Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf
Background<p>Cervical cord atrophy is linked to disability in multiple sclerosis (MS). Cervical cord cross-sectional area (CSA) measurement for atrophy quantification using magnetic resonance imaging (MRI) has been technically validated, but information about effects of methodological choices...
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| _version_ | 1849927624791425024 |
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| author | Carsten Lukas (761342) |
| author2 | Barbara Bellenberg (3954938) Ferran Prados (3220977) Paola Valsasina (310901) Katrin Parmar (5248457) Iman Brouwer (388740) Deborah Pareto (2180984) Alex Rovira (396236) Jaume Sastre-Garriga (495101) Claudia A. M. Gandini Wheeler-Kingshott (3171387) Michael Amann (513041) Maria A. Rocca (7579022) Massimo Filippi (110054) Marios C. Yiannakas (11752994) Eva M. M. Strijbis (12869519) Frederik Barkhof (146873) Hugo Vrenken (387831) |
| author2_role | author author author author author author author author author author author author author author author author |
| author_facet | Carsten Lukas (761342) Barbara Bellenberg (3954938) Ferran Prados (3220977) Paola Valsasina (310901) Katrin Parmar (5248457) Iman Brouwer (388740) Deborah Pareto (2180984) Alex Rovira (396236) Jaume Sastre-Garriga (495101) Claudia A. M. Gandini Wheeler-Kingshott (3171387) Michael Amann (513041) Maria A. Rocca (7579022) Massimo Filippi (110054) Marios C. Yiannakas (11752994) Eva M. M. Strijbis (12869519) Frederik Barkhof (146873) Hugo Vrenken (387831) |
| author_role | author |
| dc.creator.none.fl_str_mv | Carsten Lukas (761342) Barbara Bellenberg (3954938) Ferran Prados (3220977) Paola Valsasina (310901) Katrin Parmar (5248457) Iman Brouwer (388740) Deborah Pareto (2180984) Alex Rovira (396236) Jaume Sastre-Garriga (495101) Claudia A. M. Gandini Wheeler-Kingshott (3171387) Michael Amann (513041) Maria A. Rocca (7579022) Massimo Filippi (110054) Marios C. Yiannakas (11752994) Eva M. M. Strijbis (12869519) Frederik Barkhof (146873) Hugo Vrenken (387831) |
| dc.date.none.fl_str_mv | 2025-11-26T05:14:26Z |
| dc.identifier.none.fl_str_mv | 10.3389/fneur.2025.1657484.s001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Data_Sheet_1_Optimization_of_cervical_cord_atrophy_measurement_using_a_real-world_multicentre_dataset_in_multiple_sclerosis_pdf/30717470 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Neurology and Neuromuscular Diseases CSA cross-sectional area cervical cord atrophy multiple sclerosis segmentation software optimization MRI |
| dc.title.none.fl_str_mv | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | Background<p>Cervical cord atrophy is linked to disability in multiple sclerosis (MS). Cervical cord cross-sectional area (CSA) measurement for atrophy quantification using magnetic resonance imaging (MRI) has been technically validated, but information about effects of methodological choices on associations of CSA with clinical variables is lacking.</p>Aim<p>Assessing how image acquisition, cord level selection, CSA normalization and segmentation software affect measurement variance, separation of clinical groups, correlations with clinical scores, and to formulate recommendations for future study designs.</p>Methods<p>Head and neck 3D-T1-weighted MRI of people with MS (pwMS, N = 85) and healthy controls (HC, N = 19) from five European centers. CSA measurements encompassed four methods (Active surface method ASM, NeuroQLab, SCT-Propseg and SCT-Deepseg), at two different levels of the cervical cord: C1-2 and C1-7 and normalization using four methods, based on cervical dimensions. Coefficient of variation (CV) of CSA was assessed in HC. In MS, Spearman correlations of CSA with EDSS were assessed. Separation between relapsing (rMS) and progressive MS (pMS) was quantified by area-under-the-curve (AUC) from receiver-operator-characteristic analysis.</p>Results<p>For all combinations of imaging, cord level, and segmentation software, unnormalized CSA differed between HC and pMS. CV in HC varied between 10.5 and 13.5% for unnormalized CSA and was lower for CSA normalized by C1-C2 (range: 9.4–12.0%) and C1-C3 vertebral height (8.6–12.6%). Unnormalized and normalized CSA correlated with EDSS scores for all measurement combinations (Spearman’s rho between −0.646 and −0.372, all corrected p < 0.001); correlations were stronger for CSA measured at vertebral level C1-7 than C1-2, and stronger for normalized than unnormalized CSA. Mean AUC for separating rMS from pMS ranged between 0.685 and 0.877, with higher AUC for CSA measured at the C1-7 than at the C1-2 vertebral level, and for normalized compared to unnormalized CSA.</p>Conclusion<p>Clinical performance of CSA quantification regarding discrimination between rMS and pMS and correlations with EDSS was better for whole cervical cord (C1-7) than for C1-2 measurements, and for normalization by C1-C2 or C1-C3 vertebral height. Based on the quantitative results of this exploratory multi-center study and on previous literature, we formulated recommendations to support future study design decisions.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_b905adf11867cf41d28ea407317996d9 |
