Probabilistic Atlas Research Articles

Atlas-Based Evaluation of Hemodynamic in Ascending Thoracic Aortic Aneurysms

Atlas-based analyses of patients with cardiovascular diseases have recently been explored to understand the mechanistic link between shape and pathophysiology. The construction of probabilistic atlases is based on statistical shape modeling (SSM) to assess key anatomic features for a given patient population. Such an approach is relevant to study the complex nature of the ascending thoracic aortic aneurysm (ATAA) as characterized by different patterns of aortic shapes and valve phenotypes. This study was carried out to develop an SSM of the dilated aorta with both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV), and then assess the computational hemodynamic of virtual models obtained by the deformation of the mean template for specific shape boundaries (i.e., ±1.5 standard deviation, σ). Simulations demonstrated remarkable changes in the velocity streamlines, blood pressure, and fluid shear stress with the principal shape modes such as the aortic size (Mode 1), vessel tortuosity (Mode 2), and aortic valve morphologies (Mode 3). The atlas-based disease assessment can represent a powerful tool to reveal important insights on ATAA-derived hemodynamic, especially for aneurysms which are considered to have borderline anatomies, and thus challenging decision-making. The utilization of SSMs for creating probabilistic patient cohorts can facilitate the understanding of the heterogenous nature of the dilated ascending aorta.

Microstructural alterations of the locus coeruleus-entorhinal cortex pathway in Alzheimer's disease and behavioral variant frontotemporal dementia.

Locus coeruleus (LC) neurodegeneration has been documented in Alzheimer's disease (AD) and frontotemporal dementia (FTD). In AD, the LC may be the earliest site of tau pathology, which subsequently spreads to the entorhinal cortex (EC) through axonal pathways; in FTD, pathology might follow the opposite pattern, spreading from the frontal/temporal areas to the LC. In this study, we investigated in vivo the integrity of the LC-EC pathway in AD and FTD and explored its association with cognition and neurodegeneration. Twenty-one AD, 20 behavioral variant FTD (bvFTD), and 20 age-matched healthy controls (HC) underwent 3T MRI and neuropsychological exam assessing multiple cognitive domains. Fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AxD, RD) maps were calculated from diffusion weighted images using the FMRIB's Diffusion Toolbox (FSL). Microstructural integrity of the LC-EC pathway was assessed using a probabilistic atlas on diffusivity maps warped to MNI space with FSL TBSS tool. Group differences in diffusivity measures were assessed using the Kruskal-Wallis test. Associations between diffusivity changes, cognition, and neurodegeneration (hippocampal and amygdala volumes, EC and temporal/frontal/parietal/occipital lobes cortex thickness) were assessed using Spearman's rank correlation. All analyses were corrected for multiple comparisons. Compared to HC, bvFTD showed higher MD, AxD and RD in the left and right LC-EC (p<0.010 for all) and lower FA in the right LC-EC (p=0.023), while AD showed higher RD in the left LC-EC (p=0.012). Compared to AD, bvFTD showed lower FA, higher MD and RD (p<0.033 for all) in the right LC-EC. Right MD and AxD were negatively associated with right EC thickness (p<0.004) in bvFTD. No association emerged between volumetric/thickness measures and microstructural changes in AD (p>0.050). No significant association emerged with cognitive measures in AD nor bvFTD (p>0.050). Our study suggests that the LC-EC pathway is impaired in both bvFTD and AD, and that this damage is more prominent in bvFTD. Microstructural alterations in bvFTD might reflect axonal damage and demyelination secondary to medial temporal neurodegeneration. The less pronounced effect in AD together with the lack of associations with neurodegeneration suggest that LC-EC microstructural damage may be a late event in the disease cascade.

Medical Image Segmentation With Deep Atlas Prior.

Organ segmentation from medical images is one of the most important pre-processing steps in computer-aided diagnosis, but it is a challenging task because of limited annotated data, low-contrast and non-homogenous textures. Compared with natural images, organs in the medical images have obvious anatomical prior knowledge (e.g., organ shape and position), which can be used to improve the segmentation accuracy. In this paper, we propose a novel segmentation framework which integrates the medical image anatomical prior through loss into the deep learning models. The proposed prior loss function is based on probabilistic atlas, which is called as deep atlas prior (DAP). It includes prior location and shape information of organs, which are important prior information for accurate organ segmentation. Further, we combine the proposed deep atlas prior loss with the conventional likelihood losses such as Dice loss and focal loss into an adaptive Bayesian loss in a Bayesian framework, which consists of a prior and a likelihood. The adaptive Bayesian loss dynamically adjusts the ratio of the DAP loss and the likelihood loss in the training epoch for better learning. The proposed loss function is universal and can be combined with a wide variety of existing deep segmentation models to further enhance their performance. We verify the significance of our proposed framework with some state-of-the-art models, including fully-supervised and semi-supervised segmentation models on a public dataset (ISBI LiTS 2017 Challenge) for liver segmentation and a private dataset for spleen segmentation.

