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Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.

Background: Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. Objectives: This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). Methods: A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. Results: All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. Conclusions: The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.

Background: Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. Objectives: This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). Methods: A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. Results: All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. Conclusions: The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.

See Giovannoni (doi:10.1093/brain/awy200) for a scientific commentary on this article. Biomarkers of tissue damage in multiple sclerosis are urgently needed. Barro et al. show that serum neurofilament light chain (NfL) levels are increased in patients versus healthy controls and reflect radiological and clinical disease activity and progression. High serum NfL is associated with greater subsequent brain and spinal cord atrophy.

ObjectiveTo determine the levels of brain-derived neurotrophic factor (BDNF) in the serum of patients suffering from multiple sclerosis (MS) to evaluate the potential of serum BDNF as a biomarker for MS.MethodsUsing a recently validated enzyme-linked immunoassay (ELISA) we measured BDNF in patients with MS (pwMS), diagnosed according to the 2001 McDonald criteria and aged between 18 and 70 years, participating in a long-term cohort study with annual clinical visits, including blood sampling, neuropsychological testing, and brain magnetic resonance imaging (MRI). The results were compared with an age- and sex-matched cohort of healthy controls (HC). Correlations between BDNF levels and a range of clinical and magnetic resonance imaging variables were assessed using an adjusted linear model.ResultsIn total, 259 pwMS and 259 HC were included, with a mean age of 44.42 ± 11.06 and 44.31 ± 11.26 years respectively. Eleven had a clinically isolated syndrome (CIS), 178 relapsing remitting MS (RRMS), 56 secondary progressive MS (SPMS), and 14 primary progressive MS (PPMS). Compared with controls, mean BDNF levels were lower by 8 % (p˂0.001) in pwMS. The level of BDNF in patients with SPMS was lower than in RRMS (p = 0.004).InterpretationWe conclude that while the use of comparatively large cohorts enables the detection of a significant difference in BDNF levels between pwMS and HC, the difference is small and unlikely to usefully inform decision-making processes at an individual patient level.

ObjectiveTo determine the levels of brain-derived neurotrophic factor (BDNF) in the serum of patients suffering from multiple sclerosis (MS) to evaluate the potential of serum BDNF as a biomarker for MS.MethodsUsing a recently validated enzyme-linked immunoassay (ELISA) we measured BDNF in patients with MS (pwMS), diagnosed according to the 2001 McDonald criteria and aged between 18 and 70 years, participating in a long-term cohort study with annual clinical visits, including blood sampling, neuropsychological testing, and brain magnetic resonance imaging (MRI). The results were compared with an age- and sex-matched cohort of healthy controls (HC). Correlations between BDNF levels and a range of clinical and magnetic resonance imaging variables were assessed using an adjusted linear model.ResultsIn total, 259 pwMS and 259 HC were included, with a mean age of 44.42 ± 11.06 and 44.31 ± 11.26 years respectively. Eleven had a clinically isolated syndrome (CIS), 178 relapsing remitting MS (RRMS), 56 secondary progressive MS (SPMS), and 14 primary progressive MS (PPMS). Compared with controls, mean BDNF levels were lower by 8 % (p˂0.001) in pwMS. The level of BDNF in patients with SPMS was lower than in RRMS (p = 0.004).InterpretationWe conclude that while the use of comparatively large cohorts enables the detection of a significant difference in BDNF levels between pwMS and HC, the difference is small and unlikely to usefully inform decision-making processes at an individual patient level.