| identifier_str_mv | 10.3389/fneur.2025.1657484.s001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30717470 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdfCarsten Lukas (761342)Barbara Bellenberg (3954938)Ferran Prados (3220977)Paola Valsasina (310901)Katrin Parmar (5248457)Iman Brouwer (388740)Deborah Pareto (2180984)Alex Rovira (396236)Jaume Sastre-Garriga (495101)Claudia A. M. Gandini Wheeler-Kingshott (3171387)Michael Amann (513041)Maria A. Rocca (7579022)Massimo Filippi (110054)Marios C. Yiannakas (11752994)Eva M. M. Strijbis (12869519)Frederik Barkhof (146873)Hugo Vrenken (387831)Neurology and Neuromuscular DiseasesCSAcross-sectional areacervical cordatrophymultiple sclerosissegmentation softwareoptimization MRIBackground<p>Cervical cord atrophy is linked to disability in multiple sclerosis (MS). Cervical cord cross-sectional area (CSA) measurement for atrophy quantification using magnetic resonance imaging (MRI) has been technically validated, but information about effects of methodological choices on associations of CSA with clinical variables is lacking.</p>Aim<p>Assessing how image acquisition, cord level selection, CSA normalization and segmentation software affect measurement variance, separation of clinical groups, correlations with clinical scores, and to formulate recommendations for future study designs.</p>Methods<p>Head and neck 3D-T1-weighted MRI of people with MS (pwMS, N = 85) and healthy controls (HC, N = 19) from five European centers. CSA measurements encompassed four methods (Active surface method ASM, NeuroQLab, SCT-Propseg and SCT-Deepseg), at two different levels of the cervical cord: C1-2 and C1-7 and normalization using four methods, based on cervical dimensions. Coefficient of variation (CV) of CSA was assessed in HC. In MS, Spearman correlations of CSA with EDSS were assessed. Separation between relapsing (rMS) and progressive MS (pMS) was quantified by area-under-the-curve (AUC) from receiver-operator-characteristic analysis.</p>Results<p>For all combinations of imaging, cord level, and segmentation software, unnormalized CSA differed between HC and pMS. CV in HC varied between 10.5 and 13.5% for unnormalized CSA and was lower for CSA normalized by C1-C2 (range: 9.4–12.0%) and C1-C3 vertebral height (8.6–12.6%). Unnormalized and normalized CSA correlated with EDSS scores for all measurement combinations (Spearman’s rho between −0.646 and −0.372, all corrected p < 0.001); correlations were stronger for CSA measured at vertebral level C1-7 than C1-2, and stronger for normalized than unnormalized CSA. Mean AUC for separating rMS from pMS ranged between 0.685 and 0.877, with higher AUC for CSA measured at the C1-7 than at the C1-2 vertebral level, and for normalized compared to unnormalized CSA.</p>Conclusion<p>Clinical performance of CSA quantification regarding discrimination between rMS and pMS and correlations with EDSS was better for whole cervical cord (C1-7) than for C1-2 measurements, and for normalization by C1-C2 or C1-C3 vertebral height. Based on the quantitative results of this exploratory multi-center study and on previous literature, we formulated recommendations to support future study design decisions.</p>2025-11-26T05:14:26ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/fneur.2025.1657484.s001https://figshare.com/articles/dataset/Data_Sheet_1_Optimization_of_cervical_cord_atrophy_measurement_using_a_real-world_multicentre_dataset_in_multiple_sclerosis_pdf/30717470CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307174702025-11-26T05:14:26Z |
| spellingShingle | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf Carsten Lukas (761342) Neurology and Neuromuscular Diseases CSA cross-sectional area cervical cord atrophy multiple sclerosis segmentation software optimization MRI |
| status_str | publishedVersion |
| title | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| title_full | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| title_fullStr | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| title_full_unstemmed | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| title_short | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| title_sort | Data Sheet 1_Optimization of cervical cord atrophy measurement using a real-world, multicentre dataset in multiple sclerosis.pdf |
| topic | Neurology and Neuromuscular Diseases CSA cross-sectional area cervical cord atrophy multiple sclerosis segmentation software optimization MRI |