Join our Whatsapp channel

       A Chinese research team has developed an artificial intelligence (AI) tool that predicts liver cancer recurrence risk with 82.2 per cent accuracy, according to a study recently published in the journal Nature.

       Liver cancer, the third leading cause of cancer-related deaths worldwide, has a postoperative recurrence rate as high as 70pc. Accurately predicting recurrence was a critical challenge.

       Researchers from the University of Science and Technology of China, led by Sun Cheng, have developed a scoring system named TIMES, which quantifies spatial distribution patterns of immune cells within the tumour microenvironment to assess relapse likelihood.

       Advertisements

       Video Player is loading.

       Play Video Pause Loaded: 4.61%

       0:00

       Remaining Time - -:-

       Unmute

       Fullscreen

       This is a modal window.

       The media could not be loaded, either because the server or network failed or because the format is not supported.

       Beginning of dialog window. Escape will cancel and close the window.

       Text Color WhiteBlackRedGreenBlueYellowMagentaCyan TransparencyOpaqueSemi-Transparent Background Color BlackWhiteRedGreenBlueYellowMagentaCyan TransparencyOpaqueSemi-TransparentTransparent Window Color BlackWhiteRedGreenBlueYellowMagentaCyan TransparencyTransparentSemi-TransparentOpaque

       Font Size 50%75%100%125%150%175%200%300%400% Text Edge Style NoneRaisedDepressedUniformDropshadow Font Family Proportional Sans-SerifMonospace Sans-SerifProportional SerifMonospace SerifCasualScriptSmall Caps

       Reset restore all settings to the default values Done

       Close Modal Dialog End of dialog window.

       X

       The system is the world’s first liver cancer recurrence prediction tool integrating spatial immune data. The study demonstrated that immune cell spatial organisation, not just their quantity, determines clinical outcomes.

       By combining spatial transcriptomics, proteomics, multispectral immunohistochemistry, and AI-driven spatial analysis, the team established a novel method for tumour microenvironment assessment.

       The system was trained using liver cancer tissue samples from 61 patients. The researchers opened a free online version of TIMES, allowing global users to upload pathological staining images for instant risk evaluation.

       The team aims to provide a revolutionary decision-making tool to help doctors optimise personalised treatments, especially in resource-limited settings, Sun said, adding that they are actively collaborating with industry partners to standardise clinical applications.

       Published in Dawn, March 17th, 2025