Identification of discriminative neuroimaging markers for patients on hemodialysis with insomnia: a fractional amplitude of low frequency fluctuation-based machine learning analysis

BMC Psychiatry

Research

Yue Zhang¹  Yu-chi Wu²  Qi-zhan Lin²  Kan Deng³  Meng-han Feng⁴  Cheng-wei Fu⁵  Ze-ying Wen⁶  Bo Liu⁷ 

[1] Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;Hemodialysis Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;Philips Healthcare, 510120, Guangzhou, China;R&D Support Group, Xin-Huangpu Joint Innovation Institute of Chinese Medicine in Guangdong Province, 510700, Guangzhou, China;The Second Clinical College, Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;The Second Clinical College, Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;Department of Radiology, The First Affiliated Hospital of Henan University of Chinese Medicine, 450000, Zhengzhou, China;The Second Clinical College, Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, 510120, Guangzhou, China;

关键词: Hemodialysis;    Insomnia;    Amplitude of low frequency fluctuation;    Support vector machine (SVM);    Neural markers;   

DOI  :  10.1186/s12888-022-04490-1

 received in 2022-09-17, accepted in 2022-12-21,  发布年份 2022

来源: Springer

【 摘 要 】

Background and objectiveInsomnia is one of the common problems encountered in the hemodialysis (HD) population, but the mechanisms remain unclear. we aimed to (1) detect the spontaneous brain activity pattern in HD patients with insomnia (HDWI) by using fractional fractional amplitude of low frequency fluctuation (fALFF) method and (2) further identify brain regions showing altered fALFF as neural markers to discriminate HDWI patients from those on hemodialysis but without insomnia (HDWoI) and healthy controls (HCs).MethodWe compared fALFF differences among HDWI subjects (28), HDWoI subjects (28) and HCs (28), and extracted altered fALFF features for the subsequent discriminative analysis. Then, we constructed a support vector machine (SVM) classifier to identify distinct neuroimaging markers for HDWI.ResultsCompared with HCs, both HDWI and HDWoI patients exhibited significantly decreased fALFF in the bilateral calcarine (CAL), right middle occipital gyrus (MOG), left precentral gyrus (PreCG), bilateral postcentral gyrus (PoCG) and bilateral temporal middle gyrus (TMG), whereas increased fALFF in the bilateral cerebellum and right insula. Conversely, increased fALFF in the bilateral CAL/right MOG and decreased fALFF in the right cerebellum was observed in HDWI patients when compared with HDWoI patients. Moreover, the SVM classification achieved a good performance [accuracy = 82.14%, area under the curve (AUC) = 0.8202], and the consensus brain regions with the highest contributions to classification were located in the right MOG and right cerebellum.ConclusionOur result highlights that HDWI patients had abnormal neural activities in the right MOG and right cerebellum, which might be potential neural markers for distinguishing HDWI patients from non-insomniacs, providing further support for the pathological mechanism of HDWI.

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

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