Abstract #0419

Topological properties of individual gray matter morphological network effectively identify the preclinical stages of Alzheimer’s disease

Zhihao Wang¹, Hongyuan Ding², Yin Tang³, Yao Tang^4,5, Ming Qi⁶, Weiqiang Dou⁷, Long Qian⁷, Yaxin Gao^8,9, Tong Wang¹⁰, Qian Zhong¹¹, Xi Yang¹⁰, Huifang Tian¹², Ling Zhang², and Yi Zhu¹⁰

¹School of Biological Science & Medical Engineering, Southeast University, Nanjing, China, ²Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, ³Department of Medical imaging, Jingjiang People's Hospital, Jingjiang, China, ⁴School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China, ⁵Rehabilitation Medicine Department, Geriatric Hospital of Nanjing Medical University, Nanjing, China, ⁶Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Naning, China, ⁷MR Research China, GE Healthcare, Beijing, China, ⁸Department of Rehabilitation, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China, ⁹Gusu School, Nanjing Medical University, Suzhou, China, ¹⁰Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, ¹¹Department of Rehabilitation, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China, ¹²Clinical Medicine Research Institution, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China

Synopsis

Keywords: Alzheimer's Disease, NeurodegenerationIn this study, the topology of normalized individual morphological network (IMN) has been investigated for patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI) and healthy controls (HCs), respectively. Significantly different topology has been revealed among SCD and MCI patients and HCs, both at global and regional level. Moreover, the alterations of the regional topological metrics, including degree centrality and nodal efficiency, at the caudate nucleus exhibited significant correlations with all clinical scales and statistically predicted the cognitive performances. Therefore, the alterations of IMN can be regarded as an effective biomarker in early detection of SCD and MCI.

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