Search

Diffusely abnormal white matter, characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive multiple sclerosis. However, little is known about changes of diffusely abnormal white matter over time and their relation to focal white matter lesions. The objectives of this work were: (i) to characterize the longitudinal evolution of focal white matter lesions, diffusely abnormal white matter and diffusely abnormal white matter that transforms into focal white matter lesions; and (ii) to determine whether gadolinium enhancement, known to be associated with the development of new focal white matter lesions, is also related to diffusely abnormal white matter voxels that transform into focal white matter lesions. Our data included 4220 MRI scans of 689 secondary progressive multiple sclerosis participants, followed for 156 weeks, and 2677 scans of 686 relapsing-remitting multiple sclerosis participants, followed for 96 weeks. Focal white matter lesions and diffusely abnormal white matter were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, diffusely abnormal white matter voxels at each visit that transformed into focal white matter lesions on the last MRI scan as well as their overlap with gadolinium-enhancing lesion masks were identified. Our results showed that the average yearly rate of conversion of diffusely abnormal white matter to focal white matter lesions was 1.27 cm3 for secondary progressive multiple sclerosis and 0.80 cm3 for relapsing-remitting multiple sclerosis. Focal white matter lesions in secondary progressive multiple sclerosis participants significantly increased (t = 3.9; P = 0.0001) while diffusely abnormal white matter significantly decreased (t = −4.3 P We conclude that diffusely abnormal white matter transforms into focal white matter lesions over time in both relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis. Diffusely abnormal white matter appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

White matter hyperintensities (WMHs) are pathological changes that occur with increased age and are associated with cognitive decline. Most WMH research has not examined regional differences and focuses on a whole-brain approach. This study examined regional WMHs between normal controls (NCs), people with mild cognitive impairment (MCI), and Alzheimer's disease (AD). We also examined whether WMHs were associated with cognitive decline. Participants from the Alzheimer's Disease Neuroimaging Initiative were included if they had at least one WMH measurement and cognitive scores examining global cognition, executive functioning, and memory. Only amyloid-positive MCI and AD participants were included. A total of 1573 participants with 7381 timepoints over a maximum period of 13 years were included. Linear mixed-effects models examined group differences in WMH burden and associations between WMH burden and cognition. People with MCI and AD had increased total and regional WMHs compared to NCs. An association between WMHs and cognition was observed for global cognition, executive functioning, and memory in NCs in all regions. A steeper decline (stronger association between WMH and cognition) was observed in MCI compared to NCs for all cognitive domains in all regions. A steeper decline was observed in AD compared to NCs for global cognition in only the temporal region. A strong association is observed between all cognitive domains of interest and WMH burden in healthy aging and MCI, while those with AD only had a few associations between WMH and global cognition. These findings suggest that the WMH burden is associated with changes in cognition in healthy aging and early cognitive decline.

IntroductionCerebral microbleeds are small perivascular haemorrhages that can occur in both grey and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology, and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to inter- and intra-rater variabiltiy. Automated techniques so far have shown high accuracy at a neighborhood (“patch”) level at the expense of a high number of false positives voxel-wise lesions. We aimed to develop an automated, more precise microbleeds segmentation tool able to use standardizable MRI contrasts.MethodsWe first trained a ResNet50 network on another MRI segmentations task (cerberospinal fluid versus background segmentation) using T1-weighted, T2-weighted, and T2* MRI. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentations of microbleeds from 78 participants were used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, as well as data augmentation on the performance of the Microbleed ResNet50 network.ResultsThe proposed method achieved a high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57%, 99.16%, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1%, 20.1%, and 0.28 for cortical GM; 100%, 100%, and 1.0 for deep GM; and 91.1%, 44.3%, and 0.58 for WM, respectively.DiscussionThe proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity.

OBJECTIVES Cortical demyelination is common in multiple sclerosis (MS) and can be extensive. Cortical lesions contribute to disability independently from white matter lesions and may form via a distinct mechanism. However, current magnetic resonance imaging methods at 3 T are insensitive to cortical, and especially subpial cortical, lesions. Subpial lesions are well seen on T2*-weighted imaging at 7 T, but T2*-weighted methods on 3 T scanners are limited by poor lesion-to-cortex and cerebrospinal fluid-to-lesion contrast. We aimed to develop and evaluate a cerebrospinal fluid-suppressed, T2*-weighted sequence optimized for subpial cortical lesion visualization. MATERIALS AND METHODS We developed a new magnetic resonance imaging sequence, inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET; 0.8 mm × 0.8 mm in plane, 0.64 mm slice thickness with whole brain coverage, acquisition time ~5 minutes). We compared cortical lesion visualization independently on IR-SWIET (median signal from 4 acquisitions), magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE), double inversion recovery (DIR), T2*-weighted segmented echo-planar imaging, and phase-sensitive inversion recovery images for 10 adults with MS. We also identified cortical lesions with a multicontrast reading of IR-SWIET (median of 2 acquisitions), MP2RAGE, and fluid-attenuated inversion recovery (FLAIR) images for each case. Lesions identified on 3 T images were verified on "gold standard" 7 T T2* and MP2RAGE images. RESULTS Cortical, and particularly subpial, lesions appeared much more conspicuous on IR-SWIET compared with other 3 T methods. A total of 101 true-positive subpial lesions were identified on IR-SWIET (average per-participant sensitivity vs 7 T, 29% ± 8%) versus 36 on MP2RAGE (5% ± 2%; comparison to IR-SWIET sensitivity, P = 0.07), 17 on FLAIR (2% ± 1%; P < 0.05), 28 on DIR (6% ± 2%; P < 0.05), 42 on T2*-weighted segmented echo-planar imaging (11% ± 5%; P < 0.05), and 13 on phase-sensitive inversion recovery (4% ± 2%; P < 0.05). When a combination of IR-SWIET, MP2RAGE, and FLAIR images was used, a total of 147 subpial lesions (30% ± 5%) were identified versus 83 (16% ± 3%, P < 0.01) on a combination of DIR, MP2RAGE, and FLAIR. More cases had at least 1 subpial lesion on IR-SWIET, and IR-SWIET improved cortical lesion subtyping accuracy and correlation with 7 T subpial lesion number. CONCLUSIONS Subpial lesions are better visualized on IR-SWIET compared with other 3 T methods. A 3 T protocol combining IR-SWIET with MP2RAGE, in which leukocortical lesions are well seen, improves cortical lesion visualization over existing approaches. Therefore, IR-SWIET may enable improved MS diagnostic specificity and a better understanding of the clinical implications of cortical demyelination.

Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P

Manually segmenting multiple sclerosis (MS) cortical lesions (CL) is extremely time-consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep learning-based framework (CLAIMS: Cortical Lesion Artificial Intelligence-based assessment in Multiple Sclerosis) for the automated detection and classification of MS CL with 7T MRI.Two 7T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5mm isotropic MP2RAGE acquired 4 times (MP2RAGEx4), 0.7mm MP2RAGE, 0.5mm T2*-weighted GRE, and 0.5mm T2*-weighted EPI. The second dataset consisted of 20 scans including only 0.75×0.75×0.9 mm MP2RAGE. CLAIMS was first evaluated using 6-fold cross-validation with single and multi-contrast 0.5mm MRI input. Second, performance of the model was tested on 0.7mm MP2RAGE images after training with either 0.5mm MP2RAGEx4, 0.7mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state-of-the-art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGEx4 achieved comparable results to the multi-contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain-scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6μL (lesion-wise detection rate of 71% vs 48%).The proposed framework outperforms previous state-of-the-art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7T MRI, especially in the field of diagnosis and differential diagnosis of multiple sclerosis patients.

Background: Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course. Objective: Characterize cortical lesions by 7 tesla (T) T2*-/T1-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability. Methods: Sixty-four adults with MS (45 relapsing–remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing. Results: Cortical lesions were found in 94% (progressive: median 56/range 2–203; relapsing–remitting: 15/0–168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform ( p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated ( r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated ( r = 0.30, p = 0.002). Leukocortical ( p = 0.02) but not subpial lesions ( p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions ( p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores. Conclusion: Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.

Surgical treatment of kidney cancer with a tumor thrombus spreading through the inferior vena cava (IVC) up to the right atrium remains a challenge.The aim of this article was to 1. assess the safety and feasibility of four transdiaphragmatic surgical approaches to the right atrium from the abdominal cavity; 2. to evaluate the feasibility of palpation and displacement of thrombi below the diaphragm.Four cadaveric specimens preserved with the Thiel method to assess each surgical access: 1) extrapericardial T-shaped diaphragmotomy, 2) extrapericardial T-shaped + circular diaphragmotomy, 3) transpericardial T-shaped diaphragmotomy with longitudinal pericardiotomy, 4) transpericardial T-shaped + circular diaphragmotomy with longitudinal and circular pericardiotomy.Different diameters and density of tumor thrombus simulators, placed at various levels from the cava-diaphragm junction, were used to evaluate the palpation and displacement of the thrombus. Two surgeons performed each assessment independently.Approaches 2, 3 and 4 were significantly better than approach 1, regarding the feasibility of palpation, according to both surgeons (surgeon 1 Chi-square 21.56, p = 0.001; surgeon 2 Chi-square 27.83, p0.0001). Approach 1 also showed a significant higher number of impossible displacements recorded by both surgeons (surgeon 1 Chi-square 19.02, p = 0.004; surgeon 2 Chi-square 20.01, p = 0.003). Only surgeon 1 recorded a significant lower number of easy palpations at 4 cm from the cava-diaphragm junction (Chi-square 14.10, p = 0.007). There were no high-risk complications in any approach.The transdiaphragmatic access to the right atrium from the abdominal cavity is feasible using three of the four surgical approaches. They are an adequate alternative to sternotomy.

Long-term cognitive deficits have been observed in some children who experience an acquired demyelinating syndrome (ADS). We examined changes in cognitive functioning over the first two years following incident ADS andtested whether normalized brain and thalamic volume accounted for decline over time. Twenty-five youth (mean age 12.8 years) with ADS, 9 of whom were diagnosed with multiple sclerosis (MS) and 16 of whom experienced monophasic ADS (monoADS), underwent two neuropsychological evaluationsand MRI scans at approximately6- and 24-months post ADS-onset. We examined changes in cognitive outcomes over time and between patient groups. Generalized linear mixed-effect regression models were used to examine the association of normalized brain and thalamic volumesbetween the two timepointswith cognitive z-scores. Cognitive performance was within the age-expected range for both groups and remained stable over time on 15 measures. In the combined sample of monoADS and MS patients, declines (

