Clinical feasibility of longitudinal lateral ventricular volume measurements on T2-FLAIR across MRI scanner changes
•Central and whole brain atrophy are faster in MS patients with disability progression.•These measures can be reliably assessed on clinically-available FLAIR images.•They are meaningful even with longitudinal scanner and field strength changes. Greater brain atrophy is associated with disability pro...
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Veröffentlicht in: | NeuroImage clinical 2021-01, Vol.29, p.102554-102554, Article 102554 |
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Sprache: | eng |
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Zusammenfassung: | •Central and whole brain atrophy are faster in MS patients with disability progression.•These measures can be reliably assessed on clinically-available FLAIR images.•They are meaningful even with longitudinal scanner and field strength changes.
Greater brain atrophy is associated with disability progression (DP) in patients with multiple sclerosis (PwMS). However, methodological challenges limit its routine clinical use.
To determine the feasibility of atrophy measures as markers of DP in PwMS scanned across different MRI field strengths.
A total of 980 PwMS were scanned on either 1.5 T or 3.0 T MRI scanners. Demographic and clinical data were retrospectively collected, and the presence of DP was determined according to standard clinical trial criteria. Lateral ventricular volume (LVV) change was measured with the NeuroSTREAM technique on clinical routine T2-FLAIR images. Percent brain volume change (PBVC) was measured using SIENA and ventricular cerebrospinal fluid (vCSF) % change was measured using VIENA and SIENAX algorithms on 3D T1-weighted images (WI). Stable vs. DP PwMS were compared using analysis of covariance (ANCOVA). Mixed modeling determined the effect of MRI scanner change on MRI-derived atrophy measures.
Longitudinal LVV analysis was successful in all PwMS. SIENA-based PBVC and VIENA-based changes failed in 37.6% of cases, while SIENAX-based vCSF failed in 12.9% of cases. PwMS with DP (n = 241) had significantly greater absolute (20.9% vs. 8.7%, d = 0.66, p |
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ISSN: | 2213-1582 2213-1582 |
DOI: | 10.1016/j.nicl.2020.102554 |