Atrophy Measures Research Articles

MRI of Transcallosal White Matter Helps to Predict Motor Impairment in Multiple Sclerosis

Background Altered callosal integrity has been associated with motor deficits in patients with multiple sclerosis (MS), but its contribution to disability has, to the knowledge of the authors, not been investigated by using multiparametric MRI approaches. Purpose To investigate structural and functional interhemispheric MRI substrates of global disability at different milestones and upper limb motor impairment in MS. Materials and Methods In this cross-sectional study, healthy control patients and patients with MS (between January 1, 2008, and December 31, 2016) were retrospectively selected from our hospital database. Clinical assessment included Expanded Disability Status Scale (EDSS), nine-hole peg test, and digital finger tapping test. By using structural and resting-state functional MRI sequences, probabilistic tractography of hand corticospinal tract fibers, and transcallosal fibers between hand-motor cortices (hereafter, referred to as hand-M1), supplementary motor areas (SMAs), premotor cortices (PMCs), and voxel-mirror homotopic connectivity (VMHC) were analyzed. Random forest analyses identified the MRI predictors of clinical disability at different milestones (EDSS scores of 3.0, 4.0, 6.0) and upper limb motor impairment (nine-hole peg test and finger tapping test z scores < healthy control patients 5th percentile). Results One-hundred thirty healthy control patients (median age, 39 years; interquartile range, 31-50 years; 70 women) and 340 patients with MS (median age, 43 years; interquartile range, 33-51 years; 213 women) were studied. EDSS 3.0 predictors (n = 159) were global measures of atrophy and lesions together with damage measures of corticospinal tracts and transcallosal fibers between PMCs and SMAs (accuracy, 86%; P = .001-.01). For EDSS 4.0 (n = 131), similar predictors were found in addition to damage in transcallosal fibers between hand-M1 (accuracy, 89%; P = .001-.049). No MRI predictors were found for EDSS 6.0 (n = 70). Nine-hole peg test (right, n = 161; left, n = 166) and finger tapping test (right, n = 117; left, n = 111) impairments were predicted by damage in transcallosal fibers between SMAs and PMCs (accuracy range, 69%-77%; P = .001-.049). VMHC abnormalities did not explain clinical outcomes. Conclusion Structural, not functional, abnormalities at MRI in transcallosal premotor and motor white matter fibers predicted severity of global disability and upper limb motor impairment in patients with multiple sclerosis. The informative role of such predictors appeared less evident at higher disability levels. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Barkhof and Pontillo in this issue.

Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated.Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning.We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables.Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.

Utility of white matter disease and atrophy on routinely acquired brain imaging for prediction of long-term delirium risk: population-based cohort study

Backgroundbrain imaging done as part of standard care may have clinical utility beyond its immediate indication. Using delirium as an exemplar, we determined the predictive value of baseline brain imaging variables [white matter changes (WMC) and atrophy] for delirium risk on long-term follow-up after transient ischemic attack (TIA)/stroke in a population-based cohort study.Methodssurviving TIA/stroke participants in the Oxford Vascular Study (OXVASC) were assessed prospectively for delirium during all hospitalisations over 6 months (2013–14). Using logistic regression, independent associations were determined between baseline OXVASC computed tomography or magnetic resonance brain imaging measures of WMC and cerebral atrophy (none/mild versus moderate/severe) and delirium adjusted for age, sex, baseline stroke severity, depression, illness severity and pre-admission cognition.Resultsamong 1,565 TIA/stroke survivors with 194 hospital admissions (158 patients, mean/standard deviation age at admission = 79.2/11.5 years), delirium occurred in 59 (37%). WMC and atrophy on baseline imaging were associated with delirium [odds ratio (OR) = 3.41, 1.21–5.85, P = 0.001 and OR = 2.50, 1.23–5.08, P = 0.01 (unadjusted) and OR = 2.67, 1.21–5.85, P = 0.02 and OR = 2.18, 1.00–4.73, P = 0.05 (adjusted age and sex)]. Associations were strengthened when analyses were restricted to patients hospitalised within 5 years of baseline brain imaging [OR = 6.04, 2.39–15.24, P < 0.0001 and OR = 4.64, 1.46–14.82, P = 0.009 (unadjusted)] but only WMC remained significant after adjustment for all covariates including pre-admission cognition (OR = 4.83, 1.29–18.13, P = 0.02 for Mini-Mental State Examination and OR = 5.15, 1.26–21.09, P = 0.02 for Montreal Cognitive Assessment).ConclusionsWMC and atrophy on brain imaging done up to 5 years earlier predicted delirium and may have clinical utility in risk stratification. Associations with WMC but not atrophy were independent of pre-admission cognitive impairment.