IntroductionWhite matter hyperintensities (WMHs) are common magnetic resonance imaging (MRI) findings in the aging population in general, as well as in patients with neurodegenerative diseases. They are known to exacerbate the cognitive deficits and worsen the clinical outcomes in the patients. However, it is not well-understood whether there are disease-specific differences in prevalence and distribution of WMHs in different neurodegenerative disorders.MethodsData included 976 participants with cross-sectional T1-weighted and fluid attenuated inversion recovery (FLAIR) MRIs from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort of the Canadian Consortium on Neurodegeneration in Aging (CCNA) with eleven distinct diagnostic groups: cognitively intact elderly (CIE), subjective cognitive impairment (SCI), mild cognitive impairment (MCI), vascular MCI (V-MCI), Alzheimer’s dementia (AD), vascular AD (V-AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), cognitively intact elderly with Parkinson’s disease (PD-CIE), cognitively impaired Parkinson’s disease (PD-CI), and mixed dementias. WMHs were segmented using a previously validated automated technique. WMH volumes in each lobe and hemisphere were compared against matched CIE individuals, as well as each other, and between men and women.ResultsAll cognitively impaired diagnostic groups had significantly greater overall WMH volumes than the CIE group. Vascular groups (i.e. V-MCI, V-AD, and mixed dementia) had significantly greater WMH volumes than all other groups, except for FTD, which also had significantly greater WMH volumes than all non-vascular groups. Women tended to have lower WMH burden than men in most groups and regions, controlling for age. The left frontal lobe tended to have a lower WMH burden than the right in all groups. In contrast, the right occipital lobe tended to have greater WMH loads than the left.ConclusionsThere were distinct differences in WMH prevalence and distribution across diagnostic groups, sexes, and in terms of asymmetry. WMH burden was significantly greater in all neurodegenerative dementia groups, likely encompassing areas exclusively impacted by neurodegeneration as well as areas related to cerebrovascular disease pathology.

Diffusely abnormal white matter (DAWM), characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive MS (SPMS). However, little is known about changes of DAWM over time and their relation to focal white matter lesions (FWML).The objectives of this work were: 1) To characterize the longitudinal evolution of FWML, DAWM, and DAWM that transforms into FWML, and 2) To determine whether gadolinium enhancement, known to be associated with the development of new FWML, is also related to DAWM voxels that transform into FWML.Our data included 4220 MRI scans of 689 SPMS participants, followed for 156 weeks and 2677 scans of 686 RRMS participants, followed for 96 weeks. FWML and DAWM were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, DAWM voxels at each visit that transformed into FWML on the last MRI scan as well as their overlap with gadolinium enhancing lesion masks were identified.Our results showed that the average yearly rate of conversion of DAWM-to-FWML was 1.27cc for SPMS and 0.80cc for RRMS. FWML in SPMS participants significantly increased (t=3.9; p=0.0001) while DAWM significantly decreased (t=-4.3 pWe conclude that DAWM transforms into FWML over time, in both RRMS and SPMS. DAWM appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

BACKGROUND AND PURPOSE: Our aims were the following: 1) to compare multicontrast cortical lesion detection using 3T and 7T MR imaging, 2) to compare cortical lesion type frequency in relapsing-remitting and secondary-progressive MS, and 3) to assess whether detectability is related to the magnetization transfer ratio, an imaging marker sensitive to myelin content. MATERIALS AND METHODS: Multicontrast 3T and 7T MR images from 10 participants with relapsing-remitting MS and 10 with secondary-progressive MS. We used the following 3T contrast sequences: 3D-T1-weighted, quantitative T1, FLAIR, magnetization-transfer, and 2D proton-density- and T2-weighted. We used the following 7T contrast sequences: 3D-T1-weighted, quantitative T1, and 2D-T2*-weighted. RESULTS: Cortical lesion counts at 7T were the following: 720 total cortical lesions, 420 leukocortical lesions (58%), 27 intracortical lesions (4%), and 273 subpial lesions (38%). Cortical lesion counts at 3T were the following: 424 total cortical, 393 leukocortical (93%), zero intracortical, and 31 subpial (7%) lesions. Total, intracortical, and subpial 3T lesion counts were significantly lower than the 7T counts (P < .002). Leukocortical lesion counts were not significantly different between scanners. Total and leukocortical lesion counts were significantly higher in secondary-progressive MS, at 3T and 7T (P ≤ .02). Subpial lesions were significantly higher in secondary-progressive MS at 7T (P = .006). The magnetization transfer ratio values of leukocortical lesions visible on both scanners were significantly lower than the magnetization transfer ratio values of leukocortical lesions visible only at 3T. No significant difference was found in magnetization transfer ratio values between subpial lesions visible only at 7T and subpial lesions visible on both 3T and 7T. CONCLUSIONS: Detection of leukocortical lesions at 3T is comparable with that at 7T MR imaging. Imaging at 3T is less sensitive to intracortical and subpial lesions. Leukocortical lesions not visible on 7T T2*-weighted MRI may be associated with less demyelination than those that are visible. Detectability of subpial lesions does not appear to be related to the degree of demyelination.

OBJECTIVE: The objective of this study is to investigate whether cerebral small vessel disease (CSVD) is more common in virologically suppressed HIV-positive participants compared with HIV-negative controls and examine the potential synergistic effects of HIV and CSVD on brain structure and cognition. DESIGN: Cross-sectional analysis of 119 treated, virologically suppressed HIV-positive and 55 HIV-negative participants. Forty-six HIV-positive and 30 HIV-negative participants had follow-up 2 years later. All participants underwent MRI and neuropsychological testing. METHODS: Volume of white matter hyperintensities (WMH) was used as a surrogate measure of CSVD severity. Tensor-based morphometry and cortical modeling estimated brain volumes and cortical thickness, respectively. Rasch measurement theory was applied to neuropsychological test scores to estimate overall cognition. Linear models compared WMH loads, brain volumes, and cognition between groups; evaluated the association of WMH loads with brain volumes and cognition; and tested the interaction between HIV and WMH loads on brain volumes and cognition. Mixed-effects models compared the change in WMH loads between groups. RESULTS: WMH loads and change in WMH loads were similar between the groups. HIV-positive participants had poorer cognition, thinner cortex and reduced subcortical volumes compared with HIV-negative controls. Higher WMH loads were associated with reduced cortical thickness and subcortical volumes and worse cognition, regardless of HIV serostatus. No significant interactions were observed between HIV and WMH loads with regards to brain volumes or cognition. CONCLUSION: These findings suggest that the contributions of HIV and CSVD on brain atrophy and cognitive impairment are independent but additive processes. This argues that optimizing vascular health may mitigate brain injury and cognitive decline, especially in treated, virologically suppressed HIV-positive individuals.