Factors influencing atrophy progression in primary progressive aphasia

AbstractBackgroundPrimary progressive aphasia (PPA) is a rare primarily language‐related neurodegenerative disorder that subdivides into the non‐fluent (nfvPPA) and the semantic variant (svPPA). Atrophy progression shows variant‐specific patterns, however, its extent seems highly individual and thus difficult to predict.MethodWe investigated volumetric changes in patients with nfvPPA (n=18) and svPPA (n=15) with an MRI scan (3D T1 MPRAGE sequence, 3T) at baseline and 2‐years follow‐up that were recruited from the prospective German FTLD‐consortium study. According to the LONI Probabilistic Brain Atlas (Shattuck et al., 2009), 56 brain regions were assessed with automated atlas‐based volumetry (Huppertz et al., 2010). Longitudinal volumetric changes were analyzed by means of the R software (www.r‐project.org). A possible impact of group, adjusted for age and sex, had been investigated using a linear mixed effect model. Atrophy progression for each region over two years was correlated (Pearson or Kendall rank correlation; 95% BCa bootstrap CI with 1000 replicates) with age at symptom onset, years of education, and disease duration to review a possible relation.ResultVolume change within 2‐years revealed parts of the left frontal lobe (up to ‐10%) and subcortical regions in nfvPPA and parts of the left temporal lobe (up to ‐15%) and the hippocampus/amygdala complex in svPPA as most progressive.A correlation analysis with age at symptom onset rendered no relevant results. Higher educated patients showed more atrophy in the right parahippocampal gyrus in nfvPPA and less atrophy in white matter portions of the left superior frontal, the bilateral middle and inferior frontal, the right middle and bilateral lateral orbitofrontal and the bilateral cingulate gyrus in svPPA. Shorter disease duration correlated with higher atrophy in the caudate and putamen in nfvPPA, and in the left middle and inferior temporal gyrus, the right superior and bilateral middle occipital gyrus, the left cuneus, and left angular gyrus in svPPA.ConclusionAge at symptom onset showed no interrelation with atrophy progression in PPA. Higher education levels seem to slow white matter decrease of frontal areas in svPPA. Shorter disease duration is related to increased volume loss in some primarily affected regions in both nfvPPA and svPPA.

Mapping covariance in brain FDG uptake to structural connectivity

PurposeInter-subject covariance of regional 18F-fluorodeoxyglucose (FDG) PET measures (FDGcov) as proxy of brain connectivity has been gaining an increasing acceptance in the community. Yet, it is still unclear to what extent FDGcov is underlied by actual structural connectivity via white matter fiber tracts. In this study, we quantified the degree of spatial overlap between FDGcov and structural connectivity networks.MethodsWe retrospectively analyzed neuroimaging data from 303 subjects, both patients with suspected neurodegenerative disorders and healthy individuals. For each subject, structural magnetic resonance, diffusion tensor imaging, and FDG-PET data were available. The images were spatially normalized to a standard space and segmented into 62 anatomical regions using a probabilistic atlas. Sparse inverse covariance estimation was employed to estimate FDGcov. Structural connectivity was measured by streamline tractography through fiber assignment by continuous tracking.ResultsFor the whole brain, 55% of detected connections were found to be convergent, i.e., present in both FDGcov and structural networks. This metric for random networks was significantly lower, i.e., 12%. Convergent were 80% of intralobe connections and only 30% of interhemispheric interlobe connections.ConclusionStructural connectivity via white matter fiber tracts is a relevant substrate of FDGcov, underlying around a half of connections at the whole brain level. Short-range white matter tracts appear to be a major substrate of intralobe FDGcov connections.

Assessing the general utility of a probabilistic atlas for independent delineation of early visual areas

Assessing the general utility of a probabilistic atlas for independent delineation of early visual areas

An Age-Specific Atlas for Delineation of White Matter Pathways in Children Aged 6-8 Years.

