Methods for Brain Atrophy MR Quantification in Multiple Sclerosis: Application to the Multicenter INNI Dataset

被引:6
|
作者
Storelli, Loredana [1 ]
Pagani, Elisabetta [1 ]
Pantano, Patrizia [2 ,3 ]
Piervincenzi, Claudia [2 ]
Tedeschi, Gioacchino [4 ,5 ]
Gallo, Antonio [4 ,5 ]
De Stefano, Nicola [6 ]
Battaglini, Marco [6 ]
Rocca, Maria A. [1 ,7 ]
Filippi, Massimo [1 ,7 ,8 ,9 ,10 ]
INNI Network
机构
[1] IRCCS San Raffaele Sci Inst, Div Neurosci, Neuroimaging Res Unit, Via Olgettina 60, I-20132 Milan, Italy
[2] Sapienza Univ Rome, Dept Human Neurosci, Rome, Italy
[3] IRCCS NEUROMED, Pozzilli, Italy
[4] Univ Campania Luigi Vanvitelli, Dept Adv Med & Surg Sci, Naples, Italy
[5] Univ CampaniaLuigi Vanvitelli, 3T MRI Ctr, Naples, Italy
[6] Univ Siena, Dept Med Surg & Neurosci, Siena, Italy
[7] IRCCS San Raffaele Sci Inst, Neurol Unit, Milan, Italy
[8] Univ Vita Salute San Raffaele, Milan, Italy
[9] IRCCS San Raffaele Sci Inst, Neurorehabil Unit, Milan, Italy
[10] IRCCS San Raffaele Sci Inst, Neurophysiol Serv, Milan, Italy
关键词
multiple sclerosis; brain atrophy; atrophy pipelines; Italian Neuroimaging Network Initiative; GREY-MATTER ATROPHY; GRAY-MATTER; CONSENSUS RECOMMENDATIONS; MS; IMPAIRMENT;
D O I
10.1002/jmri.28616
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background Current therapeutic strategies in multiple sclerosis (MS) target neurodegeneration. However, the integration of atrophy measures into the clinical scenario is still an unmet need.Purpose To compare methods for whole-brain and gray matter (GM) atrophy measurements using the Italian Neuroimaging Network Initiative (INNI) dataset.Study Type Retrospective (data available from INNI).Population A total of 466 patients with relapsing-remitting MS (mean age = 37.3 +/- 10 years, 323 women) and 279 healthy controls (HC; mean age = 38.2 +/- 13 years, 164 women).Field Strength/SequenceA 3.0-T, T1-weighted (spin echo and gradient echo without gadolinium injection) and T2-weighted spin echo scans at baseline and after 1 year (170 MS, 48 HC).Assessment Structural Image Evaluation using Normalization of Atrophy (SIENA-X/XL; version 5.0.9), Statistical Parametric Mapping (SPM-v12); and Jim-v8 (Xinapse Systems, Colchester, UK) software were applied to all subjects.Statistical Tests In MS and HC, we evaluated the intraclass correlation coefficient (ICC) among FSL-SIENA(XL), SPM-v12, and Jim-v8 for cross-sectional whole-brain and GM tissue volumes and their longitudinal changes, the effect size according to the Cohen's d at baseline and the sample size requirement for whole-brain and GM atrophy progression at different power levels (lowest = 0.7, 0.05 alpha level). False discovery rate (Benjamini-Hochberg procedure) correction was applied. A P valueSPM-v12 and Jim-v8 showed significant agreement for cross-sectional whole-brain (ICC = 0.93 for HC and ICC = 0.84 for MS) and GM volumes (ICC = 0.66 for HC and ICC = 0.90) and longitudinal assessment of GM atrophy (ICC = 0.35 for HC and ICC = 0.59 for MS), while no significant agreement was found in the comparisons between whole-brain and GM volumes for SIENA-X/XL and both SPM-v12 (P = 0.19 and P = 0.29, respectively) and Jim-v8 (P = 0.21 and P = 0.32, respectively). SPM-v12 and Jim-v8 showed the highest effect size for cross-sectional GM atrophy (Cohen's d = -0.63 and -0.61). Jim-v8 and SIENA(XL) showed the smallest sample size requirements for whole-brain (58) and GM atrophy (152), at 0.7 power level.Data ConclusionThe findings obtained in this study should be considered when selecting the appropriate brain atrophy pipeline for MS studies.Evidence Level4.Technical EfficacyStage 1.
引用
收藏
页码:1221 / 1231
页数:11
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