AI tool for predicting liver cancer recurrence developed by Chinese scientists
A research team from China has created an AI tool that predicts the risk of liver cancer recurrence with an accuracy of 82.2 percent, as reported in a recent study published in the journal Nature. Liver cancer ranks as the third leading cause...
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A research team from China has created an AI tool that predicts the risk of liver cancer recurrence with an accuracy of 82.2 percent, as reported in a recent study published in the journal Nature.
Liver cancer ranks as the third leading cause of cancer-related deaths globally, with a postoperative recurrence rate reaching as high as 70 percent. Accurately forecasting recurrence has posed a significant challenge.
The team, led by Sun Cheng from the University of Science and Technology of China, has developed a scoring system called TIMES. This tool quantifies the spatial distribution patterns of immune cells within the tumor microenvironment to evaluate the likelihood of relapse. Notably, it is the first tool of its kind in the world to incorporate spatial immune data for predicting liver cancer recurrence.
The research revealed that the spatial organization of immune cells, as opposed to their mere numbers, plays a crucial role in determining clinical outcomes. By integrating spatial transcriptomics, proteomics, multispectral immunohistochemistry, and AI-driven spatial analysis, the researchers established an innovative method for assessing the tumor microenvironment. The tool was trained using tissue samples from 61 liver cancer patients.
Additionally, the researchers have made a free online version of TIMES accessible, enabling users worldwide to upload pathological staining images for immediate risk assessment.
Sun emphasized the goal of providing a groundbreaking decision-making tool that assists doctors in optimizing personalized treatments, especially in resource-limited environments. He also mentioned that the team is actively working with industry partners to standardize clinical applications.
Debra A Smith for TROIB News
Liver cancer ranks as the third leading cause of cancer-related deaths globally, with a postoperative recurrence rate reaching as high as 70 percent. Accurately forecasting recurrence has posed a significant challenge.
The team, led by Sun Cheng from the University of Science and Technology of China, has developed a scoring system called TIMES. This tool quantifies the spatial distribution patterns of immune cells within the tumor microenvironment to evaluate the likelihood of relapse. Notably, it is the first tool of its kind in the world to incorporate spatial immune data for predicting liver cancer recurrence.
The research revealed that the spatial organization of immune cells, as opposed to their mere numbers, plays a crucial role in determining clinical outcomes. By integrating spatial transcriptomics, proteomics, multispectral immunohistochemistry, and AI-driven spatial analysis, the researchers established an innovative method for assessing the tumor microenvironment. The tool was trained using tissue samples from 61 liver cancer patients.
Additionally, the researchers have made a free online version of TIMES accessible, enabling users worldwide to upload pathological staining images for immediate risk assessment.
Sun emphasized the goal of providing a groundbreaking decision-making tool that assists doctors in optimizing personalized treatments, especially in resource-limited environments. He also mentioned that the team is actively working with industry partners to standardize clinical applications.
Debra A Smith for TROIB News
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