Simultaneous lesion and neuroanatomy segmentation in Multiple Sclerosis using deep neural networks

Segmentation of both white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. Typically these tasks are performed separately: in this paper we present a single segmentation solution based on convolutional neural networks (CNNs) for providing fast, reliable segmentations of multimodal magnetic resonance images into lesion classes and normal-appearing grey- and white-matter structures. We show substantial, statistically significant improvements in both Dice coefficient and in lesion-wise specificity and sensitivity, compared to previous approaches, and agreement with individual human raters in the range of human inter-rater variability. The method is trained on data gathered from a single centre: nonetheless, it performs well on data from centres, scanners and field-strengths not represented in the training dataset. A retrospective study found that the classifier successfully identified lesions missed by the human raters. Lesion labels were provided by human raters, while weak labels for other brain structures (including CSF, cortical grey matter, cortical white matter, cerebellum, amygdala, hippocampus, subcortical GM structures and choroid plexus) were provided by Freesurfer 5.3. The segmentations of these structures compared well, not only with Freesurfer 5.3, but also with FSL-First and Freesurfer 6.0

Quantitative assessment of myelin density using [C-11]MeDAS PET in patients with multiple sclerosis:a first-in-human study

Purpose: Multiple sclerosis (MS) is a disease characterized by inflammatory demyelinated lesions. New treatment strategies are being developed to stimulate myelin repair. Quantitative myelin imaging could facilitate these developments. This first-in-man study aimed to evaluate [11C]MeDAS as a PET tracer for myelin imaging in humans. Methods: Six healthy controls and 11 MS patients underwent MRI and dynamic [11C]MeDAS PET scanning with arterial sampling. Lesion detection and classification were performed on MRI. [11C]MeDAS time-activity curves of brain regions and MS lesions were fitted with various compartment models for the identification of the best model to describe [11C]MeDAS kinetics. Several simplified methods were compared to the optimal compartment model. Results: Visual analysis of the fits of [11C]MeDAS time-activity curves showed no preference for irreversible (2T3k) or reversible (2T4k) two-tissue compartment model. Both volume of distribution and binding potential estimates showed a high degree of variability. As this was not the case for 2T3k-derived net influx rate (Ki), the 2T3k model was selected as the model of choice. Simplified methods, such as SUV and MLAIR2 correlated well with 2T3k-derived Ki, but SUV showed subject-dependent bias when compared to 2T3k. Both the 2T3k model and the simplified methods were able to differentiate not only between gray and white matter, but also between lesions with different myelin densities. Conclusion: [11C]MeDAS PET can be used for quantification of myelin density in MS patients and is able to distinguish differences in myelin density within MS lesions. The 2T3k model is the optimal compartment model and MLAIR2 is the best simplified method for quantification. Trial registration. NL7262. Registered 18 September 2018

Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis

Black holes; Chronic active lesions; Volumetric MRIAgujeros negros; Lesiones activas crónicas; Resonancia magnética volumétricaForats negres; Lesions actives cròniques; Ressonància magnètica volumètricaBackground Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion’s metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p < 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p < 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI −0.005 to −0.003, p < 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed-effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95%CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). Conclusions SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity and MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS

Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis

Background: Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion's metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives: To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods: 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was &amp; LE; 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results: Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p &lt; 0.001) and within-patient SEL volumes positively correlated with PBH volumes (r = 0.53, p &lt; 0.001). SELs showed a decrease in T1 intensity over time (beta = -0.004, 95%CI -0.005 to -0.003, p &lt; 0.001), accompanied by lower cross-sectional baseline and follow-up MTR. In mixed effects models, EDSS worsening was predicted by the SEL log-volumes increase over time (beta = 0.11, 95% CI 0.03 to 0.20, p = 0.01), which was confirmed in the sub-cohort of patients with early onset MS (beta = 0.14, 95%CI 0.04 to 0.25, p = 0.008). In logistic regressions, a higher risk for CDP was associated with SEL volumes (OR = 5.15, 95%CI 1.60 to 16.60, p = 0.006). Conclusions: SELs are associated with accumulation of more destructive pathology as indicated by an association with PBH volume, longitudinal reduction in T1 intensity , MTR. Higher SEL volumes are associated with clinical progression, while lower ones are associated with stability in relapse-onset MS

Comparing MRI metrics to quantify white matter microstructural damage in multiple sclerosis

