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Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
- Damian J. Mole,
-
Jonathan A. Fallowfield,
Roles Conceptualization, Investigation, Writing – review & editing
Affiliation Centre for Inflammation Research, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, United Kingdom
⨯ -
Ahmed E. Sherif,
Roles Formal analysis, Investigation
Affiliations Clinical Surgery, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh, United Kingdom, Department of HPB Surgery, National Liver Institute, Menoufia University, Shibin Elkom, Egypt
⨯ - Timothy Kendall,
- Scott Semple,
-
Matt Kelly,
Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Writing – review & editing
Affiliation Perspectum, Gemini One, Oxford, United Kingdom
⨯ - Gerard Ridgway,
-
John J. Connell ,
Roles Conceptualization, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing
* E-mail: john.connell@perspectum.com
Affiliation Perspectum, Gemini One, Oxford, United Kingdom
⨯ - John McGonigle,
- Rajarshi Banerjee,
- J. Michael Brady,
- Xiaozhong Zheng,
- Michael Hughes,
- Lucile Neyton,
- Joanne McClintock,
- Garry Tucker,
- Hilary Nailon,
- Dilip Patel,
- Anthony Wackett,
- Michelle Steven,
- Fenella Welsh,
- Myrddin Rees,
- [ ... ],
- the HepaT1ca Study Group
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https://orcid.org/0000-0002-5741-1471
Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer
- Damian J. Mole,
- Jonathan A. Fallowfield,
- Ahmed E. Sherif,
- Timothy Kendall,
- Scott Semple,
- Matt Kelly,
- Gerard Ridgway,
- John J. Connell,
- John McGonigle,
- Rajarshi Banerjee
- Published: December 2, 2020
- https://doi.org/10.1371/journal.pone.0238568