Losartan to slow the progression of mild-to-moderate Alzheimer’s disease through angiotensin targeting: the RADAR RCT

Background Medications that modify the renin–angiotensin system may reduce Alzheimer’s disease pathology and reduce the rate of disease progression. Objective This study investigated whether taking the antihypertensive drug losartan, in addition to normal care, would slow the progression of Alzheimer’s disease when compared with a placebo. Design A double-blind multicentre randomised controlled trial, after a 4-week open-label phase, with follow-up at 14 days and at 3, 6, 9 and 12 months. The primary outcome was based on measured imaging differences in brain volume between baseline and 12 months. Setting Twenty-three NHS hospital trusts across England, Scotland and Northern Ireland. Participants Patients diagnosed with mild-to-moderate Alzheimer’s disease were eligible to participate if they met the following criteria: (1) aged ≥ 55 years; (2) a Mini Mental State Examination score of 15–28; (3) a modified Hachinski Ischaemic Score of ≤ 5; (4) a previous computerised tomography, single-photon emission computed tomography or magnetic resonance imaging scan consistent with a diagnosis of Alzheimer’s disease; (5) a study companion who was willing to participate in the study; and (6) capacity to consent for themselves. Patients were ineligible if they were (1) taking or intolerant to renin–angiotensin system-related medications, (2) unlikely to undergo magnetic resonance imaging or (3) unlikely to complete the trial protocol. People who had blood pressure outside the normal ranges, defined cardiovascular issues, impaired liver or renal function, or a primary neurodegenerative disease that was not Alzheimer’s disease were also excluded, as were women who had not reached menopause and were unwilling to take relevant protocol-specific safety precautions. Intervention The intervention was either 100 mg of overencapsulated losartan (Teva Pharmaceuticals Industries Ltd, Petah Tikva, Israel) daily or a matched placebo for 12 months. Main outcome measures Difference in brain atrophy, represented by measurement of whole-brain volume before and following 12 months of treatment post randomisation, was measured using volumetric MRI and determined by boundary shift interval analysis. Secondary outcomes included changes in rates of Alzheimer’s disease progression (as assessed using the ADAS-Cog, Mini Mental State Examination and Neuropsychiatric Inventory), the volume of white matter hyperintensities, cerebral blood flow (assessed by magnetic resonance imaging), blood pressure, magnetic resonance imaging measures of atrophy and association with measures of cognitive decline, and drug compliance and tolerability. Results A total of 261 participants entered the open-label phase, of whom 211 were randomised to the intervention (n = 105) or placebo (n = 106) arms. Of the 197 people (93%) who completed the study, 81% (n = 171) had a valid primary outcome. The difference in brain volume between arms was consistent with chance (–2.79 ml, 95% confidence interval –6.46 to 0.89 ml; p = 0.19), and there was no evidence of benefit for any of the secondary outcome measures. Limitations Our study had 82% power to detect treatment-based changes and, as a result, may have been underpowered or, more likely, the intervention, which may not have crossed the blood–brain barrier as much as expected, may have been given too late or for an insufficient amount of time in the disease process to influence the outcomes. Conclusions Losartan administered over 12 months did not alter brain atrophy in Alzheimer’s disease. Future work Other related ‘sartans’ could be tested in patient groups with mild cognitive impairment and for longer to fully test this hypothesis. Trial registration Current Controlled Trials ISRCTN93682878 and EudraCT 2012-003641-15. Funding This project was funded by the Efficacy and Mechanism Evaluation (EME) programme, a Medical Research Council and National Institute for Health Research (NIHR) partnership. This will be published in full in Efficacy and Mechanism Evaluation; Vol. 8, No. 19. See the NIHR Journals Library website for further project information.

Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease.