Cortical atlases constitute a consistent division of the human cortex into areas that have common structural as well as meaningful and distinctive functional characteristics. The most widely used atlases follow the cytoarchitectonic and myeloarchitectonic characteristics of the cortex and have been combined to the standard anatomical nomenclature of gyri and sulci. More recently, common functional features depicted by resting state functional MRI have also guided the division of the cortical brain in functional regions of interest. However, to date, there are no atlases that divide the cortex considering the common evolutionary changes experienced by the mammalian cortex.Hence, the present study proposes the division of cortical areas into five main regions of interest (ROIs) following a phylogenetic approach: 1- archicortex, 2- paleocortex, 3- peri-archicortex, 4- proisocortex, 5-neocortex, and twelve neocortical sub-ROIs: 5.1.temporopolar, 5.2.post-central, 5.3.pre-central, 5.4.pericalcarine, 5.5.superior temporal, 5.6.middle temporal, 5.7.precuneus, 5.8.insular, 5.9.inferior parietal, 5.10.caudal anterior, 5.11.posterior cingulate, and 5.12.lingual gyrus.The segmentations were done using the T1-weighted MNI-ICBM152 non-linear 6th generation symmetric average brain MRI model.

BackgroundPrevious histopathology and MRI studies have addressed the differences between focal white matter lesions (FWML) and diffusely abnormal white matter (DAWM) in multiple sclerosis (MS). These two categories of white matter T2-weighted (T2w) hyperintensity show different degrees of demyelination, axonal loss and immune cell density on histopathology, potentially offering distinct correlations with symptoms.Objectives1) To automate the separation of FWML and DAWM using T2w MRI intensity thresholds and to investigate their differences in magnetization transfer ratios (MTR), which are sensitive to myelin content; 2) to correlate MTR values in FWML and DAWM with normalized signal intensity values on fluid attenuated inversion recovery (FLAIR), T2w, and T1-weighted (T1w) contrasts, as well as with the ratio of T2w/T1w normalized values, in order to determine whether these normalized intensities can be used as myelin-sensitive markers when MTR is not available.MethodsUsing similar 3T MRI protocols, 2 MS cohorts of 20 participants each were scanned in 2 centers, including: 3D T1w (MP2RAGE), 3D FLAIR, 2D T2w, and 3D magnetization-transfer (MT) contrasts. We used the first dataset to develop an automated technique to separate FWML from DAWM and the second one to validate the automation of the technique. We applied the automatic thresholds to both datasets and assessed the overlap of the manual and the automated masks using Dice kappa. We also assessed differences in mean MTR values between NAWM, DAWM and FWML, using manually and automatically derived masks in both datasets. Finally, we used the mean intensity of manually-traced areas of NAWM on T2w images as the normalization factor for each MRI contrast, and compared these with the normalized-intensity values obtained using automated NAWM (A-NAWM) masks as the normalization factor. Paired t-tests assessed the MTR differences across tissue types. Wilcoxon Signed Rank test and paired t-tests assessed FWML and DAWM differences in manual and automated derived volumes. Pearson correlations assessed the relationship between MTR and normalized intensity values in the manual and automated derived masks.ResultsThe mean Dice-kappa values for dataset 1 were: 0.8 for DAWM masks and 0.7 for FWML masks. In dataset 2, mean dice-kappa values were: 0.8 for DAWM and 0.8 for FWML. Also, manual and automated DAWM and FWML volumes were not significantly different in both datasets. MTR values (expressed as mean and standard deviation, arbitrary units) were significantly lower in manually derived FWML compared with DAWM in both datasets: 1) FWML: 37.1 ± 3.2 vs DAWM: 43.3 ± 2.1; t=13.2; pIn both datasets, manually derived FWML and DAWM MTR values showed significant correlations with normalized FLAIR (r=−0.35 to −0.67; p=0.06 to ConclusionsThe separation of FWML and DAWM on MRI scans of MS patients using automated intensity thresholds on T2w images is feasible. MTR values are significantly lower in FWML than DAWM, and DAWM values are significantly lower than NAWM, reflecting potentially greater demyelination within focal lesions. Normalized intensity values of different MRI contrasts exhibit a significant correlation with MTR values in both tissues of interest and could be used as a proxy to assess demyelination when MTR images are not available.

Summary Background The thigh region is a well-known area for harvesting cutaneous flaps for microsurgery replacement, given the characteristics of the skin: thin, flexible, and glabrous. We investigated the vascular pattern of 32 cadaveric anteroproximal thighs for the possibility of an extended harvesting area, which we call the proximal femoral artery perforator region. Materials and methods We injected colored, radio opaque latex in the external iliac artery and investigated the perforator branches from the superficial circumflex iliac, femoral common, superficial, and deep femoral (profunda femoris) arteries to the skin of the proximal femoral artery perforator region. This region was divided into 3 equal subregions (superior, medial, and lateral), and their perforators were counted and measured. Results There was no significant difference in the number of arterial pedicles across the three subregions: 30 superior, 35 inferolateral, and 27 inferomedial. The perforators had a cutaneous path in 81% of the cases, while 6% were musculocutaneous and 5% septocutaneous, without a significant difference in their proportion in the three subregions. The mean length and diameter of the pedicles were 5.39 ± 2.1 cm and 1.07 ± 0.4 mm, respectively, without significant differences in the three subregions. Conclusions The proximal femoral artery perforator region is a suitable area to generate flaps of various sizes and shapes, as needed by the surgeon. All perforators were constant and possessed a sufficient diameter and length for a successful anastomosis during the surgical procedure. The donor site retains all technical advantages to successfully replace areas of glabrous skin.

