Characterising Effective Connectivity Changes in Patients with Hepatic Encephalopathy after Liver Transplantation: A Spectral Dynamic Casual Modeling Study
Pages 74 - 79
Abstract
Objective: The exact effect of overt hepatic encephalopathy (OHE) on the neural processes involved in cognitive enhancement after liver transplantation (LT) is not currently known and requires additional study. The study aims to probe into whether the causal influences within the default mode network (DMN) are altered in OHE patients after LT using resting state functional MRI (rs-fMRI) data.
Materials and Methods: In this study, a total of 21 cirrhotic patients with OHE were included. Each patient underwent rs-fMRI scans both prior to and one month post LT. Four regions of the DMN (medial frontal cortex (MFC), posterior cingulate cortex (PCC), left parietal cortex (LPC), and right parietal cortex (RPC)) were defined for each patient using a group independent component analysis (ICA) approach. Spectral dynamic causal modeling (DCM) was employed to estimate the coupling parameters. The coupling parameters provide insights into the directional and strength of the interconnections between the DMN regions, which represent the causal interactivities among the regions.
Results: After one month of LT, the influences from the PCC to RPC, RPC to PCC and from LPC to MFC are markedly reduced.
Conclusion: The findings indicate that the disrupted causal influences including RPC exerts on PCC, PCC exerts on RPC and LPC exerts on MFC are responsive for cirrhotic patients with OHE to operate LT. And these changes in the effective connectivity have the potential to be utilized as neuroimaging biomarkers, aiding in the assessment of cognitive function restoration post LT in patients with liver cirrhosis.
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Index Terms
- Characterising Effective Connectivity Changes in Patients with Hepatic Encephalopathy after Liver Transplantation: A Spectral Dynamic Casual Modeling Study
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October 2023
1394 pages
ISBN:9798400708138
DOI:10.1145/3644116
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Published: 05 April 2024
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ISAIMS 2023: 2023 4th International Symposium on Artificial Intelligence for Medicine Science
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