Background and ObjectivesLongitudinal measurements of brain atrophy using structural MRI (sMRI) can provide powerful markers for tracking disease progression in neurodegenerative diseases. In this study, we use a disease progression model to learn individual-level disease times and hence reveal a new timeline of sMRI changes in Huntington disease (HD).MethodsWe use data from the 2 largest cohort imaging studies in HD—284 participants from TRACK-HD (100 control, 104 premanifest, and 80 manifest) and 159 participants from PREDICT-HD (36 control and 128 premanifest)—to train and test the model. We longitudinally register T1-weighted sMRI scans from 3 consecutive time points to reduce intraindividual variability and calculate regional brain volumes using an automated segmentation tool with rigorous manual quality control.ResultsOur model reveals, for the first time, the relative magnitude and timescale of subcortical and cortical atrophy changes in HD. We find that the largest (∼20% average change in magnitude) and earliest (∼2 years before average abnormality) changes occur in the subcortex (pallidum, putamen, and caudate), followed by a cascade of changes across other subcortical and cortical regions over a period of ∼11 years. We also show that sMRI, when combined with our disease progression model, provides improved prediction of onset over the current best method (root mean square error = 4.5 years and maximum error = 7.9 years vs root mean square error = 6.6 years and maximum error = 18.2 years).DiscussionOur findings support the use of disease progression modeling to reveal new information from sMRI, which can potentially inform imaging marker selection for clinical trials.

Prediction of cognitive decline in subjects with subjective memory impairment

Objective: To compare the predictive accuracy of Medial Temporal Lobe Atrophy (MTLA) measurements, for cognitive decline at two-years follow up in subjects subjective memory impairment (SMI).

Atrophy quantification in multiple sclerosis: Application to the multicenter INNI dataset

Aim of this study was to compare a set of methods for gray matter (GM) and whole-brain atrophy measurements on the Italian Neuroimaging Network Initiative (INNI) dataset, where MRI and clinical data from multiple sclerosis (MS) patients and healthy controls (HC) are collected by Italian Research Centers with recognized expertise.

The cognitive side of ALS

The presence of cognitive and/or behavioral impairment, ranging from frontotemporal dementia (FTD) to selective neuropsychological dysfunction, in now established, and has been shown to have prognostic impact.The diagnosis is now defined on the basis of the revised diagnostic criteria proposed by Strong et al. (Amyotrophic lateral sclerosis and frontotemporal degeneration 18,153–174, 2017), which emphasize the impact of disorders of executive function, but acknowledge the possible presence of “mixed” patters of cognitive impairment. This is confirmed by the results of studies using data-driven approaches, which have indicated the presence of three main test clusters, two compatible with the behavioral (ALSbi) and cognitive (ALSci) profiles of Strong et al. criteria, and a third loading on social cognition, language and memory tests, representing a distinct pattern of non-motor manifestations in a subsample of patients. The latter pattern of cognitive dysfunction is of particular interest, as disorders of social cognition and language are the typical markers of, respectively, the behavioral and language variants of FTD, and are associated to the neurodegenerative involvement of the large scale networks specifically associated with these function. Magnetic resonance studies have confirmed the correlation of performance on social cognition test wth atrophy measures in the anterior cingulate cortex and right inferior frontal gyrus, and of language impairment with left temporal pole and insular involvement in ALS. Further studies on large patient populations are ongoing to confim the existence of consistent cognitive phenotype differences and their assoiciation with additional genetic, clinical and prognostic factors.

Central nervous system atrophy predicts future dynamics of disability progression in a real-world multiple sclerosis cohort.