OBJECTIVE Cross-sectional studies have shown that spinal cord volume (SCV) loss is related to disease severity in multiple sclerosis (MS). However, long-term data are lacking. Our aim was to evaluate SCV loss as a biomarker of disease progression in comparison to other MRI measurements in a large cohort of patients with relapse-onset MS with 6-year follow-up. METHODS The upper cervical SCV, the total brain volume, and the brain T2 lesion volume were measured annually in 231 patients with MS (180 relapsing-remitting [RRMS] and 51 secondary progressive [SPMS]) over 6 years on 3-dimensional, T1-weighted, magnetization-prepared rapid-acquisition gradient echo images. Expanded Disability Status Scale (EDSS) score and relapses were recorded at every follow-up. RESULTS Patients with SPMS had lower baseline SCV ( < 0.01) but no accelerated SCV loss compared to those with RRMS. Clinical relapses were found to predict SCV loss over time ( < 0.05) in RRMS. Furthermore, SCV loss, but not total brain volume and T2 lesion volume, was a strong predictor of EDSS score worsening over time ( < 0.05). The mean annual rate of SCV loss was the strongest MRI predictor for the mean annual EDSS score change of both RRMS and SPMS separately, while correlating stronger in SPMS. Every 1% increase of the annual SCV loss rate was associated with an extra 28% risk increase of disease progression in the following year in both groups. CONCLUSION SCV loss over time relates to the number of clinical relapses in RRMS, but overall does not differ between RRMS and SPMS. SCV proved to be a strong predictor of physical disability and disease progression, indicating that SCV may be a suitable marker for monitoring disease activity and severity.

Cerebellar dysfunction is an important contributor to disability in patients with multiple sclerosis (MS), however, few in vivo studies focused on cerebellar volume loss so far. This relates to technical challenges regarding the segmentation of the cerebellum. In this study, we evaluated the semi-automatic ECCET software for performing cerebellar volumetry using high-resolution 3D T1-MR scans in patients with MS and healthy volunteers. We performed test-retest as well as inter-observer reliability testing of cerebellar segmentation and compared the ECCET results with a fully automatic cerebellar segmentation using the FreeSurfer software pipeline in 15 MS patients. In a pilot matched-pair analysis with another data set from 15 relapsing-remitting MS patients and 15 age- and sex-matched healthy controls (HC), we assessed the feasibility of the ECCET approach to detect MS-related cerebellar volume differences. For total normalized cerebellar volume as well as grey and white matter volumes, intrarater (intraclass correlation coefficient (ICC)=0.99, 95% CI=0.98-0.99) and interobserver agreement (ICC=0.98, 95% CI=0.74-0.99) were strong. Comparison between ECCET and FreeSurfer results likewise yielded a good intraclass correlation (ICC=0.86, 95% CI=0.58-0.95). Compared to HC, MS patients had significantly reduced normalized total brain, total cerebellar, and grey matter volumes (p≤0.05). ECCET is a suitable tool for cerebellar segmentation showing excellent test-retest and inter-observer reliability. Our matched-pair analysis between MS patients and healthy volunteers suggests that the method is sensitive and reliable in detecting cerebellar atrophy in MS

We present an automated method for localizing an anatomical landmark in three-dimensional medical images. The method combines two recurrent neural networks in a coarse-to-fine approach: The first network determines a candidate neighborhood by analyzing the complete given image volume. The second network localizes the actual landmark precisely and accurately in the candidate neighborhood. Both networks take advantage of multi-dimensional gated recurrent units in their main layers, which allow for high model complexity with a comparatively small set of parameters. We localize the medullopontine sulcus in 3D magnetic resonance images of the head and neck. We show that the proposed approach outperforms similar localization techniques both in terms of mean distance in millimeters and voxels w.r.t. manual labelings of the data. With a mean localization error of 1.7 mm, the proposed approach performs on par with neurological experts, as we demonstrate in an interrater comparison., Comment: 8 pages, 3 figures, 1 table

BACKGROUND: Iron accumulation in deep grey matter (GM) structures is a consistent finding in multiple sclerosis (MS) patients. This study focused on the identification of independent determinants of iron accumulation using R2* mapping.SUBJECTS AND METHODS: Ninety-seven MS patients and 81 healthy controls were included in this multicentre study. R2* mapping was performed on 3T MRI systems. R2*in deep GM was corrected for age and was related to disease duration, disability, T2 lesion load and brain volume.RESULTS: Compared to controls, R2* was increased in all deep GM regions of MS patients except the globus pallidus and the substantia nigra. R2* increase was most pronounced in the progressive stage of the disease and independently predicted by disease duration and disability. Reduced cortical volume was not associated with iron accumulation in the deep GM with the exception of the substantia nigra and the red nucleus. In lesions, R2* was inversely correlated with disease duration and higher total lesion load.CONCLUSION: Iron accumulation in deep GM of MS patients is most strongly and independently associated with duration and severity of the disease. Additional associations between cortical GM atrophy and deep GM iron accumulation appear to exist in a region specific manner.

