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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7710097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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