Quantifying white matter damage in vivo is becoming increasingly important for investigating the effects of neuroprotective and repair strategies in multiple sclerosis (MS). While various approaches are available, the relationship between MRI-based metrics of white matter microstructure in the disease, that is, to what extent the metrics provide complementary versus redundant information, remains largely unexplored. We obtained four microstructural metrics from 123 MS patients: fractional anisotropy (FA), radial diffusivity (RD), myelin water fraction (MWF), and magnetisation transfer ratio (MTR). Coregistration of maps of these four indices allowed quantification of microstructural damage through voxel-wise damage scores relative to healthy tissue, as assessed in a group of 27 controls. We considered three white matter tissue-states, which were expected to vary in microstructural damage: normal appearing white matter (NAWM), T2-weighted hyperintense lesional tissue without T1-weighted hypointensity (T2L), and T1-weighted hypointense lesional tissue with corresponding T2-weighted hyperintensity (T1L). All MRI indices suggested significant damage in all three tissue-states, the greatest damage being in T1L. The correlations between indices ranged from r = 0.18 to r = 0.87. MWF was most sensitive when differentiating T2L from NAWM, while MTR was most sensitive when differentiating T1L from NAWM and from T2L. Combining the four metrics into one, through a principal component analysis, did not yield a measure more sensitive to damage than any single measure. Our findings suggest that the metrics are (at least partially) correlated with each other, but sensitive to the different aspects of pathology. Leveraging these differences could be beneficial in clinical trials testing the effects of therapeutic interventions

Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting

Evolution of MS lesions to black holes under DNA vaccine treatment

Persistent black holes (PBH) are associated with axonal loss and disability progression in multiple sclerosis (MS). The objective of this work was to determine if BHT-3009, a DNA plasmid-encoding myelin basic protein (MBP), reduces the risk of new lesions becoming PBH, compared to placebo, and to test if pre-treatment serum anti-MBP antibody levels impact on the effect of BHT-3009 treatment. In this retrospective, blinded MRI study, we reviewed MRI scans of 155 MS patients from a double-blind, randomized, phase II trial with three treatment arms (placebo, 0.5 and 1.5mg BHT-3009). New lesions at weeks 8 and 16 were tracked at week 48 and those appearing as T1-hypointense were classified as PBH. A subset of 46 patients with available pre-treatment serum anti-MBP IgM levels were analyzed separately. Overall, there was no impact of treatment on the risk for PBH. However, there was a significant interaction between anti-MBP antibodies and treatment effect: patients receiving 0.5mg BHT-3009 showed a reduced risk of PBH with higher antibody levels compared to placebo (p<0.01). Although we found no overall reduction of the risk for PBH in treated patients, there may be an effect of low-dose BHT-3009, depending on the patients' pre-treatment immune response

A Fuzzy Regional-Based Approach for Detecting Cerebrospinal Fluid Regions in presence of Multiple Sclerosis Lesions

Postprint (published version

The Combined Quantification and Interpretation of Multiple Quantitative Magnetic Resonance Imaging Metrics Enlightens Longitudinal Changes Compatible with Brain Repair in Relapsing-Remitting Multiple Sclerosis Patients.

Quantitative and semi-quantitative MRI (qMRI) metrics provide complementary specificity and differential sensitivity to pathological brain changes compatible with brain inflammation, degeneration, and repair. Moreover, advanced magnetic resonance imaging (MRI) metrics with overlapping elements amplify the true tissue-related information and limit measurement noise. In this work, we combined multiple advanced MRI parameters to assess focal and diffuse brain changes over 2 years in a group of early-stage relapsing-remitting MS patients. Thirty relapsing-remitting MS patients with less than 5 years disease duration and nine healthy subjects underwent 3T MRI at baseline and after 2 years including T1, T2, T2* relaxometry, and magnetization transfer imaging. To assess longitudinal changes in normal-appearing (NA) tissue and lesions, we used analyses of variance and Bonferroni correction for multiple comparisons. Multivariate linear regression was used to assess the correlation between clinical outcome and multiparametric MRI changes in lesions and NA tissue. In patients, we measured a significant longitudinal decrease of mean T2 relaxation times in NA white matter (p = 0.005) and a decrease of T1 relaxation times in the pallidum (p &lt; 0.05), which are compatible with edema reabsorption and/or iron deposition. No longitudinal changes in qMRI metrics were observed in controls. In MS lesions, we measured a decrease in T1 relaxation time (p-value &lt; 2.2e-16) and a significant increase in MTR (p-value &lt; 1e-6), suggesting repair mechanisms, such as remyelination, increased axonal density, and/or a gliosis. Last, the evolution of advanced MRI metrics-and not changes in lesions or brain volume-were correlated to motor and cognitive tests scores evolution (Adj-R(2) &gt; 0.4, p &lt; 0.05). In summary, the combination of multiple advanced MRI provided evidence of changes compatible with focal and diffuse brain repair at early MS stages as suggested by histopathological studies