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AI can identify aggressive prostate cancer lesions; community engagement in genomics research; questionnaires can improve spine MRI diagnosis – Morning Medical Update

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  • An AI model can identify aggressive prostate cancer lesions, aiding in precision medicine by estimating tumor volume and associated risks.
  • A workshop focused on sustaining community engagement in genomics research, addressing trust issues due to unethical practices and discrimination.
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© Alena Kryazheva - stock.adobe.com

© Alena Kryazheva - stock.adobe.com

AI model can identify aggressive prostate cancer lesions

Prostate cancer is the second most common form of cancer in male patients. Mass General Brigham researchers trained an AI model to assist in diagnosis, which can help clinicians make more informed treatment decisions. According to the report, the AI model successfully identified and demarcated the edges of 85% of the most radiologically aggressive prostate lesions, and correctly estimated that tumors with larger volumes were associated with a higher risk of treatment failure and metastasis.

“AI-determined tumor volume has the potential to advance precision medicine for patients with prostate cancer by improving our ability to understand the aggressiveness of a patient’s cancer and therefore recommended the most optimal treatment,” David D. Yang, M.D., first author of the Department of Radiation Oncology at Brigham and Women’s Hospital, and a founding member of the Mass General Brigham healthcare system, said in a news release.

Workshop explores challenge of sustaining community engagement in genomics research

A long history of unethical practices, including systemic racism and structural discrimination, have undermined trust in genomics research, especially among underrepresented populations. The National Academies Roundtable on Genomics and Precision Health held a workshop in July 2024, focused on establishing and sustaining long-term community engagement in genomics research. Find the proceedings from that workshop, in brief.

Spine MRI diagnosis improved with knowledge of patient’s symptoms

Access to patient questionnaires can assist radiologists in lumbar spine MRI interpretation and diagnosis, a new study says. In the study, published in Radiology, radiologists were able to achieve nearly perfect diagnostic agreement with clinical experts thanks to access to patient-reported symptom information.

“MRI exams of the lumbar spine often show many degenerative abnormalities. Most of these are incidental findings that do not cause pain,” William E. Palmer, M.D., study author and division chief of Musculoskeletal Radiology at Massachusetts General Hospital, said in a news release. “To diagnose the true pain generators and make the best treatment decisions, symptoms must be matched with MRI abnormalities.”

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© Mathematica - The Commonwealth Fund
© Mathematica - The Commonwealth Fund