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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer

The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individ...

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Autores principales: Mole, Damian J., Fallowfield, Jonathan A., Sherif, Ahmed E., Kendall, Timothy, Semple, Scott, Kelly, Matt, Ridgway, Gerard, Connell, John J., McGonigle, John, Banerjee, Rajarshi, Brady, J. Michael, Zheng, Xiaozhong, Hughes, Michael, Neyton, Lucile, McClintock, Joanne, Tucker, Garry, Nailon, Hilary, Patel, Dilip, Wackett, Anthony, Steven, Michelle, Welsh, Fenella, Rees, Myrddin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710097/
https://www.ncbi.nlm.nih.gov/pubmed/33264327
http://dx.doi.org/10.1371/journal.pone.0238568
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author Mole, Damian J.
Fallowfield, Jonathan A.
Sherif, Ahmed E.
Kendall, Timothy
Semple, Scott
Kelly, Matt
Ridgway, Gerard
Connell, John J.
McGonigle, John
Banerjee, Rajarshi
Brady, J. Michael
Zheng, Xiaozhong
Hughes, Michael
Neyton, Lucile
McClintock, Joanne
Tucker, Garry
Nailon, Hilary
Patel, Dilip
Wackett, Anthony
Steven, Michelle
Welsh, Fenella
Rees, Myrddin
author_facet Mole, Damian J.
Fallowfield, Jonathan A.
Sherif, Ahmed E.
Kendall, Timothy
Semple, Scott
Kelly, Matt
Ridgway, Gerard
Connell, John J.
McGonigle, John
Banerjee, Rajarshi
Brady, J. Michael
Zheng, Xiaozhong
Hughes, Michael
Neyton, Lucile
McClintock, Joanne
Tucker, Garry
Nailon, Hilary
Patel, Dilip
Wackett, Anthony
Steven, Michelle
Welsh, Fenella
Rees, Myrddin
author_sort Mole, Damian J.
collection PubMed
description The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individual patients are at greatest risk of poor post-operative liver performance remains a challenge. Here we report results from a multicentre observational clinical trial (ClinicalTrials.gov NCT03213314) which aimed to inform personalised pre-operative risk assessment in liver cancer surgery by evaluating liver health using quantitative multiparametric magnetic resonance imaging (MRI). We combined estimation of future liver remnant (FLR) volume with corrected T1 (cT1) of the liver parenchyma as a representation of liver health in 143 patients prior to treatment. Patients with an elevated preoperative liver cT1, indicative of fibroinflammation, had a longer post-operative hospital stay compared to those with a cT1 within the normal range (6.5 vs 5 days; p = 0.0053). A composite score combining FLR and cT1 predicted poor liver performance in the 5 days immediately following surgery (AUROC = 0.78). Furthermore, this composite score correlated with the regenerative performance of the liver in the 3 months following resection. This study highlights the utility of quantitative MRI for identifying patients at increased risk of poor post-operative liver performance and a longer stay in hospital. This approach has the potential to inform the assessment of individualised patient risk as part of the clinical decision-making process for liver cancer surgery.
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spelling pubmed-77100972020-12-03 Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer Mole, Damian J. Fallowfield, Jonathan A. Sherif, Ahmed E. Kendall, Timothy Semple, Scott Kelly, Matt Ridgway, Gerard Connell, John J. McGonigle, John Banerjee, Rajarshi Brady, J. Michael Zheng, Xiaozhong Hughes, Michael Neyton, Lucile McClintock, Joanne Tucker, Garry Nailon, Hilary Patel, Dilip Wackett, Anthony Steven, Michelle Welsh, Fenella Rees, Myrddin PLoS One Research Article The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individual patients are at greatest risk of poor post-operative liver performance remains a challenge. Here we report results from a multicentre observational clinical trial (ClinicalTrials.gov NCT03213314) which aimed to inform personalised pre-operative risk assessment in liver cancer surgery by evaluating liver health using quantitative multiparametric magnetic resonance imaging (MRI). We combined estimation of future liver remnant (FLR) volume with corrected T1 (cT1) of the liver parenchyma as a representation of liver health in 143 patients prior to treatment. Patients with an elevated preoperative liver cT1, indicative of fibroinflammation, had a longer post-operative hospital stay compared to those with a cT1 within the normal range (6.5 vs 5 days; p = 0.0053). A composite score combining FLR and cT1 predicted poor liver performance in the 5 days immediately following surgery (AUROC = 0.78). Furthermore, this composite score correlated with the regenerative performance of the liver in the 3 months following resection. This study highlights the utility of quantitative MRI for identifying patients at increased risk of poor post-operative liver performance and a longer stay in hospital. This approach has the potential to inform the assessment of individualised patient risk as part of the clinical decision-making process for liver cancer surgery. Public Library of Science 2020-12-02 /pmc/articles/PMC7710097/ /pubmed/33264327 http://dx.doi.org/10.1371/journal.pone.0238568 Text en © 2020 Mole et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mole, Damian J.
Fallowfield, Jonathan A.
Sherif, Ahmed E.
Kendall, Timothy
Semple, Scott
Kelly, Matt
Ridgway, Gerard
Connell, John J.
McGonigle, John
Banerjee, Rajarshi
Brady, J. Michael
Zheng, Xiaozhong
Hughes, Michael
Neyton, Lucile
McClintock, Joanne
Tucker, Garry
Nailon, Hilary
Patel, Dilip
Wackett, Anthony
Steven, Michelle
Welsh, Fenella
Rees, Myrddin
Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title_full Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title_fullStr Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title_full_unstemmed Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title_short Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
title_sort quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710097/
https://www.ncbi.nlm.nih.gov/pubmed/33264327
http://dx.doi.org/10.1371/journal.pone.0238568
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