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Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472457/
https://www.ncbi.nlm.nih.gov/pubmed/34573869
http://dx.doi.org/10.3390/diagnostics11091527
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author 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
author_facet 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
author_sort Felli, Eric
collection PubMed
description 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.
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spelling pubmed-84724572021-09-28 Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging 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 Diagnostics (Basel) Article 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. MDPI 2021-08-24 /pmc/articles/PMC8472457/ /pubmed/34573869 http://dx.doi.org/10.3390/diagnostics11091527 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
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
Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title_full Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title_fullStr Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title_full_unstemmed Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title_short Automatic Liver Viability Scoring with Deep Learning and Hyperspectral Imaging
title_sort automatic liver viability scoring with deep learning and hyperspectral imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472457/
https://www.ncbi.nlm.nih.gov/pubmed/34573869
http://dx.doi.org/10.3390/diagnostics11091527
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