AI Tool Predicts Colon Cancer Survival, Treatment Response

Model offers actionable insights for physicians, could augment clinical decisions in resource-limited areas

Rendering of a human silhouette in blue and intestines in red
Image: Mohammed Haneefa Nizamudeen/iStock/Getty Images Plus

At a glance:

  • New AI tool accurately predicts both overall survival and disease-free survival after colorectal cancer diagnosis.
  • The model uses visual markers on pathology images to glean insights into a tumor’s genomic profile and predicts tumor behavior, disease progression, treatment response.
  • The new model could help augment clinical decision-making.
  • Because the AI tool relies on images alone, it could be particularly valuable for hospitals lacking the technology or expertise to perform sophisticated genomic profiling of tumor tissues.

A new artificial intelligence model designed by researchers at Harvard Medical School and National Cheng Kung University in Taiwan could bring much-needed clarity to doctors delivering prognoses and deciding on treatments for patients with colorectal cancer, the second deadliest cancer worldwide.

Solely by looking at images of tumor samples — microscopic depictions of cancer cells — the new tool accurately predicts how aggressive a colorectal tumor is, how likely the patient is to survive with and without disease recurrence, and what the optimal therapy might be for them.

Having a tool that answers such questions could help clinicians and patients navigate this wily disease, which often behaves differently even among people with similar disease profiles who receive the same treatment — and could ultimately spare some of the 1 million lives that colorectal cancer claims every year.

A report on the team’s work is published in Nature Communications.

The researchers say that the tool is meant to enhance, not replace, human expertise.

“Our model performs tasks that human pathologists cannot do based on image viewing alone,” said study co-senior author Kun-Hsing Yu, assistant professor of biomedical informatics in the Blavatnik Institute at HMS. Yu led an international team of pathologists, oncologists, biomedical informaticians, and computer scientists.

Read full article in HMS News

Also see

Harvard Team Uses Bridges-2 to Build AI Cancer Diagnosis Tool  | Pittsburgh Supercomputing Center