Background and purposeIn an era of individualized multiple sclerosis (MS) patient management, biomarkers for accurate prediction of future clinical outcomes are needed. We aimed to evaluate the potential of short‐term magnetic resonance imaging (MRI) atrophy measures and serum neurofilament light chain (sNfL) as predictors of the dynamics of disability accumulation in relapse‐onset MS.MethodsBrain gray and white matter, thalamic, striatal, pallidal and cervical spinal cord volumes, and lesion load were measured over three available time points (mean time span 2.24 ± 0.70 years) for 183 patients (140 relapsing‐remitting [RRMS] and 43 secondary‐progressive MS (SPMS); 123 female, age 46.4 ± 11.0 years; disease duration 15.7 ± 9.3 years), and their respective annual changes were calculated. Baseline sNfL was also measured at the third available time point for each patient. Subsequently, patients underwent annual clinical examinations over 5.4 ± 3.7 years including Expanded Disability Status Scale (EDSS) scoring, the nine‐hole peg test and the timed 25‐foot walk test.ResultsHigher annual spinal cord atrophy rates and lesion load increase predicted higher future EDSS score worsening over time in SPMS. Lower baseline thalamic volumes predicted higher walking speed worsening over time in RRMS. Lower baseline gray matter, as well as higher white matter and spinal cord atrophy rates, lesion load increase, baseline striatal volumes and baseline sNfL, predicted higher future hand dexterity worsening over time. All models showed reasonable to high prediction accuracy.ConclusionThis study demonstrates the capability of short‐term MRI metrics to accurately predict future dynamics of disability progression in a real‐world relapse‐onset MS cohort. The present study represents a step towards the utilization of structural MRI measurements in patient care.

Regional age-related atrophy after screening for preclinical alzheimer disease

Brain atrophy occurs in aging even in the absence of dementia, but it is unclear to what extent this is due to undetected preclinical Alzheimer disease. Here we examine a cross-sectional cohort (ages 18-88) free from confounding influence of preclinical Alzheimer disease, as determined by amyloid PET scans and three years of clinical evaluation post-imaging. We determine the regional strength of age-related atrophy using linear modeling of brain volumes and cortical thicknesses with age. Age-related atrophy was seen in nearly all regions, with greatest effects in the temporal lobe and subcortical regions. When modeling age with the estimated derivative of smoothed aging curves, we found that the temporal lobe declined linearly with age, subcortical regions declined faster at later ages, and frontal regions declined slower at later ages than during midlife. This age-derivative pattern was distinct from the linear measure of age-related atrophy and significantly associated with a measure of myelin. Atrophy did not detectably differ from a preclinical Alzheimer disease cohort when age ranges were matched.

Manual Versus Semi-Automated Measurement of Geographic Atrophy Area in Eyes With Age-Related Macular Degeneration.

PurposeTo investigate the agreement between and correlation of manual and semi-automated area measurements of geographic atrophy (GA) in eyes with age-related macular degeneration (AMD) using Heidelberg Eye Explorer and ImageJ software.MethodsFundus autofluorescence (FAF) images of eyes with GA secondary to AMD were analyzed. Two graders measured the atrophic area using Heidelberg Eye Explorer manual and semi-automated (RegionFinder) software, as well as ImageJ manual and semi-automated (Color Threshold) software.ResultsFifty-four FAF images were analyzed. The mean (SD) areas were 10.55 (11.4) mm2 and 9.6 (9.8) mm2 using the Heidelberg manual and semi-automated tools, respectively. The mean (SD) areas were 11.04 (12.25) mm2 and 9.75 (10.3) mm2 using ImageJ manual and semi-automated tools, respectively. Compared with the semi-automated Heidelberg RegionFinder (gold standard) area measurements, Bland–Altman plots showed mean differences of 0.96 mm2, 1.4 mm2, and 0.16 mm2 with manual Heidelberg, manual ImageJ, and semi-automated ImageJ measurements, respectively. Homogeneous GA lesions showed less disparity in area measurements across modalities compared with non-homogeneous lesions.ConclusionsImageJ appears to be a reliable tool for GA area measurements when proprietary OCT software is unavailable. Manual measurements with Heidelberg Eye Explorer and ImageJ were comparable, as were semi-automated measurements with Heidelberg RegionFinder and ImageJ Color Threshold.Translational RelevanceNovel GA measurement techniques using open-source software appear to be comparable to established techniques using proprietary platform-specific software, which may permit more widespread analysis of GA progression from multiple platforms and databases.

