Investigation of cerebral cortical morphological similarity and network topological abnormalities in hepatic encephalopathy utilizing a morphometric inverse divergence network framework - Takeaways - MDSpire

Investigation of cerebral cortical morphological similarity and network topological abnormalities in hepatic encephalopathy utilizing a morphometric inverse divergence network framework

  • By

  • Chengkun Hong

  • Taipeng Zeng

  • Xiaoyang Wang

  • Li Chen

  • Minghui Mao

  • Hao Huang

  • Jianfeng Chu

  • Liyuan Fu

  • July 6, 2026

  • 0 min

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  • 1

    This study integrates the Morphometric Inverse Divergence (MIND) network with graph theory to analyze hepatic encephalopathy (HE) and related conditions.

  • 2

    A total of 31 HE patients, 30 cirrhotic non-HE patients, and 30 healthy controls underwent 3D-T1WI MRI scanning for cortical feature extraction.

  • 3

    HE patients showed significantly increased mean MIND values across various functional subnetworks compared to healthy controls.

  • 4

    Graph theoretical analysis indicated enhanced global and local efficiency in HE patients, while NHE patients exhibited mild connectivity enhancements.

  • 5

    The MIND network indices may serve as potential imaging biomarkers for diagnosing and monitoring hepatic encephalopathy.

Original Source(s)

Investigation of cerebral cortical morphological similarity and network topological abnormalities in hepatic encephalopathy utilizing a morphometric inverse divergence network framework

  • by Chengkun Hong, Taipeng Zeng, Xiaoyang Wang, Li Chen, Minghui Mao, Hao Huang, Jianfeng Chu, Liyuan Fu

  • July 6, 2026

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