Prediction method for treatment effect of combination of anti-angiogenesis drug and immune checkpoint inhibitor

Abstract

The invention relates to a prediction method for a treatment effect of combination of an anti-angiogenesis drug and an immune checkpoint inhibitor. The method comprises the following steps: preparing curative effect evaluation data of a patient treated by an anti-angiogenesis drug combined immune checkpoint inhibitor; reading enhanced magnetic resonance imaging data of the patient before treatment by utilizing 3D medical image processing software, then carrying out focus range or focus area sketching on the same imaging data by a plurality of related doctors, and forming a plurality of feature sketching files by an enhanced magnetic resonance imaging sequence and sketching information of each doctor; respectively extracting image omics characteristic parameters of the focus from a plurality of sketching files by using a pyradiomics packet; screening a plurality of obtained radiomics characteristic parameter files to obtain effective characteristics, establishing a prediction model according to the screened characteristics, and training and verifying the prediction model for performing post-treatment curative effect prediction on a patient before treatment so as to assist clinical decision, screen effective crowds, improve the overall curative effect and relieve the economic burden of the patient, and avoid the adverse reaction.

Description

technical field [0001] The invention relates to an image analysis technology, in particular to a method for predicting therapeutic efficacy of anti-angiogenic drugs combined with immune checkpoint inhibitors. Background technique [0002] Taking liver cancer as an example, the current first-line anti-angiogenic drugs for the treatment of hepatocellular carcinoma include sorafenib, lenvatinib and donafenib, and the second-line anti-angiogenic drugs include regorafenib and apatinib . These five drugs are all multi-target tyrosine kinase inhibitors, and no effective predictive molecular markers have been found so far. [0003] Although immune checkpoint inhibitors have been used in the treatment of a variety of solid malignancies, their efficacy predictors vary, including programmed death ligand-1 (PD-L1) expression in tumor cells level, tumor mutation burden (tumor mutation burden, TMB), combined positive score (combined positive score, CPS) and microsatellite instability (M...

AI Technical Summary

Problems solved by technology

[0006]Aiming at the difficulty of predicting the curative effect of the disease, a method for predicting the curative effect of anti-angiogenic drugs combined with immune checkpoint inhibitors was proposed. Enhancing Magnetic Resonance Imaging Data to Develop a Computational Method to Predict the Response to Antiangiogenic Drug Combination Immune Checkpoint Inhibitor Therapy