-insular tracts were associated with worse APM task performance. In those with APM task impairments, there was, additionally, disconnection of the posterior corpus callosum, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and optic radiations. This study highlights an important perisylvian white matter network supporting proprioceptive processing in the human brain. It also identifies white matter tracts, important for relaying proprioceptive information from parietal and frontal brain regions, that are not traditionally considered proprioceptive in nature.

Cerebrovascular lesion loads and accelerated brain aging: insights into the cognitive spectrum.

White matter hyperintensities (WMHs) and cerebral microbleeds are widespread among aging population and linked with cognitive deficits in mild cognitive impairment (MCI), vascular MCI (V-MCI), and Alzheimer's disease without (AD) or with a vascular component (V-AD). In this study, we aimed to investigate the association between brain age, which reflects global brain health, and cerebrovascular lesion load in the context of pathological aging in diverse forms of clinically-defined neurodegenerative conditions. We computed brain-predicted age difference (brain-PAD: predicted brain age minus chronological age) in the Comprehensive Assessment of Neurodegeneration and Dementia cohort of the Canadian Consortium on Neurodegeneration in Aging including 70 cognitively intact elderly (CIE), 173 MCI, 88 V-MCI, 50 AD, and 47 V-AD using T1-weighted magnetic resonance imaging (MRI) scans. We used a well-established automated methodology that leveraged fluid attenuated inversion recovery MRIs for precise quantification of WMH burden. Additionally, cerebral microbleeds were detected utilizing a validated segmentation tool based on the ResNet50 network, utilizing routine T1-weighted, T2-weighted, and T2* MRI scans. The mean brain-PAD in the CIE cohort was around zero, whereas the four categories showed a significantly higher mean brain-PAD compared to CIE, except MCI group. A notable association trend between brain-PAD and WMH loads was observed in aging and across the spectrum of cognitive impairment due to AD, but not between brain-PAD and microbleed loads. WMHs were associated with faster brain aging and should be considered as a risk factor which imperils brain health in aging and exacerbate brain abnormalities in the context of neurodegeneration of presumed AD origin. Our findings underscore the significance of novel research endeavors aimed at elucidating the etiology, prevention, and treatment of WMH in the area of brain aging.

Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults

BackgroundWhite matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. Methods40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. ResultsWithin our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. ConclusionWMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.

Outcome Prediction by Combining Corticospinal Tract Lesion Load with Diffusion-tensor Fractional Anisotropy in Patients after Hemorrhagic Stroke.

The objective of this study was to evaluate the predictive precision of combining the corticospinal tract lesion load (CST-LL) with the diffusion-tensor fractional anisotropy of the corticospinal tract (CST-FA) in the lesioned hemispheres regarding motor outcomes. Patients with putaminal and/or thalamic hemorrhage who had undergone computed tomography (CT) soon after onset in our hospital were retrospectively enrolled. The CST-LL was calculated after registration of the CT images to a standard brain. Diffusion-tensor imaging was performed during the second week after onset. Standardized automated tractography was employed to calculate the CST-FA. Outcomes were assessed at discharge from our affiliated rehabilitation facility using total scores of the motor component of the Stroke Impairment Assessment Set (SIAS-motor total; null to full, 0 to 25). Multivariate regression analysis was performed with CST-LL and CST-FA as explanatory variables and SIAS-motor total as a target value. Twenty-five patients participated in this study. SIAS-motor total ranged from 0 to 25 (median, 17). CST-LL ranged from 0.298 to 7.595 (median, 2.522) mL, and the lesion-side CST-FA ranged from 0.211 to 0.530 (median, 0.409). Analysis revealed that both explanatory variables were detected as statistically significant contributory factors. The estimated t values indicated that the contributions of these two variables were almost equal. The obtained regression model accounted for 63.9% of the variability of the target value. Incorporation of the CST-LL with the lesion-side CST-FA enhances the precision of the stroke outcome prediction model.

