RT Journal Article
SR Electronic
T1 Quantification of Thalamic Atrophy in MS: From the Multicenter Italian Neuroimaging Network Initiative Data Set to Clinical Application
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 1399
OP 1404
DO 10.3174/ajnr.A8050
VO 44
IS 12
A1 Storelli, Loredana
A1 Pagani, Elisabetta
A1 Pantano, Patrizia
A1 Gallo, Antonio
A1 De Stefano, Nicola
A1 Rocca, Maria A.
A1 Filippi, Massimo
A1 for the INNI Network
YR 2023
UL http://www.ajnr.org/content/44/12/1399.abstract
AB BACKGROUND AND PURPOSE: Thalamic atrophy occurs from the earliest phases of MS; however, this measure is not included in clinical practice. Our purpose was to obtain a reliable segmentation of the thalamus in MS by comparing existing automatic methods cross-sectionally and longitudinally.MATERIALS AND METHODS: MR images of 141 patients with relapsing-remitting MS (mean age, 38 years; range, 19–58 years; 95 women) and 69 healthy controls (mean age, 36 years; range, 22–69 years; 47 women) were retrieved from the Italian Neuroimaging Network Initiative repository: T1WI, T2WI, and DWI at baseline and after 1 year (136 patients, 31 healthy controls). Three segmentation software programs (FSL-FIRST, FSL-MIST, FreeSurfer) were compared. At baseline, agreement among pipelines, correlations with age, disease duration, clinical score, and T2-hyperintense lesion volume were evaluated. Effect sizes in differentiating patients and controls were assessed cross-sectionally and longitudinally. Variability of longitudinal changes in controls and sample sizes were assessed. False discovery rate–adjusted P < .05 was considered significant.RESULTS: At baseline, FSL-FIRST and FSL-MIST showed the highest agreement in the results of thalamic volume (R = 0.87, P < .001), with the highest effect size for FSL-MIST (Cohen d = 1.11); correlations with demographic and clinical variables were comparable for all software. Longitudinally, FSL-MIST showed the lowest variability in estimating thalamic volume changes for healthy controls (SD = 1.07%), the highest effect size (Cohen d = 0.44), and the smallest sample size at 80% power level (15 subjects per group).CONCLUSIONS: Multimodal segmentation by FSL-MIST increased the robustness of the results with better capability to detect small variations in thalamic volumes.EDSSExpanded Disability Status ScaleFAfractional anisotropyHChealthy controlsICCintraclass correlation coefficientINNIItalian Neuroimaging Network InitiativeLVlesion volumesRRrelapsing-remitting