MRI-histology correlation studies of the ex vivo brain mostly employ fresh, extracted (ex situ) specimens, aldehyde fixed by immersion. This method entails manipulation of the fresh brain during extraction, introducing several disadvantages: deformation of the specimen prior to MRI acquisition; introduction of air bubbles in the sulci, creating artifacts; and uneven or poor fixation of the deeper regions of the brain.We propose a new paradigm to scan the ex vivo brain, exploiting a technique used by anatomists: fixation by whole body perfusion, which implies fixation of the brain in situ. This allows scanning the brain surrounded by fluids, meninges, and skull, thus preserving the structural relationships of the brain in vivo and avoiding the disadvantages of ex situ scanning. Our aims were: 1) to assess whether months of in situ fixation resulted in a loss of fluid around the brain; 2) to evaluate whether in situ fixation modified antigenicity for myelin and neuron specific marker; 3) to assess whether in situ fixation improved the register of ex vivo brain images to standard neuroanatomical templates in pseudo-Talairach space for morphometry studies.Five head specimens fixed with a saturated sodium chloride solution (a non-standard fixative used in our anatomy laboratory for neurosurgical simulation) were employed. We acquired 3D T1-weighted (MPRAGE), 2D fluid-attenuated inversion recovery T2-weighted turbo spin echo (T2w-FLAIR), and 3D gradient-echo (3D-GRE) pulse sequences of all brains on a 1.5T MRI. After brain extraction, sections were processed for binding with myelin basic protein (MBP) and neuronal nuclei (NeuN) primary antibodies by immunofluorescence.This study showed that all but one specimen retained fluids in the subarachnoid and ventricular spaces. The specimen that lost fluid was the oldest one, with the longest interval between the time of death and the MRI scanning day being 403 days. All T1-weighted images were successfully processed through a validated pipeline used with in vivo MRIs. The pipeline did not require any modification to run on the ex vivo-in situ scans. All scans were successfully registered to the brain template, more accurately than an ex vivo-ex situ scan and exhibited positive antigenicity for MBP and NeuN.MRI and histology study of the ex vivo-in situ brain fixed by perfusion is feasible and allows for in situ MRI imaging for of at least 10 months post-mortem prior to histology analyses. Fluids around and inside the brain specimens and antigenicity for myelin and neurons were all well preserved.

White Matter Hyperintensities (WMHs) are associated with cognitive decline in aging and Alzheimer's disease. However, the pathogenesis of cognitive decline in Parkinson's disease (PD) is not as clearly related to vascular causes, and therefore the role of WMHs as a marker of small-vessel disease (SVD) in PD is less clear. Currently, SVD in PD is assessed and treated independently of the disease. However, if WMH as the major MRI sign of SVD has a higher impact on cognitive decline in PD patients than in healthy controls, vascular pathology needs to be assessed and treated with a higher priority in this population. Here we investigate whether the presence of WMHs leads to increased cognitive decline in de novo PD, and if these effects relate to cortical atrophy. WMHs and cortical thickness were measured in de novo PD patients and age-matched controls (NPD = 365, NControl = 174) from Parkinson's Progression Markers Initiative (PPMI) to study the relationship between baseline WMHs, future cognitive decline (follow-up: 4.09 ± 1.14 years) and cortical atrophy (follow-up: 1.05 ± 0.10 years). PD subjects with high baseline WMH loads had significantly greater cognitive decline than i) PD subjects with low WMH load, and ii) control subjects with high WMH load. Furthermore, in PD subjects, high WMH load resulted in more cortical thinning in the right frontal lobe. Theses results show that the presence of WMHs in de novo PD patients predicts greater future cognitive decline and cortical atrophy than in normal aging., Highlights • High WMH loads cause greater cognitive decline in PD patients compared to controls. • Higher WMH loads cause greater future cortical atrophy in PD patients. • WMHs interact with PD to increase future cognitive decline. • Baseline WMHs are linked with future decline in different cognitive domains in PD.

Objective: To determine the frequency of cortical lesions (CLs) in patients with pediatric-onset multiple sclerosis (POMS) using multi-contrast magnetic resonance imaging (MRI), and the relationship between frontal CL load and upper limb dexterity assessed with the Nine-Hole Peg Test (9-HPT). Methods: Participants completed the 9-HPT and were imaged on a 3T MRI scanner to collect T1-weighted three-dimensional (3D) magnetization prepared rapid gradient echo (MPRAGE), proton density–weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) images. CLs were manually segmented using all MRI contrasts. Results: We enrolled 24 participants with POMS (mean (standard deviation) age at first symptom: 13.3 (±2.7) years; mean age at scan: 18.8 (±3) years; mean disease duration of 5 (±3.2) years). A total of 391 CLs (mean, 16.3 ± 27.2; median, 7) were identified in 19 of 24 POMS patients (79%). The total number of CLs was positively associated with white matter lesion volume ( p = 0.04) but not with thalamic volume, age at the time of the scan, or disease duration. The number of frontal CLs was associated with slower performance on the 9-HPT ( p = 0.05). Conclusion: Multi-contrast 3T MRI led to a high rate of CL detection, demonstrating that cortical pathology occurs even in pediatric-onset disease. Frontal lobe CL count was associated with reduced manual dexterity, indicating that these CLs are clinically relevant.

