Establishing pathological cut-offs for lateral ventricular volume expansion rates
Language English Country Netherlands Media electronic-ecollection
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
29527505
PubMed Central
PMC5842310
DOI
10.1016/j.nicl.2018.02.009
PII: S2213-1582(18)30043-3
Knihovny.cz E-resources
- Keywords
- Brain atrophy, Multiple sclerosis, NEDA, Pathological cutoff, Ventricular volume,
- MeSH
- Databases, Factual statistics & numerical data MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Magnetic Resonance Imaging MeSH
- Nonlinear Dynamics MeSH
- Image Processing, Computer-Assisted MeSH
- Disability Evaluation MeSH
- Disease Progression MeSH
- Reference Values MeSH
- Multiple Sclerosis, Relapsing-Remitting diagnostic imaging pathology MeSH
- ROC Curve MeSH
- Severity of Illness Index MeSH
- Lateral Ventricles diagnostic imaging pathology MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: A percent brain volume change (PBVC) cut-off of -0.4% per year has been proposed to distinguish between pathological and physiological changes in multiple sclerosis (MS). Unfortunately, standardized PBVC measurement is not always feasible on scans acquired outside research studies or academic centers. Percent lateral ventricular volume change (PLVVC) is a strong surrogate measure of PBVC, and may be more feasible for atrophy assessment on real-world scans. However, the PLVVC rate corresponding to the established PBVC cut-off of -0.4% is unknown. OBJECTIVE: To establish a pathological PLVVC expansion rate cut-off analogous to -0.4% PBVC. METHODS: We used three complementary approaches. First, the original follow-up-length-weighted receiver operating characteristic (ROC) analysis method establishing whole brain atrophy rates was adapted to a longitudinal ventricular atrophy dataset of 177 relapsing-remitting MS (RRMS) patients and 48 healthy controls. Second, in the same dataset, SIENA PBVCs were used with non-linear regression to directly predict the PLVVC value corresponding to -0.4% PBVC. Third, in an unstandardized, real world dataset of 590 RRMS patients from 33 centers, the cut-off maximizing correspondence to PBVC was found. Finally, correspondences to clinical outcomes were evaluated in both datasets. RESULTS: ROC analysis suggested a cut-off of 3.09% (AUC = 0.83, p < 0.001). Non-linear regression R2 was 0.71 (p < 0.001) and a - 0.4% PBVC corresponded to a PLVVC of 3.51%. A peak in accuracy in the real-world dataset was found at a 3.51% PLVVC cut-off. Accuracy of a 3.5% cut-off in predicting clinical progression was 0.62 (compared to 0.68 for PBVC). CONCLUSIONS: Ventricular expansion of between 3.09% and 3.51% on T2-FLAIR corresponds to the pathological whole brain atrophy rate of 0.4% for RRMS. A conservative cut-off of 3.5% performs comparably to PBVC for clinical outcomes.
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