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A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging

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). 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of inter...

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Main Authors:	Nair, S.R., Tan, L.K., Ramli, Norlisah, Lim, S.Y., Rahmat, K., Nor, H.M.
Format:	Article
Language:	English
Published:	Springer Verlag 2013
Subjects:	R Medicine
Online Access:	http://eprints.um.edu.my/11216/1/Nair-2013-A_decision_tree_for.pdf http://eprints.um.edu.my/11216/ http://www.ncbi.nlm.nih.gov/pubmed/23300042
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spelling	my.um.eprints.112162019-02-14T01:03:03Z http://eprints.um.edu.my/11216/ A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging Nair, S.R. Tan, L.K. Ramli, Norlisah Lim, S.Y. Rahmat, K. Nor, H.M. R Medicine 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). 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. 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 < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 sensitivity, 96 specificity, 92 PPV and 96 NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. aEuro cent Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. aEuro cent Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. aEuro cent A decision tree is descriptive and predictive in differentiating between clinical entities. aEuro cent A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy. Springer Verlag 2013 Article PeerReviewed text en http://eprints.um.edu.my/11216/1/Nair-2013-A_decision_tree_for.pdf Nair, S.R. and Tan, L.K. and Ramli, Norlisah and Lim, S.Y. and Rahmat, K. and Nor, H.M. (2013) A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging. European Radiology, 23 (6). pp. 1459-1466. ISSN 0938-7994 http://www.ncbi.nlm.nih.gov/pubmed/23300042
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
language	English
topic	R Medicine
spellingShingle	R Medicine Nair, S.R. Tan, L.K. Ramli, Norlisah Lim, S.Y. Rahmat, K. Nor, H.M. A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
description	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). 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. 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 < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 sensitivity, 96 specificity, 92 PPV and 96 NPV. Twelve out of 13 MSA patients were accurately classified. Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD. aEuro cent Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. aEuro cent Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. aEuro cent A decision tree is descriptive and predictive in differentiating between clinical entities. aEuro cent A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.
format	Article
author	Nair, S.R. Tan, L.K. Ramli, Norlisah Lim, S.Y. Rahmat, K. Nor, H.M.
author_facet	Nair, S.R. Tan, L.K. Ramli, Norlisah Lim, S.Y. Rahmat, K. Nor, H.M.
author_sort	Nair, S.R.
title	A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
title_short	A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
title_full	A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
title_fullStr	A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
title_full_unstemmed	A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging
title_sort	decision tree for differentiating multiple system atrophy from parkinson's disease using 3-t mr imaging
publisher	Springer Verlag
publishDate	2013
url	http://eprints.um.edu.my/11216/1/Nair-2013-A_decision_tree_for.pdf http://eprints.um.edu.my/11216/ http://www.ncbi.nlm.nih.gov/pubmed/23300042
_version_	1643688996329488384
score	13.211869

A decision tree for differentiating multiple system atrophy from Parkinson's disease using 3-T MR imaging

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