Current strategies for predicting post-hepatectomy liver failure and a new ultrasound-based nomogram

Abstract

Liver cancer is associated with a few factors, such as viruses and alcohol consumption, and hepatectomy is an important treatment for patients with liver cancer. However, post-hepatectomy liver failure (PHLF) is the most serious complication and has a high mortality rate. Effective prediction of PHLF allows for the adjustment of clinical treatment strategies and is critical to the long-term prognosis of patients. Many factors have been associated with the development of PHLF, so there is an increasing interest in the development of predictive models for PHLF, such as nomograms that integrate intra-operative factors, imaging and biochemical characteristics of the patient. Ultrasound, as a simple and important examination method, plays an important role in predicting PHLF, especially the Nomogram established based on ultrasound measurements of liver stiffness and spleen area provides a more convenient way to predict the occurrence of PHLF.

Keywords: Ultrasound; Liver stiffness; Spleen area; Hepatocellular carcinoma; Post-hepatectomy liver failure

Core Tip: Existing strategies for predicting post-hepatectomy liver failure include multiple clinical scoring systems that assess surgical risk by quantifying metrics related to liver function. However, each has limitations such as high subjectivity and insufficient prediction accuracy. Ultrasound-based nomograms are innovative predictive methods that combine radiomic features with clinical risk factors and construct a model through multivariate logistic regression to achieve prediction of post-hepatectomy liver failure. This method is non-invasive, low cost and high precision, and is expected to provide clinicians with a more reliable prediction tool, assisting doctors in formulating optimal surgical and therapeutic plans.