Introduction Fluid-attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter hyperintensities (WMHs) in aging and Alzheimer's disease populations. However, many existing large multisite studies forgo their acquisition in favor of other MRI sequences due to economic and time constraints. Methods In this article, we have investigated whether FLAIR and T2w/PD sequences are necessary to detect WMHs in Alzheimer's and aging studies, compared to using only T1w images. Using a previously validated automated tool based on a Random Forests classifier, WMHs were segmented for the baseline visits of subjects from ADC, ADNI1, and ADNI2/GO studies with and without T2w/PD and FLAIR information. The obtained WMH loads (WMHLs) in different lobes were then correlated with manually segmented WMHLs, each other, age, cognitive, and clinical measures to assess the strength of the correlations with and without using T2w/PD and FLAIR information. Results The WMHLs obtained from T1w-Only segmentations correlated with the manual WMHLs (ADNI1: r = .743, p

Introduction White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown. Methods We compare 10 different linear and nonlinear classification techniques to identify WMHs from MRI data. Each classifier is trained and optimized based on a set of features obtained from co-registered MR images containing spatial location and intensity information. We further assess the performance of the classifiers using different combinations of MRI contrast information. The performances of the different classifiers were compared on three heterogeneous multi-site datasets, including images acquired with different scanners and different scan-parameters. These included data from the ADC study from University of California Davis, the NACC database and the ADNI study. The classifiers (naive Bayes, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, bagging, and boosting) were evaluated using a variety of voxel-wise and volumetric similarity measures such as Dice Kappa similarity index (SI), Intra-Class Correlation (ICC), and sensitivity as well as computational burden and processing times. These investigations enable meaningful comparisons between the performances of different classifiers to determine the most suitable classifiers for segmentation of WMHs. In the spirit of open-source science, we also make available a fully automated tool for segmentation of WMHs with pre-trained classifiers for all these techniques. Results Random Forests yielded the best performance among all classifiers with mean Dice Kappa (SI) of 0.66±0.17 and ICC=0.99 for the ADC dataset (using T1w, T2w, PD, and FLAIR scans), SI=0.72±0.10, ICC=0.93 for the NACC dataset (using T1w and FLAIR scans), SI=0.66±0.23, ICC=0.94 for ADNI1 dataset (using T1w, T2w, and PD scans) and SI=0.72±0.19, ICC=0.96 for ADNI2/GO dataset (using T1w and FLAIR scans). Not using the T2w/PD information did not change the performance of the Random Forest classifier (SI=0.66±0.17, ICC=0.99). However, not using FLAIR information in the ADC dataset significantly decreased the Dice Kappa, but the volumetric correlation did not drastically change (SI=0.47±0.21, ICC=0.95). Conclusion Our investigations showed that with appropriate features, most off-the-shelf classifiers are able to accurately detect WMHs in presence of FLAIR scan information, while Random Forests had the best performance across all datasets. However, we observed that the performances of most linear classifiers and some nonlinear classifiers drastically decline in absence of FLAIR information, with Random Forest still retaining the best performance.

Objective:To identify gadolinium-enhancing lesions affecting the cortex of patients with early multiple sclerosis (MS) and to describe the frequency and evolution of these lesions.Methods:We performed a retrospective, observational, longitudinal analysis of MRI scans collected as part of the Betaseron vs Copaxone in Multiple Sclerosis with Triple-Dose Gadolinium and 3T MRI Endpoints (BECOME) study. Seventy-five patients with early-stage MS were scanned monthly, over a period of 12–24 months, using 3T MRI after administration of triple-dose gadolinium. A total of 1,188 scans were included in the analysis. A total of 139 were selected using an image pipeline algorithm that integrated the image information from cortical gray matter masks and gadolinium-enhancing lesion masks. These scans were evaluated to identify gadolinium-enhancing lesions affecting the cortex.Results:The total number of gadolinium-enhancing lesions was 2,044. The number of gadolinium-enhancing lesions affecting the cortex was 120 (6%), 95% of which were leukocortical. The number of patients who showed gadolinium-enhancing lesions affecting the cortex was 27 (36%). The number of gadolinium-enhancing lesions affecting the cortex at baseline was 25 (21%) and the number of new lesions that developed in follow-up scans was 49 (41%). The number of persistent lesions was 46 (38%).Conclusions:The presence of enhancing lesions affecting the cortex and adjacent white matter, although transient and not frequent, suggests that at least some cortical lesions are related to blood–brain barrier disruption. Our data support the concept that there may be an acute inflammatory phase in the development of leukocortical MS lesions.Clinicaltrials.gov identifier:NCT00176592.

Objectives1) To automatically segment focal white matter lesions (FWML) and Diffusely abnormal white matter (DAWM), i.e. regions of diffuse abnormality observed on conventional (T2-weighted) MRI and characterize their longitudinal volumetric and normalized T1-weighted (T1w) intensity evolution, 2) To assess associations of FWML and DAWM with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP).MethodsData includes 3951 timepoints of 589 SPMS participants followed for three years. FWML and DAWM were automatically segmented using a 2-weighted-intensity thresholding technique. Screening DAWM volumes that transformed into FWML at the last visit (DAWM-to-FWML) and normalized T1w intensities (as a marker of severity of damage) in those voxels were calculated.ResultsFWML volume significantly increased and DAWM volume significantly decreased as disease duration increased (pConclusionDAWM transformed into FWML over time, and this transformation was significantly associated with clinical progression. DAWM voxels that transformed had greater normalized T1w intensity decrease over time, in keeping with relatively greater tissue damage evolution. Evaluation of DAWM in progressive MS provides a useful measure to evaluate therapies that aim to protect this at-risk tissue with the potential to slow progression.

