ArticleNeuroImage. Clinical2019
Validation of mean upper cervical cord area (MUCCA) measurement techniques in multiple sclerosis (MS): High reproducibility and robustness to lesions, but large software and scanner effects.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 31 citations in OpenAlex.
- Charting Cervical Spinal Cord Morphometry Across the Lifespan.Human brain mapping · 2026Article
- Charting Cervical Spinal Cord Morphometry Across the Lifespan.bioRxiv : the preprint server for biology · 2026Article
- Spinal Cord Abnormalities in Early Pediatric Multiple Sclerosis.Annals of clinical and translational neurology · 2025Article
- Multiple Sclerosis-Specific Reference Curves for Brain Volumes to Explain Disease Severity.Neurology · 2025Observational
- Super-Resolution in Clinically Available Spinal Cord MRIs Enables Automated Atrophy Analysis.AJNR. American journal of neuroradiology · 2025Article
- Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.Frontiers in neurology · 2025Article
- Progressive cervical cord atrophy parallels cognitive decline in Alzheimer's disease.Scientific reports · 2024Article
- Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future.Brain communications · 2024Review
- A database of the healthy human spinal cord morphometry in the PAM50 template space.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- The role of diet in multiple sclerosis onset and course: results from a nationwide retrospective birth-year cohort.Annals of clinical and translational neurology · 2023Article
- Spinal Cord Atrophy Predicts Progressive Disease in Relapsing Multiple Sclerosis.Annals of neurology · 2022Observational
- Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction.Frontiers in neuroimaging · 2022Article
- Quantification of Cervical Cord Cross-Sectional Area: Which Acquisition, Vertebra Level, and Analysis Software? A Multicenter Repeatability Study on a Traveling Healthy Volunteer.Frontiers in neurology · 2021Article
- Considerations for Mean Upper Cervical Cord Area Implementation in a Longitudinal MRI Setting: Methods, Interrater Reliability, and MRI Quality Control.AJNR. American journal of neuroradiology · 2020Article
- Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders.Frontiers in neurology · 2020Review
- Spinal cord atrophy in a primary progressive multiple sclerosis trial: Improved sample size using GBSI.NeuroImage. Clinical · 2020Article
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Authors and funding
14 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAtrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking.
methodsFive methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations.
resultsIn dataset A, MUCCA differed between MR machines (p < 0.001) and methods (p < 0.001) used, but not between scan sessions. With respect to MUCCA values, Xinapse JIM showed the highest within-scanner reproducibility (ICC absolute agreement = 0.995) while Xinapse JIM and SCT-PropSeg showed the highest between-scanner robustness (ICC consistency = 0.981 and 0.976, respectively). Reproducibility of segmentations between scan sessions was highest in Xinapse JIM and SCT-PropSeg segmentations (median SI ≥ 0.921), with a significant main effect of method (p < 0.001), but not of MR machine or subject group. In dataset B, SI with manual outlines did not differ between patients with or without cervical lesions for any of the segmentation methods (p > 0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p < 0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement = 0.940 and median SI = 0.962).
conclusionAlthough MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance.
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