IntroductionDiffusion MRI allows non-invasive assessment of white matter connectivity in typical development and of changes due to brain injury or pathology. Probabilistic white matter atlases allow diffusion metrics to be measured in specific white matter pathways, and are a critical component in spatial normalisation for group analysis. However, given the known developmental changes in white matter it may be sub-optimal to use an adult template when assessing data acquired from children.MethodsBy averaging subject-specific fibre bundles from 28 children aged from 6 to 8 years, we created an age-specific probabilistic white matter atlas for 12 major white matter tracts. Using both the newly developed and Johns Hopkins adult atlases, we compared the atlas to subject-specific fibre bundles in two independent validation cohorts, assessing accuracy in terms of volumetric overlap and measured diffusion metrics.ResultsOur age-specific atlas gave better overall performance than the adult atlas, achieving higher volumetric overlap with subject-specific fibre tracking and higher correlation of FA measurements with those measured from subject-specific fibre bundles. Specifically, estimates of FA values for cortico-spinal tract, uncinate fasciculus, forceps minor, cingulate gyrus part of the cingulum and anterior thalamic radiation were all significantly more accurate when estimated with an age-specific atlas.DiscussionThe age-specific atlas allows delineation of white matter tracts in children aged 6-8 years, without the need for tractography, more accurately than when normalising to an adult atlas. To our knowledge, this is the first publicly available probabilistic atlas of white matter tracts for this age group.

White Matter Abnormalities in Traumatic Subarachnoid Hemorrhage: A Tract-Based Spatial Statistics Study.

BackgroundThe pathophysiology of traumatic subarachnoid hemorrhage and brain injury has not been fully elucidated. In this study, we examined abnormalities of white matter in isolated traumatic subarachnoid hemorrhage patients by applying tract-based spatial statistics.Material/MethodsFor this study, 10 isolated traumatic subarachnoid hemorrhage patients and 10 age- and sex-matched healthy control subjects were recruited. Fractional anisotropy data voxel-wise statistical analyses were conducted through the tract-based spatial statistics as implemented in the FMRIB Software Library. Depending on the intersection between the fractional anisotropy skeleton and the probabilistic white matter atlases of Johns Hopkins University, we calculated mean fractional anisotropy values within the entire tract skeleton and 48 regions of interest.ResultsThe fractional anisotropy values for 19 of 48 regions of interest showed significant divergences (P<0.05) between the patient group and control group. The regions showing significant differences included the corpus callosum and its adjacent neural structures, the brainstem and its adjacent neural structures, and the subcortical white matter that passes the long neural tract.ConclusionsThe results demonstrated abnormalities of white matter in traumatic subarachnoid hemorrhage patients, and the abnormality locations are compatible with areas that are vulnerable to diffuse axonal injury. Based on these results, traumatic subarachnoid hemorrhage patients also exhibit diffuse axonal injuries; thus, traumatic subarachnoid hemorrhage could be an indicator of the presence of severe brain injuries associated with acute or excessive mechanical forces.

Probabilistic Atlas of the Mesencephalic Reticular Formation, Isthmic Reticular Formation, Microcellular Tegmental Nucleus, Ventral Tegmental Area Nucleus Complex, and Caudal-Rostral Linear Raphe Nucleus Complex in Living Humans from 7 Tesla Magnetic Resonance Imaging.

