Abstract #3469

Machine learning models using T1-mapping and arterial spin labeling images to identify Alzheimer’s disease and mild cognitive impairment

Shengyong Li¹, Xiaonan Wang^2,3, Yida Wang¹, Yang Song⁴, and Guang Yang¹

¹Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, ²Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Beijing, China, ³Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China, ⁴MR Scientific Marketing, Siemens Healthcare, Shanghai, China

Synopsis

Keywords: Alzheimer's Disease, Arterial spin labellingTo investigate the added value of T1-mapping to arterial spin labeling (ASL) for computer-aided early diagnosis of Alzheimer’s disease (AD). A total of 97 (45 AD/24 mild cognitive impairment (MCI)/38 normal control (NC)) people were enrolled retrospectively. We extracted features from 24 automatically segmented brain regions based on T1-mapping and ASL MR images and constructed three radiomics models to differentiate AD-NC/MIC-NC/AD-MCI, for which the radiomics models achieved a favorable prediction performance with the AUCs of 0.921/0.764/0.727, respectively.

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