Regional Cerebellar Volume Loss Predicts Future Disability in Multiple Sclerosis Patients

Cerebellar symptoms in multiple sclerosis (MS) are well described; however, the exact contribution of cerebellar damage to MS disability has not been fully explored. Longer-term observational periods are necessary to better understand the dynamics of pathological changes within the cerebellum and their clinical consequences. Cerebellar lobe and single lobule volumes were automatically segmented on 664 3D-T1-weighted MPRAGE scans (acquired at a single 1.5 T scanner) of 163 MS patients (111 women; mean age: 47.1 years; 125 relapsing–remitting (RR) and 38 secondary progressive (SP) MS, median EDSS: 3.0) imaged annually over 4 years. Clinical scores (EDSS, 9HPT, 25FWT, PASAT, SDMT) were determined per patient per year with a maximum clinical follow-up of 11 years. Linear mixed-effect models were applied to assess the association between cerebellar volumes and clinical scores and whether cerebellar atrophy measures may predict future disability progression. SPMS patients exhibited faster posterior superior lobe volume loss over time compared to RRMS, which was related to increase of EDSS over time. In RRMS, cerebellar volumes were significant predictors of motor scores (e.g. average EDSS, T25FWT and 9HPT) and SDMT. Atrophy of motor-associated lobules (IV-VI + VIII) was a significant predictor of future deterioration of the 9HPT of the non-dominant hand. In SPMS, the atrophy rate of the posterior superior lobe (VI + Crus I) was a significant predictor of future PASAT performance deterioration. Regional cerebellar volume reduction is associated with motor and cognitive disability in MS and may serve as a predictor for future disease progression, especially of dexterity and impaired processing speed.

Carotid Atherosclerosis and Longitudinal Changes of MRI Visual Rating Measures in Stroke Survivors: A Seven-Year Follow-Up Study

ObjectivesWe aimed to assess longitudinal changes in MRI measures of brain atrophy and white matter lesions in stroke and transient ischemic attack (TIA) survivors, and explore whether carotid stenosis predicts progression of these changes, assessed by visual rating scales. Materials and MethodsAll patients with a first-ever stroke or TIA admitted to Bærum Hospital, Norway, in 2007/2008, were invited in the acute phase and followed for seven years. Carotid ultrasound was performed during the hospital stay. Carotid stenosis was defined as ≥50% narrowing of lumen. MRI was performed one and seven years after the index event and analyzed according to the visual rating scales Fazekas scale (0-3), Medial Temporal Lobe Atrophy (MTLA) (0-4) score, and Global Cortical Atrophy (GCA) scale (0-3). Patients with MRI scans at both time points were included in this sub-study. ResultsOf 227 patients recruited, 76 had both MRI examinations. Mean age 73.9±10.6, 41% women, and 9% had ≥50% carotid stenosis. Mean Fazekas scale was 1.7±0.9 and 1.8±1.0, mean MTLA score 1.0 ±1.0 and 1.7±1.0, and mean GCA scale score 1.4±0.7 and 1.4±0.6 after one and seven years, respectively. 71% retained the same Fazekas scale score, while 21% showed progression. Deterioration in GCA scale was seen in 20% and increasing MTLA score in 57%. Carotid stenosis was not associated with progression on Fazekas score, MTLA score or GCA scale. ConclusionsThree out of five showed progression on the MTLA score. Carotid stenosis was not associated with longitudinal change of visual rating scales.

Plasma neurofilament light chain levels and cognitive testing as predictors of fast progression in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by a heterogeneous course. Predicting a fast rather than a slow decline over time is crucial to both provide a reliable prognosis and elaborate stricter enrolment criteria in clinical trials. Here we searched for independent predictors of cognitive decline rate to assess the risk of fast disease progression already at baseline. Fifty-three subjects with an "in-vivo biomarker confirmed" diagnosis of AD were included. Neuropsychological assessment, plasma neurofilaments (NfL) concentrations and, in a subsample of 23 patients, brain magnetic resonance imaging were available. Patients were labelled FAST or SLOW depending on the Mini-Mental State Examination (MMSE) points lost per year (FAST if more than 3 points). We adopted single logistic regression models to search for independent predictors of FAST progression. At baseline no differences were found between FAST and SLOW subgroups in demographics, MMSE scores, vascular burden and medial temporal lobe atrophy measurements. Higher plasma NfL concentrations and worse scores at semantic verbal fluency (SVF) and clock drawing test (CDT) were independent predictors of FAST decline, after controlling for age, education, sex and baseline disease severity stage. The regression model combining all the predictors correctly classified 80% of patients overall. The risk of FAST decline was 81.2% if all the three predictors were abnormal (i.e., SVF≤21.5, CDT≤5.5, NfL≥22.19). An easily applicable algorithm, including plasma NfL measurement and two neuropsychological tests worldwide adopted in clinical practice (SVF and CDT), may allow clinicians to reliably stratify AD patients in relation to the risk of fast cognitive decline.