Introduction: The mesencephalic reticular formation, isthmic reticular formation, microcellular tegmental nucleus, ventral tegmental area-parabrachial pigmented nucleus complex, and caudal-rostral linear nucleus of the raphe are small brainstem regions crucially involved in arousal, sleep, and reward. Yet, these nuclei are difficult to identify with magnetic resonance imaging (MRI) of living humans. In the current work, we developed a probabilistic atlas of these brainstem nuclei in living humans, using noninvasive ultra-high-field MRI. Methods: We acquired single-subject, multicontrast (diffusion and T2-weighted), 1.1-mm isotropic resolution, 7 Tesla MRI images of 12 healthy subjects. After preprocessing and alignment to the stereotactic space, these images were used to delineate (in each subject) the nuclei of interest based on the image contrast as well as on neighboring nuclei and landmarks. Nucleus labels were averaged across subjects to yield probabilistic labels. The latter were further validated by assessment of the label inter-rater agreement, internal consistency, and volume. Results: Labels were delineated for each nucleus with good overlap across subjects. The inter-rater agreement and internal consistency were below (p < 10-8) the linear spatial imaging resolution (1.1 mm), thus validating the generated probabilistic atlas labels. The volumes of our labels did not differ from literature volumes (p < 0.05), further validating our atlas. Discussion and Conclusion: The probabilistic atlas of these five mesopontine nuclei expands current in vivo brainstem nuclei atlases and can be used as a tool to identify the location of these areas in conventional (e.g., 3 Tesla) images. This might serve to unravel the brainstem structure-to-function link and thus improve clinical outcomes. Impact statement The mesencephalic reticular formation, isthmic reticular formation, microcellular tegmental nucleus, ventral tegmental area-parabrachial pigmented nucleus complex, and caudal-rostral linear nucleus of the raphe are small brainstem regions crucially involved in arousal, sleep, and reward. In the current work, we developed a probabilistic atlas of these brainstem nuclei in living humans, using noninvasive, ultra-high-field magnetic resonance imaging. The probabilistic atlas of these five mesopontine nuclei expands current in vivo brainstem nuclei atlases and can be used as a tool to identify the location of these areas in conventional (e.g., 3 Tesla) images. This might serve to unravel the brainstem structure-to-function link and thus improve clinical outcomes.

Commentary: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept

Commentary: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept

Commentary: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept.

Commentary: Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept.

Planning Brain Tumor Resection Using a Probabilistic Atlas of Cortical and Subcortical Structures Critical for Functional Processing: A Proof of Concept.

Functional preoperative planning for resection of intrinsic brain tumors in eloquent areas is still a challenge. Predicting subcortical functional framework is especially difficult. Direct electrical stimulation (DES) is the recommended technique for resection of these lesions. A reliable probabilistic atlas of the critical cortical epicenters and subcortical framework based on DES data was recently published. To propose a pipeline for the automated alignment of the corticosubcortical maps of this atlas with T1-weighted MRI. To test the alignment, we selected 10 patients who underwent resection of brain lesions by using DES. We aligned different cortical and subcortical functional maps to preoperative volumetric T1 MRIs (with/without gadolinium). For each patient we quantified the quality of the alignment, and we calculated the match between the location of the functional sites found at DES and the functional maps of the atlas. We found an accurate brain extraction and alignment of the functional maps with both the T1 MRIs of each patient. The matching analysis between functional maps and functional responses collected during surgeries was 88% at cortical and, importantly, 100% at subcortical level, providing a further proof of the correct alignment. We demonstrated quantitatively and qualitatively the reliability of this tool that may be used for presurgical planning, providing further functional information at the cortical level and a unique probabilistic prevision of distribution of the critical subcortical structures. Finally, this tool offers the chance for multimodal planning through integrating this functional information with other neuroradiological and neurophysiological techniques.

Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network.

Brain atlases are of fundamental importance for analyzing the dynamic neurodevelopment in fetal brain studies. Since the brain size, shape, and anatomical structures change rapidly during the prenatal period, it is essential to construct a spatiotemporal (4D) atlas equipped with tissue probability maps, which can preserve sharper early brain folding patterns for accurately characterizing dynamic changes in fetal brains and provide tissue prior informations for related tasks, e.g., segmentation, registration, and parcellation. In this work, we propose a novel unsupervised age-conditional learning framework to build temporally continuous fetal brain atlases by incorporating tissue segmentation maps, which outperforms previous traditional atlas construction methods in three aspects. First, our framework enables learning age-conditional deformable templates by leveraging the entire collection. Second, we leverage reliable brain tissue segmentation maps in addition to the low-contrast noisy intensity images to enhance the alignment of individual images. Third, a novel loss function is designed to enforce the similarity between the learned tissue probability map on the atlas and each subject tissue segmentation map after registration, thereby providing extra anatomical consistency supervision for atlas building. Our 4D temporally-continuous fetal brain atlases are constructed based on 82 healthy fetuses from 22 to 32 gestational weeks. Compared with the atlases built by the state-of-the-art algorithms, our atlases preserve more structural details and sharper folding patterns. Together with the learned tissue probability maps, our 4D fetal atlases provide a valuable reference for spatial normalization and analysis of fetal brain development.

Mapping the Human Brain: What Is the Next Frontier?

Abstract The structure and function of the human brain have long been the topic of exploration by scientists. To understand how the brain works, researchers have created various brain navigation maps, i.e. brain atlases, which are still being developed and improved. To clarify the trend of human brain mapping and to achieve better applications in brain science and diseases, this commentary briefly traces the history of human brain mapping and describes insights into the next stage of building brain atlases.