International audience; Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

Background: Studies including patients with well-established multiple sclerosis (MS) have shown a significant and disability-related reduction in the cervical spinal cord (SC) magnetisation transfer ratio (MTR). Objectives: The objectives are to (1) assess whether MTR reduction is already measurable in the SC of patients with early relapsing–remitting multiple sclerosis (RRMS) and (2) describe its spatial distribution. Methods: We included 60 patients with RRMS Results: Mean whole SC MTR was significantly lower in patients than controls (33.7 vs 34.9 pu, p = 0.00005), even after excluding lesions (33.9 pu, p = 0.0003). We observed a greater mean reduction in MTR for vertebral levels displaying the highest lesion loads (C2–C4). In the axial plane, we observed a greater mean MTR reduction at the SC periphery and barycentre. Conclusion: Cervical SC tissue damage measured using MTR is not restricted to macroscopic lesions in patients with early RRMS and is not homogeneously distributed.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. The goal of this study was to develop a fully-automatic framework, robust to variability in both image parameters and clinical condition, for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data. Scans of 1,042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n=30). Data spanned three contrasts (T1-, T2-, and T2*-weighted) for a total of 1,943 volumes. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg, a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. The proposed framework is open-source and readily available in the Spinal Cord Toolbox., Comment: 38 pages, 7 figures, 2 tables

The purpose of our study was to evaluate the utility of measurements of cortical surface magnetization transfer ratio (csMTR) on the inner, mid and outer cortical boundaries as clinically accessible biomarkers of cortical gray matter pathology in multiple sclerosis (MS). Twenty-five MS patients and 12 matched controls were recruited from the MS Clinic of the Montreal Neurological Institute. Anatomical and magnetization transfer ratio (MTR) images were acquired using 3 Tesla MRI at baseline and two-year time-points. MTR maps were smoothed along meshes representing the inner, mid and outer neocortical boundaries. To evaluate csMTR reductions suggestive of sub-pial demyelination in MS patients, a mixed model analysis was carried out at both the individual vertex level and in anatomically parcellated brain regions. Our results demonstrate that focal areas of csMTR reduction are most prevalent along the outer cortical surface in the superior temporal and posterior cingulate cortices, as well as in the cuneus and precentral gyrus. Additionally, age regression analysis identified that reductions of csMTR in MS patients increase with age but appear to hit a plateau in the outer caudal anterior cingulate, as well as in the precentral and postcentral cortex. After correction for the naturally occurring gradient in cortical MTR, the difference in csMTR between the inner and outer cortex in focal areas in the brains of MS patients correlated with clinical disability. Overall, our findings support multi-surface analysis of csMTR as a sensitive marker of cortical sub-pial abnormality indicative of demyelination in MS patients., Highlights • Novel cortical MTR analysis identifies areas of sub-pial abnormality in MS patients. • A greater area of sub-pial abnormality in MS exists on the outer cortical layer. • Cortical regions most affected were involved in executive function and processing speed. • Normalized differences between outer and inner cortex MTR correlate with EDSS in MS. • This technique can be applied for clinical trials at the MRI field strength of 3 T.

Background MRI-histology correlation studies of the ex vivo brain mostly employ fresh, extracted (ex situ) specimens, aldehyde fixed by immersion, which has several disadvantages for MRI scanning (e.g. deformation of the organ). A minority of studies are done ex vivo-in situ (unfixed brain), requiring an MRI scanner readily available within a few hours of the time of death. New Method We propose a new technique, exploited by anatomists, for scanning the ex vivo brain: fixation by whole body perfusion, which implies fixation of the brain in situ. This allows scanning the brain surrounded by fluids, meninges, and skull, preserving the structural relationships of the brain in vivo. To evaluate the proposed method, five heads perfused-fixed with a saturated sodium chloride solution were employed. Three sequences were acquired on a 1.5 T MRI scanner: T1weighted, T2weighted-FLAIR, and Gradient-echo. Histology analysis included immunofluorescence for myelin basic protein and neuronal nuclei. Results All MRIs were successfully processed through a validated pipeline used with in vivo MRIs. All cases exhibited positive antigenicity for myelin and neuronal nuclei. Comparison with existing methods All scans registered to a standard neuroanatomical template in pseudo-Talairach space more accurately than an ex vivo-ex situ scan. The time interval to scan the ex vivo brain in situ was increased to at least 10 months. Conclusions MRI and histology study of the ex vivo-in situ brain fixed by perfusion is an alternative approach that has important procedural and practical advantages over the two standard methods to study the ex vivo brain.

Background Brain volume loss measured from magnetic resonance imaging (MRI) is a marker of neurodegeneration and predictor of disability progression in MS, and is commonly used to assess drug efficacy at the group level in clinical trials. Whether measures of brain volume loss could be useful to help guide management of individual patients depends on the relative magnitude of the changes over a given interval to physiological and technical sources of variability. Goal To understand the relative contributions of neurodegeneration vs. physiological and technical sources of variability to measurements of brain volume loss in individuals. Material and methods Multiple T1-weighted 3D MPRAGE images were acquired from a healthy volunteer and MS patient over varying time intervals: 7 times on the first day (before breakfast at 7:30AM and then every 2 ​h for 12 ​h), each day for the next 6 working days, and 6 times over the remainder of the year, on 2 ​Siemens MRI scanners: 1.5T Sonata (S1) and 3.0T TIM Trio (S2). Scan-reposition-rescan data were acquired on S2 for daily, monthly and 1-year visits. Percent brain volume change (PBVC) was measured from baseline to each follow-up scan using FSL/SIENA. We estimated the effect of physiologic fluctuations on brain volume using linear regression of the PBVC values over hourly and daily intervals. The magnitude of the physiological effect was estimated by comparing the root-mean-square error (RMSE) of the regression of all the data points relative to the regression line, for the hourly scans vs the daily scans. Variance due to technical sources was assessed as the RMSE of the regression over time using the intracranial volume as a reference. Results The RMSE of PBVC over 12 ​h, for both scanners combined, (“Hours”, 0.15%), was similar to the day-to-day variation over 1 week (“Days”, 0.14%), and both were smaller than the RMS error over the year (0.21%). All of these variations, however, were smaller than the scan-reposition-rescan RMSE (0.32%). The variability of PBVC for the individual scanners followed the same trend. The standard error of the mean (SEM) for PBVC was 0.26 for S1, and 0.22 for S2. From these values, we computed the minimum detectable change (MDC) to be 0.7% on S1 and 0.6% on S2. The location of the brain along the z-axis of the magnet inversely correlated with brain volume change for hourly and daily brain volume fluctuations (p ​ Conclusion Consistent diurnal brain volume fluctuations attributable to physiological shifts were not detectable in this small study. Technical sources of variation dominate measured changes in brain volume in individuals until the volume loss exceeds around 0.6–0.7%. Reliable interpretation of measured brain volume changes as pathological (greater than normal aging) in individuals over 1 year requires changes in excess of about 1.1% (depending on the scanner). Reliable brain atrophy detection in an individual may be feasible if the rate of brain volume loss is large, or if the measurement interval is sufficiently long.

