Hepatica - Quantitative MRI Predicts Individual Future Liver Performance After Liver Resection скачать в хорошем качестве

Hepatica - Quantitative MRI Predicts Individual Future Liver Performance After Liver Resection

Presented at IHPBA 2020 27th November - Best of the Best Oral Presentation Background and Aims: The future liver performance [FLP] of an individual undergoing surgical liver resection to remove cancer is critical for their survival and recovery. We report the development and clinical testing of a novel magnetic resonance image [MRI] post-processing software that combines multiparametric MRI signal processing with automated anatomical liver segmentation to estimate FLP. This is intended to inform the assessment of individualised operative risk and augment patient and surgeon decision making prior to liver resection. Method: This software combines iron-corrected T1 [cT1] mapping, previously demonstrated to correlate with fibroinflammation and predict clinical outcomes in chronic liver disease, with a 3D U-net pipeline to automatically delineate the liver volume prior to Couinaud segments based on anatomical landmarks. Interactive removal of these segments, combined with virtual wedge resections allows accurate estimation of the future liver remnant [FLR] volume, which when combined with quantitative cT1 mapping, provides a prediction of FLP, termed the “HepaT1ca score”. The ability of this score to predict post-operative morbidity, length of stay and regenerative capacity was evaluated in a prospective clinical trial [ClinicalTrials.gov NCT03213314]. Results: Of the 143 patients recruited, 135 underwent liver resection. 84% of participants had liver metastases from colorectal cancer, with the remaining having primary liver cancer or other secondary cancers. 21% of participants had cT1 values above the upper limit of normal [795ms] indicating increased risk of background liver disease. The HepaT1ca score showed a significant linear correlation with the modified Hyder-Pawlik score, an indicator of post-operative morbidity [adjusted R2 = 0.26, P = 0.001], and liver regenerative performance [adjusted R2 = 0.46, P = 0.001]. Furthermore, in patients with an FLR below 90%, a high mean cT1 [795ms] was associated with a longer duration of hospital stay [median [IQR] of 6.5 [5.3-12] vs. 5 [4-7.1]; P = 0.0053]. cT1 also correlated with histological measures of inflammation and ballooning. Conclusion: We demonstrate the utility of a non-invasive quantitative MRI approach for predicting post-operative liver performance. This has the potential to transform surgical decision-making and augment individualised risk assessment for patients undergoing liver resection for cancer.