Diffusion tensor imaging and voxel-based morphometry in differentiating multiple sclerosis and its mimics

BackgroundThe discrimination between multiple sclerosis (MS) and other white matter lesions in adults is still problematic as multiple diseases have similar clinical and radiological findings, especially at the disease onset. This case–control study aimed to evaluate the efficacy of diffusion tensor imaging (DTI) and brain morphometry in the differentiation between adult MS and its magnetic resonance imaging (MRI) mimics.MethodsFifty-eight patients (49 women and 9 men; mean age 35.74 ± 11.86 years, range 18–50 years) with clinically suspected MS and age- and sex-matched fifteen healthy subjects were included. All study subjects underwent MRI using 3D FLAIR, 3D T1 MPRAGE, axial T2WI fast spin echo, and DTI sequences. The included patients were classified into MS and mimics groups according to MC Donald’s criteria 2017. Image post-processing using the region of interest (ROI) analysis for DTI parameters and automated voxel brain morphometry and segmentation was done for all study groups. Statistical comparison between the two patient groups and between them and the control group was performed regarding DTI indices (fractional anisotropy [FA], mean diffusivity [MD], and relative anisotropy [RA]) and brain morphometry parameters (including white matter volume (WMV), grey matter volume (GMV), cerebrospinal fluid volume (CSFV), T2 lesion load and deep grey matter volume).ResultsA statistically significant difference was observed between the MD, FA, and RA values of the patients and control groups. The MD values were significantly higher in the MS than in its mimics with a cut-off value of > 1.058 × 10−3 mm2/s (p < 0.001). Compared to the mimics group, the MS patients showed significantly lower WMV (33.31 ± 4.40 versus 35.71 ± 4.58; p = 0.047) and higher CSFV (16.38 ± 5.93 versus 13.06 ± 3.09; p = 0.012) with no significant difference regarding the GMV.ConclusionsMD analysis of DTI, WMV, and CSFV are useful quantitative measurements in confirming the diagnosis of MS and differentiating it from its imaging mimics.

Preserved Corticospinal Tract Revealed by Acute Perfusion Imaging Relates to Better Outcome After Thrombectomy in Stroke.

The indication for mechanical thrombectomy (MT) in stroke patients with large vessel occlusion has been constantly expanded over the past years. Despite remarkable treatment effects at the group level in clinical trials, many patients remain severely disabled even after successful recanalization. A better understanding of this outcome variability will help to improve clinical decision-making on MT in the acute stage. Here, we test whether current outcome models can be refined by integrating information on the preservation of the corticospinal tract as a functionally crucial white matter tract derived from acute perfusion imaging. We retrospectively analyzed 162 patients with stroke and large vessel occlusion of the anterior circulation who were admitted to the University Medical Center Lübeck between 2014 and 2020 and underwent MT. The ischemic core was defined as fully automatized based on the acute computed tomography perfusion with cerebral blood volume data using outlier detection and clustering algorithms. Normative whole-brain structural connectivity data were used to infer whether the corticospinal tract was affected by the ischemic core or preserved. Ordinal logistic regression models were used to correlate this information with the modified Rankin Scale after 90 days. The preservation of the corticospinal tract was associated with a reduced risk of a worse functional outcome in large vessel occlusion-stroke patients undergoing MT, with an odds ratio of 0.28 (95% CI, 0.15-0.53). This association was still significant after adjusting for multiple confounding covariables, such as age, lesion load, initial symptom severity, sex, stroke side, and recanalization status. A preinterventional computed tomography perfusion-based surrogate of corticospinal tract preservation or disconnectivity is strongly associated with functional outcomes after MT. If validated in independent samples this concept could serve as a novel tool to improve current outcome models to better understand intersubject variability after MT in large vessel occlusion stroke.

Accelerated brain ageing in participants with higher cerebrovascular lesion load across aging, cognitive impairment, and mixed presentation