Endovascular deep brain stimulation: Investigating the relationship between vascular structures and deep brain stimulation targets

BackgroundEndovascular delivery of current using ‘stentrodes’ – electrode bearing stents – constitutes a potential alternative to conventional deep brain stimulation (DBS). The precise neuroanatomical relationships between DBS targets and the vascular system, however, are poorly characterized to date. ObjectiveTo establish the relationships between cerebrovascular system and DBS targets and investigate the feasibility of endovascular stimulation as an alternative to DBS. MethodsNeuroanatomical targets as employed during deep brain stimulation (anterior limb of the internal capsule, dentatorubrothalamic tract, fornix, globus pallidus pars interna, medial forebrain bundle, nucleus accumbens, pedunculopontine nucleus, subcallosal cingulate cortex, subthalamic nucleus, and ventral intermediate nucleus) were superimposed onto probabilistic vascular atlases obtained from 42 healthy individuals. Euclidian distances between targets and associated vessels were measured. To determine the electrical currents necessary to encapsulate the predefined neurosurgical targets and identify potentially side-effect inducing substrates, a preliminary volume of tissue activated (VTA) analysis was performed. ResultsSix out of ten DBS targets were deemed suitable for endovascular stimulation: medial forebrain bundle (vascular site: P1 segment of posterior cerebral artery), nucleus accumbens (vascular site: A1 segment of anterior cerebral artery), dentatorubrothalamic tract (vascular site: s2 segment of superior cerebellar artery), fornix (vascular site: internal cerebral vein), pedunculopontine nucleus (vascular site: lateral mesencephalic vein), and subcallosal cingulate cortex (vascular site: A2 segment of anterior cerebral artery). While VTAs effectively encapsulated mfb and NA at current thresholds of 3.5 V and 4.5 V respectively, incremental amplitude increases were required to effectively cover fornix, PPN and SCC target (mean voltage: 8.2 ± 4.8 V, range: 3.0–17.0 V). The side-effect profile associated with endovascular stimulation seems to be comparable to conventional lead implantation. Tailoring of targets towards vascular sites, however, may allow to reduce adverse effects, while maintaining the efficacy of neural entrainment within the target tissue. ConclusionsWhile several challenges remain at present, endovascular stimulation of select DBS targets seems feasible offering novel and exciting opportunities in the neuromodulation armamentarium.

A comparison of Freesurfer and multi-atlas MUSE for brain anatomy segmentation: Findings about size and age bias, and inter-scanner stability in multi-site aging studies

Automatic segmentation of brain anatomy has been a key processing step in quantitative neuroimaging analyses. An extensive body of literature has relied on Freesurfer segmentations. Yet, in recent years, the multi-atlas segmentation framework has consistently obtained results with superior accuracy in various evaluations. We compared brain anatomy segmentations from Freesurfer, which uses a single probabilistic atlas strategy, against segmentations from Multi-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters and locally optimal atlas selection (MUSE), one of the leading ensemble-based methods that calculates a consensus segmentation through fusion of anatomical labels from multiple atlases and registrations. The focus of our evaluation was twofold. First, using manual ground-truth hippocampus segmentations, we found that Freesurfer segmentations showed a bias towards over-segmentation of larger hippocampi, and under-segmentation in older age. This bias was more pronounced in Freesurfer-v5.3, which has been used in multiple previous studies of aging, while the effect was mitigated in more recent Freesurfer-v6.0, albeit still present. Second, we evaluated inter-scanner segmentation stability using same day scan pairs from ADNI acquired on 1.5T and 3T scanners. We also found that MUSE obtains more consistent segmentations across scanners compared to Freesurfer, particularly in the deep structures.

White Matter Abnormalities in Spontaneous Subarachnoid Hemorrhage: A Tract-Based Spatial Statistics Study.