BACKGROUND: Iron accumulation in deep grey matter (GM) structures is a consistent finding in multiple sclerosis (MS) patients. This study focused on the identification of independent determinants of iron accumulation using R2* mapping.SUBJECTS AND METHODS: Ninety-seven MS patients and 81 healthy controls were included in this multicentre study. R2* mapping was performed on 3T MRI systems. R2*in deep GM was corrected for age and was related to disease duration, disability, T2 lesion load and brain volume.RESULTS: Compared to controls, R2* was increased in all deep GM regions of MS patients except the globus pallidus and the substantia nigra. R2* increase was most pronounced in the progressive stage of the disease and independently predicted by disease duration and disability. Reduced cortical volume was not associated with iron accumulation in the deep GM with the exception of the substantia nigra and the red nucleus. In lesions, R2* was inversely correlated with disease duration and higher total lesion load.CONCLUSION: Iron accumulation in deep GM of MS patients is most strongly and independently associated with duration and severity of the disease. Additional associations between cortical GM atrophy and deep GM iron accumulation appear to exist in a region specific manner.

Magnetization transfer ratio (MTR) is a semi-quantitative measure that seems to correlate with the degree of myelin loss and generally tissue destruction in multiple sclerosis (MS). Our objective wasto comprehensively assess the MTR of lesions and normal appearing (NA) tissue separately in the white matter (WM), the cortex, the thalamus and the basal ganglia (BG) and determine their relative contribution to disability. In this cross-sectional study 71 patients were included (59 with relapsing-remitting MS, 12 with secondary progressive MS). We used a three-dimensional MTR sequence with high spatial resolution, based on balanced steady-state free precession. Mean MTR was calculated for lesions and NA tissue separately for each tissue type. Lesional MTR was lower than normal-appearing MTR in WM, cortex and thalamus. In the regression analysis, MTR of cortical lesions (β=−0.23, p=0.05) and MTR of WML (β=−0.21, p=0.08) were related by trend to the expanded disability status scale. MTR of WML significantly predicted the paced auditory serial-addition test (β=0.35, p=0.004). MTR of normal-appearing tissue did not relate to any outcome. Our results suggest that MTR of lesions in the white matter and cortex rather than of normal-appearing tissue relates to disability in patients with MS.

See Giovannoni (doi:10.1093/brain/awy200) for a scientific commentary on this article. Biomarkers of tissue damage in multiple sclerosis are urgently needed. Barro et al. show that serum neurofilament light chain (NfL) levels are increased in patients versus healthy controls and reflect radiological and clinical disease activity and progression. High serum NfL is associated with greater subsequent brain and spinal cord atrophy.

Cerebellar dysfunction is an important contributor to disability in patients with multiple sclerosis (MS), however, few in vivo studies focused on cerebellar volume loss so far. This relates to technical challenges regarding the segmentation of the cerebellum. In this study, we evaluated the semi-automatic ECCET software for performing cerebellar volumetry using high-resolution 3D T1-MR scans in patients with MS and healthy volunteers. We performed test-retest as well as inter-observer reliability testing of cerebellar segmentation and compared the ECCET results with a fully automatic cerebellar segmentation using the FreeSurfer software pipeline in 15 MS patients. In a pilot matched-pair analysis with another data set from 15 relapsing-remitting MS patients and 15 age- and sex-matched healthy controls (HC), we assessed the feasibility of the ECCET approach to detect MS-related cerebellar volume differences. For total normalized cerebellar volume as well as grey and white matter volumes, intrarater (intraclass correlation coefficient (ICC)=0.99, 95% CI=0.98-0.99) and interobserver agreement (ICC=0.98, 95% CI=0.74-0.99) were strong. Comparison between ECCET and FreeSurfer results likewise yielded a good intraclass correlation (ICC=0.86, 95% CI=0.58-0.95). Compared to HC, MS patients had significantly reduced normalized total brain, total cerebellar, and grey matter volumes (p≤0.05). ECCET is a suitable tool for cerebellar segmentation showing excellent test-retest and inter-observer reliability. Our matched-pair analysis between MS patients and healthy volunteers suggests that the method is sensitive and reliable in detecting cerebellar atrophy in MS