Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage

Brain Informatics

Research

Ruizhe Zheng¹  Ying Mao¹  Zhe Wang¹  Di Zang¹  Zeyu Xu¹  Xuehai Wu¹  Zengxin Qi¹  Jiayu Huo²  Xiangyu Zhao²  Lichi Zhang²  Yuanfang Qiao² 

[1] Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 200040, Shanghai, China;National Center for Neurological Disorders, 200040, Shanghai, China;Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 200040, Shanghai, China;Neurosurgical Institute of Fudan University, 200040, Shanghai, China;Shanghai Clinical Medical Center of Neurosurgery, 200040, Shanghai, China;State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, 200040, Shanghai, China;School of Biomedical Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China;

关键词: Structural imaging;    Brain parcellation;    Hydrocephalus;    Traumatic brain injury;    Consciousness;   

DOI  :  10.1186/s40708-022-00181-5

 received in 2022-10-24, accepted in 2022-12-01,  发布年份 2022

来源: Springer

【 摘 要 】

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient’s consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

【 授权许可】

CC BY   
© The Author(s) 2022

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