White matter hyperintensities (WMHs) are common in individuals with mild cognitive impairment (MCI) and Alzheimer's disease. Patients with MCI with high WMH volumes are known to have an increased chance of conversion to Alzheimer's disease compared with those without WMHs. In this article, we assess the differences between patients with MCI that remain stable (N = 413) and those that progress to dementia (N = 178) in terms of WMH volume (as a surrogate of amount of tissue damage) and T1-weighted (T1w) image hypointensity (as a surrogate of severity of tissue damage) in periventricular, deep, and juxtacortical brain regions. Together, lesion volume and T1w hypointensity are used as a surrogate of vascular disease burden. Our results show a significantly greater increase of all regional WMH volumes in the MCI population that converts to dementia (p 0.001). T1w hypointensity for the juxtacortical WMHs was significantly lower in the converter group (p 0.0001) and was not affected by age. Conversely, T1w hypointensity in other regions showed a significant decrease with age (p0.0001). Within the converters, Time2Conversion was associated with both WMH volume and T1w hypointensity (p0.0001), and conversion to dementia was significantly associated with decreased intensity (and not volume) of periventricular and juxtacortical WMHs (p0.001). These changes differ according to the WM region, suggesting that different mechanisms affect the juxtacortical area in comparison to deep and periventricular regions in the process of conversion to dementia.

ObjectiveWhite Matter Hyperintensities (WMHs) are associated with cognitive decline in normative aging and Alzheimer’s disease. However, the pathogenesis of cognitive decline in Parkinson’s disease (PD) is not directly related to vascular causes, and therefore the role of WMHs in PD remains unclear. If WMH has a higher impact on cognitive decline in PD, vascular pathology should be assessed and treated with a higher priority in this population. Here we investigate whether WMH leads to increased cognitive decline in PD, and if these effects relate to cortical thinningMethodsTo investigate the role of WMHs in PD, it is essential to study recently-diagnosed/non-treated patients.De novoPD patients and age-matched controls (NPD=365,NControl=174) with FLAIR/T2-weighted scans at baseline were selected from Parkinson’s Progression Markers Initiative (PPMI). WMHs and cortical thickness were measured to analyse the relationship between baseline WMHs and future cognitive decline (follow-up:4.09±1.14 years) and cortical thinning (follow-up:1.05±0.10 years).ResultsHigh WMH load (WMHL) at baseline in PD was associated with increased cognitive decline, significantly more than i) PDs with low WMHL and ii) controls with high WMHL. Furthermore, PD patients with higher baseline WMHL showed more cortical thinning in right frontal lobe than subjects with low WMHL. Cortical thinning of this region also predicted decline in performance on a cognitive test.InterpretationPresence of WMHs inde novoPD patients predicts greater future cognitive decline and cortical thinning than in normal aging. Recognizing WMHs as a potential predictor of cognitive deficit in PD provides an opportunity for timely interventions.

BACKGROUND AND PURPOSE: Double inversion recovery has been suggested as the MR imaging contrast of choice for segmenting cortical lesions in patients with multiple sclerosis. In this study, we sought to determine the utility of double inversion recovery for cortical lesion identification by comparing 3 MR imaging reading protocols that combine different MR imaging contrasts. MATERIALS AND METHODS: Twenty-five patients with relapsing-remitting MS and 3 with secondary-progressive MS were imaged with 3T MR imaging by using double inversion recovery, dual fast spin-echo proton-density/T2-weighted, 3D FLAIR, and 3D T1-weighted imaging sequences. Lesions affecting the cortex were manually segmented by using the following 3 MR imaging reading protocols: Protocol 1 (P1) used all available MR imaging contrasts; protocol 2 (P2) used all the available contrasts except for double inversion recovery; and protocol 3(P3) used only double inversion recovery. RESULTS: Six hundred forty-three cortical lesions were identified with P1 (mean = 22.96); 633, with P2 (mean = 22.6); and 280, with P3 (mean = 10). The counts obtained by using P1 and P2 were not significantly different (P = .93). The counts obtained by using P3 were significantly smaller than those obtained by using either P1 (P < .001) or P2 (P < .001). The intraclass correlation coefficients were P1 versus P2 = 0.989, P1 versus P3 = 0.615, and P2 versus P3 = 0.588. CONCLUSIONS: MR imaging cortical lesion segmentation can be performed by using 3D T1-weighted and 3D FLAIR images acquired with a 1-mm isotropic voxel size, supported by conventional T2-weighted and proton-density images with 3-mm-thick sections. Inclusion of double inversion recovery in this multimodal reading protocol did not significantly improve the cortical lesion identification rate. A multimodal approach is superior to using double inversion recovery alone.

Several methods exist and are frequently used to quantify grey matter (GM) atrophy in multiple sclerosis (MS). Fundamental to all available techniques is the accurate segmentation of GM in the brain, a difficult task confounded even further by the pathology present in the brains of MS patients. In this paper, we examine the segmentations of six different automated techniques and compare them to a manually defined reference standard. Results demonstrate that, although the algorithms perform similarly to manual segmentations of cortical GM, severe shortcomings are present in the segmentation of deep GM structures. This deficiency is particularly relevant given the current interest in the role of GM in MS and the numerous reports of atrophy in deep GM structures.