Neuroimaging correlates of brain injury in Wilson's disease: a multimodal, whole-brain MRI study.

Wilson’s disease is an autosomal-recessive disorder of copper metabolism with neurological and hepatic presentations. Chelation therapy is used to ‘de-copper’ patients but neurological outcomes remain unpredictable. A range of neuroimaging abnormalities have been described and may provide insights into disease mechanisms, in addition to prognostic and monitoring biomarkers. Previous quantitative MRI analyses have focused on specific sequences or regions of interest, often stratifying chronically treated patients according to persisting symptoms as opposed to initial presentation.In this cross-sectional study, we performed a combination of unbiased, whole-brain analyses on T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and susceptibility-weighted imaging data from 40 prospectively recruited patients with Wilson’s disease (age range 16–68). We compared patients with neurological (n = 23) and hepatic (n = 17) presentations to determine the neuroradiological sequelae of the initial brain injury. We also subcategorized patients according to recent neurological status, classifying those with neurological presentations or deterioration in the preceding 6 months as having ‘active’ disease. This allowed us to compare patients with active (n = 5) and stable (n = 35) disease and identify imaging correlates for persistent neurological deficits and copper indices in chronically treated, stable patients.Using a combination of voxel-based morphometry and region-of-interest volumetric analyses, we demonstrate that grey matter volumes are lower in the basal ganglia, thalamus, brainstem, cerebellum, anterior insula and orbitofrontal cortex when comparing patients with neurological and hepatic presentations. In chronically treated, stable patients, the severity of neurological deficits correlated with grey matter volumes in similar, predominantly subcortical regions. In contrast, the severity of neurological deficits did not correlate with the volume of white matter hyperintensities, calculated using an automated lesion segmentation algorithm. Using tract-based spatial statistics, increasing neurological severity in chronically treated patients was associated with decreasing axial diffusivity in white matter tracts whereas increasing serum non-caeruloplasmin-bound (‘free’) copper and active disease were associated with distinct patterns of increasing mean, axial and radial diffusivity. Whole-brain quantitative susceptibility mapping identified increased iron deposition in the putamen, cingulate and medial frontal cortices of patients with neurological presentations relative to those with hepatic presentations and neurological severity was associated with iron deposition in widespread cortical regions in chronically treated patients.Our data indicate that composite measures of subcortical atrophy provide useful prognostic biomarkers, whereas abnormal mean, axial and radial diffusivity are promising monitoring biomarkers. Finally, deposition of brain iron in response to copper accumulation may directly contribute to neurodegeneration in Wilson’s disease.

Measurement of Cortical Atrophy and Its Correlation to Memory Impairment in Patients With Asymptomatic Carotid Artery Stenosis Based on VBM-DARTEL.

ObjectiveSevere carotid artery stenosis (CAS) can lead to atrophy of gray matter (GM) and memory impairment; however, the underlying mechanism is unknown. Thus, we aimed to identify memory impairment and GM atrophy and explore the possible correlation between them in patients with asymptomatic severe CAS.MethodsTwenty-four patients with asymptomatic severe CAS and 10 healthy controls completed the mini-mental state examination (MMSE) and clinical memory scale (CMS) and underwent 7T magnetic resonance imaging (MRI) scan. Field intensity inhomogeneities were corrected. Images were processed using VBM8, and GM images were flipped. First, 11 flipped and 10 non-flipped images of patients with unilateral CAS and 5 flipped and 5 non-flipped images of controls were pre-processed using DARTEL algorithm and analyzed using an analysis of variance (ANOVA). Second, flipped and non-flipped images of unilateral patients were similarly pre-processed and analyzed using the paired t-test. Third, pre-processed non-flipped GM images and CMS scores of 24 patients were analyzed by multiple regression analysis. Nuisance variables were corrected accordingly.ResultsBasic information was well matched between patients and controls. MMSE scores of patients were in the normal range; however, memory function was significantly reduced (all P < 0.05). GM volumes of patients were significantly reduced in the anterior circulation regions. The stenosis-side hemispheres showed greater atrophy. GM volumes of the left pars opercularis, pars triangularis, and middle frontal gyrus were strongly positively correlated with the total scores of CMS (all r > 0.7, P = 0.001). Additionally, the left middle frontal gyrus was strongly positively correlated with associative memory (r = 0.853, P = 0.001). The left pars opercularis was moderately positively correlated with semantic memory (r = 0.695, P = 0.001).ConclusionPatients with asymptomatic CAS suffer from memory impairment. Bilateral anterior circulation regions showed extensive atrophy. The hemisphere with stenosis showed severer atrophy. Memory impairment in patients may be related to atrophy of the left frontal gyrus and atrophy of different regions may result in different memory impairments.

