Abstract #3595

Validation of a Semi-Automated Method to Quantify Lesion Volume Changes in Multiple Sclerosis Using Subtraction Images

Rozemarijn M. Mattiesing¹, Serena Stel¹, Alysha S. Mangroe¹, Iman Brouwer¹, Adriaan Versteeg¹, Ronald A. van Schijndel¹, Bernard M.J. Uitdehaag², Frederik Barkhof^1,3, Hugo Vrenken¹, and Joost P.A. Kuijer¹

¹MS Center Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, Netherlands, ²MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC location VUmc, Amsterdam, Netherlands, ³UCL London, Institutes of Neurology and Healthcare Engineering, London, United Kingdom

Synopsis

Keywords: Segmentation, Multiple SclerosisMonitoring changes in white matter lesions with MRI is important to evaluate the effects of treatment in multiple sclerosis. In this study a validation of a semi-automated method to quantify lesion volume changes based on 2D proton-density-weighted images and image subtraction was performed. With this method new and enlarging but also disappearing and shrinking lesion activity can be quantified. As assessed with the intraclass correlation coefficient for absolute agreement, we found that the reproducibility was excellent and the accuracy was good overall. This semi-automated subtraction method can reliably quantify lesion volume changes in patients with (early) multiple sclerosis.

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