Using AI in Tumor Assessment

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A new Friends of Cancer Research white paper, “Leveraging AI-Enabled Tumor Assessment Tools on Radiological Images to Evaluate Treatment Effect and Support Clinical Trial Endpoints in Solid Tumors,” presents findings from a multi-stakeholder working group it convened to evaluate the current landscape of artificial intelligence (AI)-enabled tumor assessment tools and propose a stepwise roadmap for integration into clinical trials. The white paper outlines:

  • limitations of current imaging-based endpoints and opportunities to improve upon the Response Evaluation Criteria in Solid Tumors (RECIST);
  • emerging AI-driven approaches, including enhanced RECIST, radiomics, volumetric analysis, and growth kinetics; and
  • necessary components of a framework to validate a novel AI-imaging-based endpoint as an early endpoint, including outstanding questions for defining the endpoint and considerations for a meta-analysis.

“By advancing and aligning on methodological standards,” the paper says, “the oncology community can enable AI-enabled tumor assessments to supplement, and in some cases surpass, traditional measurement approaches in clinical trials. This shift has the potential to improve endpoint precision, reduce trial timelines and costs, and ultimately accelerate patient access to safe and effective therapies.”

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