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Automated brain volumetrics in multiple sclerosis: a step closer to clinical application
  1. C Wang1,2,
  2. H N Beadnall2,
  3. S N Hatton1,2,
  4. G Bader3,
  5. D Tomic3,
  6. D G Silva3,
  7. M H Barnett1,2
  1. 1Sydney Neuroimaging Analysis Centre, Sydney, New South Wales, Australia
  2. 2Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
  3. 3Novartis Pharma AG, Basel, Switzerland
  1. Correspondence to Associate Professor, MH Barnett, Sydney Medical School, Brain and Mind Centre, The University of Sydney, Sydney, NSW 2006 Australia; michael{at}sydneyneurology.com.au

Abstract

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.

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