Automated brain volumetrics in multiple sclerosis: a step closer to clinical application

BACKGROUND: Whole brain volume (WBV) estimates in patients with multiple sclerosis (MS) correlate more robustly with clinical disability than traditional, lesion-based metrics. Numerous algorithms to measure WBV have been developed over the past two decades. We compare Structural Image Evaluation using Normalisation of Atrophy-Cross-sectional (SIENAX) to NeuroQuant and MSmetrix, for assessment of cross-sectional WBV in patients with MS. METHODS: MRIs from 61 patients with relapsing-remitting MS and 2 patients with clinically isolated syndrome were analysed. WBV measurements were calculated using SIENAX, NeuroQuant and MSmetrix. Statistical agreement between the methods was evaluated using linear regression and Bland-Altman plots. Precision and accuracy of WBV measurement was calculated for (1) NeuroQuant versus SIENAX and (2) MSmetrix versus SIENAX. RESULTS: Precision (Pearson's r) of WBV estimation for NeuroQuant and MSmetrix versus SIENAX was 0.983 and 0.992, respectively. Accuracy (Cb) was 0.871 and 0.994, respectively. NeuroQuant and MSmetrix showed a 5.5% and 1.0% volume difference compared with SIENAX, respectively, that was consistent across low and high values. CONCLUSIONS: In the analysed population, NeuroQuant and MSmetrix both quantified cross-sectional WBV with comparable statistical agreement to SIENAX, a well-validated cross-sectional tool that has been used extensively in MS clinical studies.