Network-constrained technique to characterize pathology progression rate in Alzheimer's disease.

Current methods for measuring the chronic rates of cognitive decline and degeneration in Alzheimer’s disease rely on the sensitivity of longitudinal neuropsychological batteries and clinical neuroimaging, particularly structural magnetic resonance imaging of brain atrophy, either at a global or regional scale. There is particular interest in approaches predictive of future disease progression and clinical outcomes using a single time point. If successful, such approaches could have great impact on differential diagnosis, therapeutic treatment and clinical trial inclusion. Unfortunately, it has proven quite challenging to accurately predict clinical and degeneration progression rates from baseline data. Specifically, a key limitation of the previously proposed approaches for disease progression based on the brain atrophy measures has been the limited incorporation of the knowledge from disease pathology progression models, which suggest a prion-like spread of disease pathology and hence the neurodegeneration. Here, we present a new metric for disease progression rate in Alzheimer that uses only MRI-derived atrophy data yet is able to infer the underlying rate of pathology transmission. This is enabled by imposing a spread process driven by the brain networks using a Network Diffusion Model. We first fit this model to each patient’s longitudinal brain atrophy data defined on a brain network structure to estimate a patient-specific rate of pathology diffusion, called the pathology progression rate. Using machine learning algorithms, we then build a baseline data model and tested this rate metric on data from longitudinal Alzheimer’s Disease Neuroimaging Initiative study including 810 subjects. Our measure of disease progression differed significantly across diagnostic groups as well as between groups with different genetic risk factors. Remarkably, hierarchical clustering revealed 3 distinct clusters based on CSF profiles with >90% accuracy. These pathological clusters exhibit progressive atrophy and clinical impairments that correspond to the proposed rate measure. We demonstrate that a subject’s degeneration speed can be best predicted from baseline neuroimaging volumetrics and fluid biomarkers for subjects in the middle of their degenerative course, which may be a practical, inexpensive screening tool for future prognostic applications.

Brain Atrophy and Physical and Cognitive Disability in Multiple Sclerosis.

Brain atrophy is associated with physical disability in multiple sclerosis (MS), but there is a great variability between different studies and methodologies, and its use is still limited to research projects. We aimed to analyze the relationship between several volumetric measurements and physical disability and cognitive functioning in MS patients in a clinical practice setting. This is a cross-sectional study. A total of 41 patients (31 relapsing-remitting MS, 6 secondary-progressive MS, and 4 primary-progressive MS) were included. Whole brain volume (WBV), gray matter volume (GMV), and T2 lesion load (T2L) were obtained using Icometrix® software. Physical disability was measured with the Expanded Disability Status Scale (EDSS), and cognitive status was evaluated with the brief repeatable battery of neuropsychological tests (BRB-N). The relationship between brain volumes and EDSS was analyzed through linear multivariate regression. The association between volumetry measurements and the number of affected cognitive domains was studied with negative binomial regression. GMV was associated with age (b=-1.7, P=0.014) and with EDSS (b=-7.55, P=0.013). T2L was associated with EDSS (b=2.29, P=0.032). The number of affected cognitive domains was associated with clinical phenotype, worse in primary progressive MS (PPMS). There was not correlations between cognitive impairment and cerebral volumes. Brain atrophy measurement is feasible in clinical practice setting, and it is helpful in monitoring the EDSS progression. Primary progressive phenotype is associated with greater risk of cognitive dysfunction. The T2 lesion load is associated with physical disability in patients with multiple sclerosis (MS).The gray matter volume is associated with age and physical disability in patients with MS.There is no significant correlation between cognitive impairment and cerebral volumes in patients with MS. Conventional magnetic resonance imaging (MRI) is still used for diagnosing and monitoring multiple sclerosis (MS). Analysis of Brain volumes including Whole brain volume (WBV), gray matter volume (GMV), and T2 lesion load (T2L) allows the evaluation of its neurodegenerative mechanisms. Robust evidence links brain atrophy with disability in MS. This study aims to analyze the relationship between advanced MRI sequences and physical disability and cognitive functioning in MS patients. According to the results, T2L was associated with physical disability and GMV was associated with age and physical disability. There was no significant correlation between cognitive impairment and cerebral volumes in patients with MS.

