Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral

MAGNIMS Study Group

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Objective: Spinal cord atrophy is a clinically relevant feature of multiple sclerosis (MS), but longitudinal assessments on magnetic resonance imaging using segmentation-based methods suffer from measurement variability, especially in multicenter studies. We compared the generalized boundary shift integral (GBSI), a registration-based method, with a standard segmentation-based method. Methods: Baseline and 1-year spinal cord 3-dimensional T1-weighted images (1mm isotropic) were obtained from 282 patients (52 clinically isolated syndrome [CIS], 196 relapsing–remitting MS [RRMS], 34 progressive MS [PMS]), and 82 controls from 8 MAGNIMS (Magnetic Resonance Imaging in Multiple Sclerosis) sites on multimanufacturer and multi–field-strength scans. Spinal Cord Toolbox was used for C2-5 segmentation and cross-sectional area (CSA) calculation. After cord straightening and registration, GBSI measured atrophy based on the probabilistic boundary-shift region of interest. CSA and GBSI percentage annual volume change was calculated. Results: GBSI provided similar rates of atrophy, but reduced measurement variability compared to CSA in all MS subtypes (CIS: −0.95 ± 2.11% vs −1.19 ± 3.67%; RRMS: −1.74 ± 2.57% vs −1.74 ± 4.02%; PMS: −2.29 ± 2.40% vs −1.29 ± 3.20%) and healthy controls (0.02 ± 2.39% vs −0.56 ± 3.77%). GBSI performed better than CSA in differentiating healthy controls from CIS (area under the curve [AUC] = 0.66 vs 0.53; p = 0.03), RRMS (AUC = 0.73 vs 0.59; p < 0.001), PMS (AUC = 0.77 vs 0.53; p < 0.001), and patients with disability progression from patients without progression (AUC = 0.59 vs 0.50; p = 0.04). Sample size to detect 60% treatment effect on spinal cord atrophy over 1 year was lower for GBSI than CSA (CIS: 106 vs 830; RRMS: 95 vs 335; PMS: 44 vs 215; power = 80%; alpha = 5%). Interpretation: The registration-based method (GBSI) allowed better separation between MS patients and healthy controls and improved statistical power, when compared with a conventional segmentation-based method (CSA), although it is still far from perfect. ANN NEUROL 2019.
Original languageEnglish
JournalAnnals of Neurology
DOIs
Publication statusPublished - 2019

Cite this

@article{a8b8b25ff93c4f54ac3de4af2dd17e43,
title = "Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral",
abstract = "Objective: Spinal cord atrophy is a clinically relevant feature of multiple sclerosis (MS), but longitudinal assessments on magnetic resonance imaging using segmentation-based methods suffer from measurement variability, especially in multicenter studies. We compared the generalized boundary shift integral (GBSI), a registration-based method, with a standard segmentation-based method. Methods: Baseline and 1-year spinal cord 3-dimensional T1-weighted images (1mm isotropic) were obtained from 282 patients (52 clinically isolated syndrome [CIS], 196 relapsing–remitting MS [RRMS], 34 progressive MS [PMS]), and 82 controls from 8 MAGNIMS (Magnetic Resonance Imaging in Multiple Sclerosis) sites on multimanufacturer and multi–field-strength scans. Spinal Cord Toolbox was used for C2-5 segmentation and cross-sectional area (CSA) calculation. After cord straightening and registration, GBSI measured atrophy based on the probabilistic boundary-shift region of interest. CSA and GBSI percentage annual volume change was calculated. Results: GBSI provided similar rates of atrophy, but reduced measurement variability compared to CSA in all MS subtypes (CIS: −0.95 ± 2.11{\%} vs −1.19 ± 3.67{\%}; RRMS: −1.74 ± 2.57{\%} vs −1.74 ± 4.02{\%}; PMS: −2.29 ± 2.40{\%} vs −1.29 ± 3.20{\%}) and healthy controls (0.02 ± 2.39{\%} vs −0.56 ± 3.77{\%}). GBSI performed better than CSA in differentiating healthy controls from CIS (area under the curve [AUC] = 0.66 vs 0.53; p = 0.03), RRMS (AUC = 0.73 vs 0.59; p < 0.001), PMS (AUC = 0.77 vs 0.53; p < 0.001), and patients with disability progression from patients without progression (AUC = 0.59 vs 0.50; p = 0.04). Sample size to detect 60{\%} treatment effect on spinal cord atrophy over 1 year was lower for GBSI than CSA (CIS: 106 vs 830; RRMS: 95 vs 335; PMS: 44 vs 215; power = 80{\%}; alpha = 5{\%}). Interpretation: The registration-based method (GBSI) allowed better separation between MS patients and healthy controls and improved statistical power, when compared with a conventional segmentation-based method (CSA), although it is still far from perfect. ANN NEUROL 2019.",
author = "{MAGNIMS Study Group} and Marcello Moccia and Ferran Prados and Massimo Filippi and Rocca, {Maria A.} and Paola Valsasina and Brownlee, {Wallace J.} and Chiara Zecca and Antonio Gallo and Alex Rovira and Achim Gass and Jacqueline Palace and Carsten Lukas and Hugo Vrenken and Sebastien Ourselin and {Gandini Wheeler-Kingshott}, {Claudia A. M.} and Olga Ciccarelli and Frederik Barkhof",
year = "2019",
doi = "10.1002/ana.25571",
language = "English",
journal = "Annals of Neurology",
issn = "0364-5134",
publisher = "John Wiley and Sons Inc.",

}

Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral. / MAGNIMS Study Group.

