A decision tree for differentiating multiple system ...
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A decision tree for differentiating multiple system atrophy from Parkinson’s disease using 3-T MR imaging Shalini Rajandran Nair, Li Kuo Tan, Norlisah Mohd Ramli, Shen Yang Lim, Kartini Rahmat & Hazman Mohd Nor European Radiology ISSN 0938-7994 Eur Radiol DOI 10.1007/s00330-012-2759-9
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Author's personal copy Eur Radiol DOI 10.1007/s00330-012-2759-9
NEURO
A decision tree for differentiating multiple system atrophy from Parkinson’s disease using 3-T MR imaging Shalini Rajandran Nair & Li Kuo Tan & Norlisah Mohd Ramli & Shen Yang Lim & Kartini Rahmat & Hazman Mohd Nor
Received: 22 July 2012 / Revised: 26 November 2012 / Accepted: 28 November 2012 # European Society of Radiology 2013
Abstract Objective To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson’s disease (PD). Methods 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3. Results Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta–rostral) showed statistically significant (P
