MRI-based tool informs surgeons on previously undiagnosed background liver disease

A study published in PLOS ONE on patients with primary and secondary liver cancer shows how Perspectum’s non-invasive MRI technology Hepatica can help predict those at increased risk of poor surgical outcomes.

Hepatica integrates into routine pre-operative MRI assessment and combines pre-surgical measurements of liver health with AI-driven liver volumetry, providing actionable information to inform surgical decision-making and improve patient care. It helps surgeons identify and characterise previously undiagnosed background liver disease.

The non-invasive MRI-based tool combines LiverMultiScan cT1 (corrected T1) and PDFF, respective measures of liver fibro-inflammation and fat, with future liver remnant (FLR) volume to evaluate an individual’s risk of having a poor post-operative outcome. In a study by Jayaswal et al (2020), LiverMultiScan was shown to be the best predictor of outcomes in chronic liver disease patients.

In the current, prospective, observational study of 143 patients being considered for liver cancer surgery, elevated cT1 corresponded to a longer post-operative stay in hospital, with the combination of cT1 and FLR predicting poor liver performance in the five days immediately following surgery, and correlating with liver regenerative performance in the three months following surgery.

Lead author Professor Damian Mole, professor of clinical and experimental surgery and honorary consultant surgeon at the University of Edinburgh, said: “As surgeons, we are constantly trying to make operations safer and have improved outcomes for patients. Operating on the liver to remove cancer can give patients with advanced cancer a chance of a cure. Hepatica allows us to make better informed decisions about the extent of safe surgery. This allows patients and the surgical team to approach the challenge with more information about their future liver performance.”

Picture: Hepatica provides AI-driven liver volumetry.

Published on page 20 of the January 2021 issue of RAD Magazine.

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