Felli, Eric; Al-Taher, Mahdi; Collins, Toby; Nkusi, Richard; Felli, Emanuele; Baiocchini, Andrea; Lindner, Veronique; Vincent, Cindy; Barberio, Manuel; Geny, Bernard; Ettorre, Giuseppe Maria; Hostettler, Alexandre; Mutter, Didier; Gioux, Sylvain; Schuster, Catherine; Marescaux, Jacques; Gracia-Sancho, Jordi; Diana, Michele (2021). Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging. Diagnostics, 11(9) MDPI 10.3390/diagnostics11091527
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Hyperspectral imaging (HSI) is a non-invasive imaging modality already applied to evaluate hepatic oxygenation and to discriminate different models of hepatic ischemia. Nevertheless, the ability of HSI to detect and predict the reperfusion damage intraoperatively was not yet assessed. Hypoxia caused by hepatic artery occlusion (HAO) in the liver brings about dreadful vascular complications known as ischemia-reperfusion injury (IRI). Here, we show the evaluation of liver viability in an HAO model with an artificial intelligence-based analysis of HSI. We have combined the potential of HSI to extract quantitative optical tissue properties with a deep learning-based model using convolutional neural networks. The artificial intelligence (AI) score of liver viability showed a significant correlation with capillary lactate from the liver surface (r = -0.78, p = 0.0320) and Suzuki's score (r = -0.96, p = 0.0012). CD31 immunostaining confirmed the microvascular damage accordingly with the AI score. Our results ultimately show the potential of an HSI-AI-based analysis to predict liver viability, thereby prompting for intraoperative tool development to explore its application in a clinical setting.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Hepatologie 04 Faculty of Medicine > Pre-clinic Human Medicine > BioMedical Research (DBMR) > DBMR Forschung Mu35 > Forschungsgruppe Hepatologie |
UniBE Contributor: |
Felli, Eric, Gracia Sancho, Jorge Sergio |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
2075-4418 |
Publisher: |
MDPI |
Language: |
English |
Submitter: |
Rahel Fuhrer |
Date Deposited: |
27 Oct 2021 08:01 |
Last Modified: |
03 Apr 2024 05:13 |
Publisher DOI: |
10.3390/diagnostics11091527 |
PubMed ID: |
34573869 |
Uncontrolled Keywords: |
CNNs artificial intelligence convolutional networks deep learning hepatic artery occlusion hyperspectral imaging liver viability |
BORIS DOI: |
10.48350/160346 |
URI: |
https://boris.unibe.ch/id/eprint/160346 |
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