Automated Method for Identification of Patients With Alzheimer’s Disease Based on Three-dimensional MR Images

Arimura, Hidetaka; Yoshiura, Takashi; Kumazawa, Seiji; Tanaka, Kazuhiro; Koga, Hiroshi; Mihara, Futoshi; Honda, Hiroshi; Sakai, Shuji; Toyofuku, Fukai; Higashida, Yoshiharu

doi:10.1016/j.acra.2007.10.020

« Previous Next »Academic Radiology
Volume 15, Issue 3 , Pages 274-284, March 2008

Automated Method for Identification of Patients With Alzheimer’s Disease Based on Three-dimensional MR Images

Hidetaka Arimura, PhD
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
- Address correspondence to: H.A.
Takashi Yoshiura, MD, PhD
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Seiji Kumazawa, PhD
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Kazuhiro Tanaka, MD, PhD
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Hiroshi Koga, MD, PhD
- Department of Neuropsychiatry, Okumura Hospital, Fukuoka 839-1321, Japan
Futoshi Mihara, MD, PhD
- Department of Radiology, National Fukuoka-Higashi Medical Center, Fukuoka 811-3195, Japan.
Hiroshi Honda, MD, PhD
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Shuji Sakai, MD, PhD
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Fukai Toyofuku, PhD
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
Yoshiharu Higashida, PhD
- Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan

Received 10 July 2007; accepted 12 October 2007.

Rationale and Objectives

An automated method for identification of patients with cerebral atrophy due to Alzheimer’s disease (AD) was developed based on three-dimensional (3D) T1-weighted magnetic resonance (MR) images.

Materials and Methods

Our proposed method consisted of determination of atrophic image features and identification of AD patients. The atrophic image features included white matter and gray matter volumes, cerebrospinal fluid (CSF) volume, and cerebral cortical thickness determined based on a level set method. The cortical thickness was measured with normal vectors on a voxel-by-voxel basis, which were determined by differentiating a level set function. The CSF spaces within cerebral sulci and lateral ventricles (LVs) were extracted by wrapping the brain tightly in a propagating surface determined with a level set method. Identification of AD cases was performed using a support vector machine (SVM) classifier, which was trained by the atrophic image features of AD and non-AD cases, and then an unknown case was classified into either AD or non-AD group based on an SVM model. We applied our proposed method to MR images of the whole brains obtained from 54 cases, including 29 clinically diagnosed AD cases (age range, 52−82 years; mean age, 70 years) and 25 non-AD cases (age range, 49−78 years; mean age, 62 years).

Results

As a result, the area under a receiver operating characteristic (ROC) curve (Az value) obtained by our computerized method was 0.909 based on a leave-one-out test in identification of AD cases among 54 cases.