Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer's disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Luoyu Wang; Qi Feng; Xiuhong Ge; Fenyang Chen; Bo Yu; Bing Chen; Zhengluan Liao; Biying Lin; Yating Lv; Zhongxiang Ding

doi:10.3389/fnins.2022.970245

Textural features reflecting local activity of the hippocampus improve the diagnosis of Alzheimer's disease and amnestic mild cognitive impairment: A radiomics study based on functional magnetic resonance imaging

Front Neurosci. 2022 Aug 8:16:970245. doi: 10.3389/fnins.2022.970245. eCollection 2022.

Authors

Luoyu Wang^{1

2}, Qi Feng¹, Xiuhong Ge¹, Fenyang Chen³, Bo Yu⁴, Bing Chen⁵, Zhengluan Liao⁶, Biying Lin¹, Yating Lv⁷, Zhongxiang Ding¹

Affiliations

¹ Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
² The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
³ The Fourth School of Medical, Zhejiang Chinese Medical University, Hangzhou, China.
⁴ School of Medical Imaging, Hangzhou Medical College, Hangzhou, China.
⁵ Jing Hengyi School of Education, Hangzhou Normal University, Hangzhou, China.
⁶ Center for Rehabilitation Medicine, Department of Geriatric VIP No. 3, Department of Clinical Psychology, Zhejiang Provincial People's Hospital, Hangzhou, China.
⁷ Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.

Abstract

Background: Textural features of the hippocampus in structural magnetic resonance imaging (sMRI) images can serve as potential diagnostic biomarkers for Alzheimer's disease (AD), while exhibiting a relatively poor discriminant performance in detecting early AD, such as amnestic mild cognitive impairment (aMCI). In contrast to sMRI, functional magnetic resonance imaging (fMRI) can identify brain functional abnormalities in the early stages of cerebral disorders. However, whether the textural features reflecting local functional activity in the hippocampus can improve the diagnostic performance for AD and aMCI remains unclear. In this study, we combined the textural features of the amplitude of low frequency fluctuation (ALFF) in the slow-5 frequency band and structural images in the hippocampus to investigate their diagnostic performance for AD and aMCI using multimodal radiomics technique.

Methods: Totally, 84 AD, 50 aMCI, and 44 normal controls (NCs) were included in the current study. After feature extraction and feature selection, the radiomics models incorporating sMRI images, ALFF values and their combinations in the bilateral hippocampus were established for the diagnosis of AD and aMCI. The effectiveness of these models was evaluated by receiver operating characteristic (ROC) analysis. The radiomics models were further validated using the external data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

Results: The results of ROC analysis showed that the radiomics models based on structural images in the hippocampus had a better diagnostic performance for AD compared with the models using ALFF, while the ALFF-based model exhibited better discriminant performance for aMCI than the models with structural images. The radiomics models based on the combinations of structural images and ALFF were found to exhibit the highest accuracy for distinguishing AD from NCs and aMCI from NCs.

Conclusion: In this study, we found that the textural features reflecting local functional activity could improve the diagnostic performance of traditional structural models for both AD and aMCI. These findings may deepen our understanding of the pathogenesis of AD, contributing to the early diagnosis of AD.

Keywords: Alzheimer’s disease; amnestic mild cognitive impairment; radiomics; resting-state functional magnetic resonance imaging; the amplitude of low frequency fluctuation.