Clinical predictors and neural correlates for compromised swallowing safety in Huntington disease.

Dysphagia is one of the most common and important complications in Huntington disease (HD), frequently leading to aspiration pneumonia and mortality. Objective estimates of prevalence using instrumental diagnostics and data on neural correlates of dysphagia in HD are scarce or lacking entirely. Similarly, its correlation with other clinical markers is still not fully known. We aimed at defining clinical risk factors and neural correlates for compromised swallowing safety in HD more precisely. Thirty-four HD subjects (16 female, Shoulson & Fahn Stage I-IV, two premanifest) underwent a full clinical-neurological examination including the cranial nerves, the Unified Huntington's Disease Rating Scale total motor score, and the Mini-Mental State Examination. Fiberoptic endoscopic evaluation of swallowing (FEES) was performed by a trained speech and language therapist. Twenty-sixsubjects additionally underwent a high-resolution anatomical magnetic resonance imaging (MRI) scan (T1, 3-T Siemens Prisma). Moreover, we correlated clinical and atrophy (MRI) measures with swallowing safety levels as judged by the validated Penetration-Aspiration Scale. FEES showed penetration or aspiration in 70.6%. Using partial correlation, no significant correlations were found between swallowing safety and any of the clinical markers after correcting for disease duration and CAG repeat length. Voxel-based morphometry demonstrated atrophy associated with compromised swallowing safety in a network of parietothalamocerebellar areas related to sensorimotor communication, notably excluding striatum. Our results characterise dysphagia in HD as a disorder of communication between sensory and motor networks involved in swallowing. This finding and high rates of silent aspiration argue in favor of instrumental swallowing evaluation early in the disease.

Pathogenesis of Chronic Subdural Hematoma: A Cohort Evidencing De Novo and Transformational Origins.

Chronic subdural hematoma (CSDH) is a common neurosurgical pathology, yet conflicting opinions exist concerning the pathophysiological processes involved. Many consider CSDH a product of an aged acute subdural hematoma (ASDH) secondary to trauma. Serial imaging, however, has demonstrated CSDH formation in patients without any initial ASDH. To understand the relevance of acute hemorrhage in a cohort of patients with CSDH, transformation from an ASDH were categorized as CSDH-acute transformed (CSDH-AT) and those without any acute hemorrhage at the outset as CSDH-de-novo (CSDH-DN). A cohort of 41 eligible patients with CSDH were included, with baseline imaging after trauma (or spontaneous ASDH) available for assessment of acute hemorrhage. Volumetric analysis of all subdural collections and measurements of baseline atrophy were performed. In 37% of cases, there was an ASDH present on baseline imaging (CSDH-AT), whereas 63% had no acute hemorrhage at baseline (CSDH-DN). The CSDH-ATs developed more rapidly (mean 16 days from baseline to diagnosis) and were smaller in volume than the CSDH-DNs, which developed at a mean delay of 57 days. In 54% of the CSDH-DNs, a subdural hygroma was present on baseline imaging, and there was a wide range of baseline cerebral atrophy. This study provides radiological evidence for two distinct pathways in the formation of CSDH, with CSDH-DN occurring more commonly and often involving subdural hygroma. Further work is needed to understand whether the pathological origin has implications for patient outcome.