In: Annals of Neurology, 2019.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Longitudinal spinal cord atrophy in multiple sclerosis using the generalized boundary shift integral

AU - MAGNIMS Study Group

AU - Moccia, Marcello

AU - Prados, Ferran

AU - Filippi, Massimo

AU - Rocca, Maria A.

AU - Valsasina, Paola

AU - Brownlee, Wallace J.

AU - Zecca, Chiara

AU - Gallo, Antonio

AU - Rovira, Alex

AU - Gass, Achim

AU - Palace, Jacqueline

AU - Lukas, Carsten

AU - Vrenken, Hugo

AU - Ourselin, Sebastien

AU - Gandini Wheeler-Kingshott, Claudia A. M.

AU - Ciccarelli, Olga

AU - Barkhof, Frederik

PY - 2019

Y1 - 2019

N2 - Objective: Spinal cord atrophy is a clinically relevant feature of multiple sclerosis (MS), but longitudinal assessments on magnetic resonance imaging using segmentation-based methods suffer from measurement variability, especially in multicenter studies. We compared the generalized boundary shift integral (GBSI), a registration-based method, with a standard segmentation-based method. Methods: Baseline and 1-year spinal cord 3-dimensional T1-weighted images (1mm isotropic) were obtained from 282 patients (52 clinically isolated syndrome [CIS], 196 relapsing–remitting MS [RRMS], 34 progressive MS [PMS]), and 82 controls from 8 MAGNIMS (Magnetic Resonance Imaging in Multiple Sclerosis) sites on multimanufacturer and multi–field-strength scans. Spinal Cord Toolbox was used for C2-5 segmentation and cross-sectional area (CSA) calculation. After cord straightening and registration, GBSI measured atrophy based on the probabilistic boundary-shift region of interest. CSA and GBSI percentage annual volume change was calculated. Results: GBSI provided similar rates of atrophy, but reduced measurement variability compared to CSA in all MS subtypes (CIS: −0.95 ± 2.11% vs −1.19 ± 3.67%; RRMS: −1.74 ± 2.57% vs −1.74 ± 4.02%; PMS: −2.29 ± 2.40% vs −1.29 ± 3.20%) and healthy controls (0.02 ± 2.39% vs −0.56 ± 3.77%). GBSI performed better than CSA in differentiating healthy controls from CIS (area under the curve [AUC] = 0.66 vs 0.53; p = 0.03), RRMS (AUC = 0.73 vs 0.59; p < 0.001), PMS (AUC = 0.77 vs 0.53; p < 0.001), and patients with disability progression from patients without progression (AUC = 0.59 vs 0.50; p = 0.04). Sample size to detect 60% treatment effect on spinal cord atrophy over 1 year was lower for GBSI than CSA (CIS: 106 vs 830; RRMS: 95 vs 335; PMS: 44 vs 215; power = 80%; alpha = 5%). Interpretation: The registration-based method (GBSI) allowed better separation between MS patients and healthy controls and improved statistical power, when compared with a conventional segmentation-based method (CSA), although it is still far from perfect. ANN NEUROL 2019.

AB - Objective: Spinal cord atrophy is a clinically relevant feature of multiple sclerosis (MS), but longitudinal assessments on magnetic resonance imaging using segmentation-based methods suffer from measurement variability, especially in multicenter studies. We compared the generalized boundary shift integral (GBSI), a registration-based method, with a standard segmentation-based method. Methods: Baseline and 1-year spinal cord 3-dimensional T1-weighted images (1mm isotropic) were obtained from 282 patients (52 clinically isolated syndrome [CIS], 196 relapsing–remitting MS [RRMS], 34 progressive MS [PMS]), and 82 controls from 8 MAGNIMS (Magnetic Resonance Imaging in Multiple Sclerosis) sites on multimanufacturer and multi–field-strength scans. Spinal Cord Toolbox was used for C2-5 segmentation and cross-sectional area (CSA) calculation. After cord straightening and registration, GBSI measured atrophy based on the probabilistic boundary-shift region of interest. CSA and GBSI percentage annual volume change was calculated. Results: GBSI provided similar rates of atrophy, but reduced measurement variability compared to CSA in all MS subtypes (CIS: −0.95 ± 2.11% vs −1.19 ± 3.67%; RRMS: −1.74 ± 2.57% vs −1.74 ± 4.02%; PMS: −2.29 ± 2.40% vs −1.29 ± 3.20%) and healthy controls (0.02 ± 2.39% vs −0.56 ± 3.77%). GBSI performed better than CSA in differentiating healthy controls from CIS (area under the curve [AUC] = 0.66 vs 0.53; p = 0.03), RRMS (AUC = 0.73 vs 0.59; p < 0.001), PMS (AUC = 0.77 vs 0.53; p < 0.001), and patients with disability progression from patients without progression (AUC = 0.59 vs 0.50; p = 0.04). Sample size to detect 60% treatment effect on spinal cord atrophy over 1 year was lower for GBSI than CSA (CIS: 106 vs 830; RRMS: 95 vs 335; PMS: 44 vs 215; power = 80%; alpha = 5%). Interpretation: The registration-based method (GBSI) allowed better separation between MS patients and healthy controls and improved statistical power, when compared with a conventional segmentation-based method (CSA), although it is still far from perfect. ANN NEUROL 2019.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070923988&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/31385358

U2 - 10.1002/ana.25571

DO - 10.1002/ana.25571

M3 - Article

JO - Annals of Neurology

JF - Annals of Neurology

SN - 0364-5134

ER -