PLoS ONE (Jan 2020)

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,
  • 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,
  • HepaT1ca Study Group

DOI
https://doi.org/10.1371/journal.pone.0238568
Journal volume & issue
Vol. 15, no. 12
p. e0238568

Abstract

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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.