AbstractBackgroundWe aimed to investigate the association between cortical brain age and white matter hyperintensities (WMH) in diverse forms of clinically‐defined vascular conditions. Our hypothesis was that a higher WMH burden would be associated with higher cortical brain age in all clinical subtypes.MethodWe used standardized MRI data obtained from participants in the COMPASS‐ND cohort of the CCNA. We used a standard linear support vector regression algorithm to estimate brain age, matching chronological age to cortical anatomical measurements obtained with the FreeSurfer toolbox on T1‐weighted MRI, sex, and intracranial volume. We calculated brain‐PAD (i.e., predicted brain age minus real age) and applied bias adjustment to remove age‐dependency in the estimates. A validated automated technique utilizing T2‐weighted and fluid attenuated inversion recovery MRIs was used to compute WMH loads.ResultParticipants included 107 CIE, 240 mild cognitive impairment (MCI), 115 vascular‐MCI (V‐MCI), 81 probable Alzheimer’s disease (AD), and 50 V‐AD. There was a significant difference in brain‐PAD [ F (4,599) = 56, P &lt; 0.001, ANCOVA test] among groups, whilst adjusting for sex and chronological age. All four categories of patients exhibited a significantly higher mean brain‐PAD than CIE (P &lt; 0.001), with the AD cohort having the highest brain‐PAD. There was a significant difference in WMH loads [ F (4,586) = 48, P &lt; 0.001, ANCOVA test] between groups, whilst adjusting for sex and age. All cohorts showed a positive correlation between brain‐PAD and WMH, indicating accelerated ageing in people with higher WMHs. We observed moderate and significant correlations between brain‐PAD and WMH loads for V‐MCI (r = 0.34, P &lt; 0.001) and V‐AD (r = 0.36, P = 0.001) but weaker, while significant correlations in CIE (r = 0.20, P = 0.035) and AD cohorts (r = 0.24, P = 0.025).ConclusionWe observed a positive and significant link between brain‐PAD and WMH in all categories. This finding indicates on the importance of treatment and prevention strategies for vascular risk factors, which might be able to slow down the progression of cerebrovascular lesions and delay the effect on cortical thickness.

White Matter Correlates of Speech in Cerebrovascular Disease

AbstractBackgroundAnalyses of spoken discourse (speech beyond single words or sentences) can detect cognitive impairment in cerebrovascular disease (CVD) [Roberts, et al. (2021). Top Lang Disord 41(1):73‐98]. However, the neurological basis for altered spoken discourse in CVD is poorly defined. This study examined the association between spoken discourse and visible white matter damage detected using structural magnetic resonance imaging (MRI) and potential early‐stage damage in normal‐appearing white matter (NAWM) detected using diffusion tensor imaging (DTI) to better define the link between CVD‐related neurodegeneration and altered speech.MethodSpoken discourse and 3T MRI data were obtained from the CVD cohort of the Ontario Neurodegenerative Disease Research Initiative (n = 127). Spoken discourse analyses were completed previously [Roberts et al., 2021]. White matter hyperintensities (WMH) and the NAWM portions of the inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus – parietal (SLFp) and temporal (SLFt) endings, and uncinate fasciculus (UNC) were segmented in each hemisphere (Figure 1). Mean values of fractional anisotropy (FA) and mean diffusivity (MD) within NAWM, and normalized WMH volume were calculated for each of the white matter tracts. Three canonical correlation analyses examined associations between 10 spoken discourse measures and the imaging metrics (WMH volume, FA, MD) in each tract.ResultCanonical correlations were significant for FA (rc = 0.51, p&lt;0.05) and MD (rc = 0.56, p&lt;0.05) but not WMH volume (rc = 0.42, p = 0.69). Among the white matter tracts, the strongest canonical loadings were seen for FA and MD in the left SLFp (FA: 0.80; MD: ‐0.61) and left SLFt (FA: 0.60; MD: ‐0.40) (Figure 2). Higher FA and lower MD in the left SLFp and left SLFt were associated with fluency, information content, and syntax performance.ConclusionSpoken discourse performance was associated with microstructural integrity of NAWM but not visible white matter damage. These results suggest that DTI metrics provide a more relevant assessment of white matter tract function in relation to speech than a volumetric measure of tract lesion load. Of the white matter tracts investigated in this study, spoken discourse performance in CVD was most strongly linked to white matter microstructure in the parietal and temporal endings of the left superior longitudinal fasciculus.

White Matter Lesion Asymmetry: A Potential Indicator of Amyloid Positivity in Patients with Mild Cognitive Impairment