We investigated white matter abnormalities in patients with spontaneous subarachnoid hemorrhage following aneurysmal rupture, by using tract-based spatial statistics. Sixteen patients with spontaneous subarachnoid hemorrhage due to aneurysmal rupture and 18 age- and sex-matched healthy control subjects were recruited. Voxel-wise statistical analysis of fractional anisotropy data was performed by using tract-based spatial statistics as implemented in the Functional Magnetic Resonance Imaging of the Brain Software Library. We calculated mean fractional anisotropy values across the tract skeleton and within 48 regions of interest based on the intersections between the fractional anisotropy skeleton and the probabilistic Johns Hopkins University white matter atlases. Comparing the patient and control groups, the fractional anisotropy values of 44 regions of interest among the 48 regions of interest showed significant differences (P<0.05). However, significant differences were not observed in the remaining 4 regions of interest (both retrolenticular parts of the internal capsule, the right superior longitudinal fasciculus, and the right superior corona radiata; P>0.05). By undertaking tract-based spatial statistics analysis, we detected wide-ranging white matter abnormalities in patients with spontaneous subarachnoid hemorrhage. Registration: URL: http://www.e-irb.com/index.jsp. Unique identifier: 2019-06-032.

Amygdala pathology in amyotrophic lateral sclerosis and primary lateral sclerosis

Temporal lobe studies in motor neuron disease overwhelmingly focus on white matter alterations and cortical grey matter atrophy. Reports on amygdala involvement are conflicting and the amygdala is typically evaluated as single structure despite consisting of several functionally and cytologically distinct nuclei. A prospective, single-centre, neuroimaging study was undertaken to comprehensively characterise amygdala pathology in 100 genetically-stratified ALS patients, 33 patients with PLS and 117 healthy controls. The amygdala was segmented into groups of nuclei using a Bayesian parcellation algorithm based on a probabilistic atlas and shape deformations were additionally assessed by vertex analyses. The accessory basal nucleus (p = .021) and the cortical nucleus (p = .022) showed significant volume reductions in C9orf72 negative ALS patients compared to controls. The lateral nucleus (p = .043) and the cortico-amygdaloid transition (p = .024) were preferentially affected in C9orf72 hexanucleotide carriers. A trend of total volume reduction was identified in C9orf72 positive ALS patients (p = .055) which was also captured in inferior-medial shape deformations on vertex analyses. Our findings highlight that the amygdala is affected in ALS and our study demonstrates the selective involvement of specific nuclei as opposed to global atrophy. The genotype-specific patterns of amygdala involvement identified by this study are consistent with the growing literature of extra-motor clinical features. Mesial temporal lobe pathology in ALS is not limited to hippocampal pathology but, as a key hub of the limbic system, the amygdala is also affected in ALS.

Multiple sclerosis lesions in motor tracts from brain to cervical cord: spatial distribution and correlation with disability.

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 < 0.0001). Voxel-wise analyses confirmed that lesion frequency was higher in progressive compared to relapsing-remitting patients, with significant bilateral clusters in the spinal cord corticospinal tracts (P < 0.01). The baseline Expanded Disability Status Scale score was associated with lesion volume fraction within the brain (r = 0.31, P < 0.0001), brainstem (r = 0.45, P < 0.0001) and spinal cord (r = 0.57, P < 0.0001) corticospinal tracts. The spinal cord corticospinal tracts lesion volume fraction remained the strongest factor in the multiple linear regression model, independently from cord atrophy. Baseline spinal cord corticospinal tracts lesion volume fraction was also associated with disability progression at 2-year follow-up (P = 0.003). Our results suggest a cumulative effect of lesions within the corticospinal tracts along the brain, brainstem and spinal cord portions to explain physical disability in multiple sclerosis patients, with a predominant impact of intramedullary lesions.

A probabilistic atlas of finger dominance in the primary somatosensory cortex

With the advent of ultra-high field (7T), high spatial resolution functional MRI (fMRI) has allowed the differentiation of the cortical representations of each of the digits at an individual-subject level in human primary somatosensory cortex (S1). Here we generate a probabilistic atlas of the contralateral SI representations of the digits of both the left and right hand in a group of 22 right-handed individuals. The atlas is generated in both volume and surface standardised spaces from somatotopic maps obtained by delivering vibrotactile stimulation to each distal phalangeal digit using a travelling wave paradigm.Metrics quantify the likelihood of a given position being assigned to a digit (full probability map) and the most probable digit for a given spatial location (maximum probability map). The atlas is validated using a leave-one-out cross validation procedure. Anatomical variance across the somatotopic map is also assessed to investigate whether the functional variability across subjects is coupled to structural differences. This probabilistic atlas quantifies the variability in digit representations in healthy subjects, finding some quantifiable separability between digits 2, 3 and 4, a complex overlapping relationship between digits 1 and 2, and little agreement of digit 5 across subjects. The atlas and constituent subject maps are available online for use as a reference in future neuroimaging studies.