Magnetic resonance support vector machine discriminates between Parkinson disease and progressive supranuclear palsy. Issue 2 (3rd December 2013)

• Record Type: Journal Article
• Authors: Cherubini, Andrea; Morelli, Maurizio; Nisticó, Rita; Salsone, Maria; Arabia, Gennarina; Vasta, Roberta; Augimeri, Antonio; Caligiuri, Maria Eugenia; Quattrone, Aldo
• Is Part Of: Movement disorders. Volume 29:Issue 2(2014)
• Page Start: 266
• Page End: 269
• Publication Date: 2013-12-03
• Subjects: Movement disorders -- Periodicals; 610
• DOI: 10.1002/mds.25737
• Languages: English
• ISSNs: 0885-3185

Abstract

<abstract abstract-type="main"> <title>ABSTRACT</title> <sec id="mds25737-sec-0001" sec-type="section"> <title>Background</title> <p>The aim of the current study was to distinguish patients with Parkinson disease (PD) from those with progressive supranuclear palsy (PSP) at the individual level using pattern recognition of magnetic resonance imaging data.</p> </sec> <sec id="mds25737-sec-0002" sec-type="section"> <title>Methods</title> <p>We combined diffusion tensor imaging and voxel‐based morphometry in a support vector machine algorithm to evaluate 21 patients with PSP and 57 patients with PD.</p> </sec> <sec id="mds25737-sec-0003" sec-type="section"> <title>Results</title> <p>The automated algorithm correctly distinguished patients who had PD from those who had PSP with 100% accuracy. This accuracy value was obtained when white matter atrophy was considered. Diffusion parameters combined with gray matter atrophy exhibited 90% sensitivity and 96% specificity.</p> </sec> <sec id="mds25737-sec-0004" sec-type="section"> <title>Conclusions</title> <p>Our findings demonstrate that automated pattern recognition can help distinguish patients with PSP from those with PD on an individual basis. © 2013 International Parkinson and Movement Disorder Society</p> </sec> </abstract>