AbstractBackgroundAssessing amyloid‐positivity in patients with mild cognitive impairment (MCI) is crucial as amyloid‐positive individuals have a higher risk of dementia conversion than amyloid‐negative patients. This study aimed to investigate whether the asymmetry of white matter lesions (WML) on T2‐fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), measured by artificial intelligence (AI) hyperintensity segmentation, could be a potential indicator for amyloid positron emission tomography (PET) positivity in patients with MCI.MethodThis retrospective cohort study included MCI patients who visited the memory clinic of Yeouido St. Mary’s Hospital. All participants underwent a set of clinical and neuropsychological assessments, brain MRI, and amyloid PET using [18F]‐Flutemetamol. Our in‐house AI software was utilized on paired T1 and T2‐FLAIR MRIs to process to segment and separate WML into left and right hemispheres. From the processed segmentation, we measured the subjects' individual WML differences through a volumetric assessment.ResultsTotal 122 subjects were enrolled in this study. By the amyloid‐PET positivity, 53 and 69 patients were in the amyloid‐negative and amyloid‐positive groups, respectively. The two groups were comparable with no significant differences of age (p = 0.189), sex (p = 0.057), education years (p = 0.411) and MMSE scores (p = 0.861). However, the amyloid‐positive group had a significantly higher frequency of having an e4 allele of APOE genotype (p = 0.033) and Clinical Dementia Rating scale (p = 0.024). The average volume between hemispheres significantly differed in the amyloid‐negative group (p = 0.020) but not in the amyloid‐positive group (p = 0.220). Both groups had a larger WML volume in the left hemisphere, which did not differ significantly between groups.ConclusionOur findings suggest that evaluating the asymmetry of WML rather than the total hyperintensity lesion load is necessary in MCI patients, particularly in those without amyloid pathology. In conclusion, WML asymmetry may serve as a potential indicator of amyloid positivity in MCI patients.

White Matter Correlates of Speech in Cerebrovascular Disease

AbstractBackgroundAnalyses of spoken discourse (speech beyond single words or sentences) can detect cognitive impairment in cerebrovascular disease (CVD) [Roberts, et al. (2021). Top Lang Disord 41(1):73‐98]. However, the neurological basis for altered spoken discourse in CVD is poorly defined. This study examined the association between spoken discourse and visible white matter damage detected using structural magnetic resonance imaging (MRI) and potential early‐stage damage in normal‐appearing white matter (NAWM) detected using diffusion tensor imaging (DTI) to better define the link between CVD‐related neurodegeneration and altered speech.MethodSpoken discourse and 3T MRI data were obtained from the CVD cohort of the Ontario Neurodegenerative Disease Research Initiative (n = 127). Spoken discourse analyses were completed previously [Roberts et al., 2021]. White matter hyperintensities (WMH) and the NAWM portions of the inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus – parietal (SLFp) and temporal (SLFt) endings, and uncinate fasciculus (UNC) were segmented in each hemisphere (Figure 1). Mean values of fractional anisotropy (FA) and mean diffusivity (MD) within NAWM, and normalized WMH volume were calculated for each of the white matter tracts. Three canonical correlation analyses examined associations between 10 spoken discourse measures and the imaging metrics (WMH volume, FA, MD) in each tract.ResultCanonical correlations were significant for FA (rc = 0.51, p&lt;0.05) and MD (rc = 0.56, p&lt;0.05) but not WMH volume (rc = 0.42, p = 0.69). Among the white matter tracts, the strongest canonical loadings were seen for FA and MD in the left SLFp (FA: 0.80; MD: ‐0.61) and left SLFt (FA: 0.60; MD: ‐0.40) (Figure 2). Higher FA and lower MD in the left SLFp and left SLFt were associated with fluency, information content, and syntax performance.ConclusionSpoken discourse performance was associated with microstructural integrity of NAWM but not visible white matter damage. These results suggest that DTI metrics provide a more relevant assessment of white matter tract function in relation to speech than a volumetric measure of tract lesion load. Of the white matter tracts investigated in this study, spoken discourse performance in CVD was most strongly linked to white matter microstructure in the parietal and temporal endings of the left superior longitudinal fasciculus.

Phase I clinical trial of intracerebroventricular transplantation of allogeneic neural stem cells in people with progressive multiple sclerosis

We report the analysis of 1 year of data from the first cohort of 15 patients enrolled in an open-label, first-in-human, dose-escalation phase I study (ClinicalTrials.gov: NCT03282760, EudraCT2015-004855-37) to determine the feasibility, safety, and tolerability of the transplantation of allogeneic human neural stem/progenitor cells (hNSCs) for the treatment of secondary progressive multiple sclerosis. Participants were treated with hNSCs delivered via intracerebroventricular injection in combination with an immunosuppressive regimen. No treatment-related deaths nor serious adverse events (AEs) were observed. All participants displayed stability of clinical and laboratory outcomes, as well as lesion load and brain activity (MRI), compared with the study entry. Longitudinal metabolomics and lipidomics of biological fluids identified time- and dose-dependent responses with increased levels of acyl-carnitines and fatty acids in the cerebrospinal fluid (CSF). The absence of AEs and the stability of functional and structural outcomes are reassuring and represent a milestone for the safe translation of stem cells into regenerative medicines.

