Magnetic resonance support vector machine discriminates essential tremor with rest tremor from tremor‐dominant Parkinson disease. Issue 9 (13th April 2014)

• Record Type: Journal Article
• Authors: Cherubini, Andrea; Nisticó, Rita; Novellino, Fabiana; Salsone, Maria; Nigro, Salvatore; Donzuso, Giulia; Quattrone, Aldo
• Is Part Of: Movement disorders. Volume 29:Issue 9(2014)
• Page Start: 1216
• Page End: 1219
• Publication Date: 2014-04-13
• Subjects: Movement disorders -- Periodicals; 610
• DOI: 10.1002/mds.25869
• Languages: English
• ISSNs: 0885-3185

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <sec id="mds25869-sec-0001" sec-type="section"> <title>Background</title> <p>The aim of the current study was to distinguish patients who had tremor‐dominant Parkinson's disease (tPD) from those who had essential tremor with rest tremor (rET).</p> </sec> <sec id="mds25869-sec-0002" sec-type="section"> <title>Methods</title> <p>We combined voxel‐based morphometry‐derived gray matter and white matter volumes and diffusion tensor imaging‐derived mean diffusivity and fractional anisotropy in a support vector machine (SVM) to evaluate 15 patients with rET and 15 patients with tPD. Dopamine transporter single‐photon emission computed tomography imaging was used as ground truth.</p> </sec> <sec id="mds25869-sec-0003" sec-type="section"> <title>Results</title> <p>SVM classification of individual patients showed that no single predictor was able to fully discriminate patients with tPD from those with rET. By contrast, when all predictors were combined in a multi‐modal algorithm, SVM distinguished patients with rET from those with tPD with an accuracy of 100%.</p> </sec> <sec id="mds25869-sec-0004" sec-type="section"> <title>Conclusions</title> <p>SVM is an operator‐independent and automatic technique that may help distinguish patients with tPD from those with rET at the individual level. © 2014 International Parkinson and Movement Disorder Society</p> </sec> </abstract>