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Proceedings Paper

Accurate discrimination of Alzheimer's disease from other dementia and/or normal subjects using SPECT specific volume analysis
Author(s): Hitoshi Iyatomi; Jun Hashimoto; Fumuhito Yoshii; Toshiki Kazama; Shuichi Kawada; Yutaka Imai
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Paper Abstract

Discrimination between Alzheimer’s disease and other dementia is clinically significant, however it is often difficult. In this study, we developed classification models among Alzheimer’s disease (AD), other dementia (OD) and/or normal subjects (NC) using patient factors and indices obtained by brain perfusion SPECT. SPECT is commonly used to assess cerebral blood flow (CBF) and allows the evaluation of the severity of hypoperfusion by introducing statistical parametric mapping (SPM). We investigated a total of 150 cases (50 cases each for AD, OD, and NC) from Tokai University Hospital, Japan. In each case, we obtained a total of 127 candidate parameters from: (A) 2 patient factors (age and sex), (B) 12 CBF parameters and 113 SPM parameters including (C) 3 from specific volume analysis (SVA), and (D) 110 from voxel-based analysis stereotactic extraction estimation (vbSEE). We built linear classifiers with a statistical stepwise feature selection and evaluated the performance with the leave-one-out cross validation strategy. Our classifiers achieved very high classification performances with reasonable number of selected parameters. In the most significant discrimination in clinical, namely those of AD from OD, our classifier achieved both sensitivity (SE) and specificity (SP) of 96%. In a similar way, our classifiers achieved a SE of 90% and a SP of 98% in AD from NC, as well as a SE of 88% and a SP of 86% in AD from OD and NC cases. Introducing SPM indices such as SVA and vbSEE, classification performances improved around 7-15%. We confirmed that these SPM factors are quite important for diagnosing Alzheimer’s disease.

Paper Details

Date Published: 24 March 2014
PDF: 6 pages
Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 903523 (24 March 2014); doi: 10.1117/12.2044011
Show Author Affiliations
Hitoshi Iyatomi, Hosei Univ. (Japan)
Jun Hashimoto, Tokai Univ. School of Medicine (Japan)
Fumuhito Yoshii, Tokai Univ. School of Medicine (Japan)
Toshiki Kazama, Tokai Univ. School of Medicine (Japan)
Shuichi Kawada, Tokai Univ. School of Medicine (Japan)
Yutaka Imai, Tokai Univ. School of Medicine (Japan)

Published in SPIE Proceedings Vol. 9035:
Medical Imaging 2014: Computer-Aided Diagnosis
Stephen Aylward; Lubomir M. Hadjiiski, Editor(s)

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