Automatic segmentation of white matter hyperintensities in T2-FLAIR with AQUA: A comparative validation study against conventional methods

White matter hyperintensities (WMHs) are lesions in the white matter of the brain that are associated with cognitive decline and an increased risk of dementia. The manual segmentation of WMHs is highly time-consuming and prone to intra- and inter-variability. Therefore, automatic segmentation approaches are gaining attention as a more efficient and objective means to detect and monitor WMHs. In this study, we propose AQUA, a deep learning model designed for fully automatic segmentation of WMHs from T2-FLAIR scans, which improves upon our previous study for small lesion detection and incorporating a multicenter approach. AQUA implements a two-dimensional U-Net architecture and uses patch-based training. Additionally, the network was modified to include Bottleneck Attention Module on each convolutional block of both the encoder and decoder to enhance performance for small-sized WMH. We evaluated the performance and robustness of AQUA by comparing it with five well-known supervised and unsupervised methods for automatic segmentation of WMHs (LGA, LPA, SLS, UBO, and BIANCA). To accomplish this, we tested these six methods on the MICCAI 2017 WMH Segmentation Challenge dataset, which contains MRI images from 170 elderly participants with WMHs of presumed vascular origin, and assessed their robustness across multiple sites and scanner types. The results showed that AQUA achieved superior performance in terms of spatial (Dice = 0.72) and volumetric (logAVD = 0.10) agreement with the manual segmentation compared to the other methods. While the recall and F1-score were moderate at 0.49 and 0.59, respectively, they improved to 0.75 and 0.82 when excluding small lesions (≤ 6 voxels). Remarkably, despite being trained on a different dataset with different ethnic backgrounds, lesion loads, and scanners, AQUA's results were comparable to the top 10 ranked methods of the MICCAI challenge. The findings suggest that AQUA is effective and practical for automatic segmentation of WMHs from T2-FLAIR scans, which could help identify individuals at risk of cognitive decline and dementia and allow for early intervention and management.

Networks of microstructural damage predict disability in multiple sclerosis

BackgroundNetwork-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening...

Microstructural changes of peripheral nerves in early multiple sclerosis: A prospective magnetic resonance neurography study.

Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system (CNS). However, there is increasing evidence of peripheral nerve involvement. This study aims to characterize the pattern of peripheral nerve changes in patients with newly diagnosed MS using quantitative magnetic resonance (MR) neurography. In this prospective study, 25 patients first diagnosed with MS according to the revised McDonald criteria (16 female, mean age = 32.8 ± 10.6 years) and 14 healthy controls were examined with high-resolution 3-T MR neurography of the sciatic nerve using diffusion kurtosis imaging (DKI; 20 diffusional directions, b = 0, 700, 1200 s/mm2 ) and magnetization transfer imaging (MTI). In total, 15 quantitative MR biomarkers were analyzed and correlated with clinical symptoms, intrathecal immunoglobulin synthesis, electrophysiology, and lesion load on brain and spine MR imaging. Patients showed decreased fractional anisotropy (mean = 0.51 ± 0.04 vs. 0.56 ± 0.03, p < 0.001), extra-axonal tortuosity (mean = 2.32 ± 0.17 vs. 2.49 ± 0.17, p = 0.008), and radial kurtosis (mean = 1.40 ± 0.23 vs. 1.62 ± 0.23, p = 0.014) and higher radial diffusivity (mean = 1.09 ∙ 10-3 mm2 /s ± 0.16 vs. 0.98 ± 0.11 ∙ 10-3 mm2 /s, p = 0.036) than controls. Groups did not differ in MTI. No significant association was found between MR neurography markers and clinical/laboratory parameters or CNS lesion load. This study provides further evidence of peripheral nerve involvement in MS already at initial diagnosis. The characteristic pattern of DKI parameters indicates predominant demyelination and suggests a primary coaffection of the peripheral nervous system in MS. This first human study using DKI for peripheral nerves shows its potential and clinical feasibility in providing novel biomarkers.