AI automates radiation therapy planning: 5 notes

AI-powered, knowledge-based planning models can automate acceptable radiation care plans, saving physicians time and accelerating workflows, according to a study published Oct. 30 in Radiation & Oncology

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The care plans improved radiation therapy efficiency and lightened the workload for cancer treatment planners, according to a Dec. 30 news release from the National Cancer Institute. 

Here are five notes on the study:

  1. Researchers from Houston-based University of Texas MD Anderson Cancer Center worked with researchers from Stanford (Calif.) University, as well as institutions in the United Kingdom and South Africa, to create 10 knowledge-based planning models based on high-quality, clinical radiation treatment plans.
  2. The models were verified and validated using quantitative and qualitative analysis,  reviewed by physicians and rated for clinical acceptability, the study authors wrote.
  3. The models were designed for full automation, meaning no human intervention was needed for treatment plan generation.
  4. Treatment plans were automated for 10 cancer sites: anorectal, bladder, breast/chest wall, cervix, esophagus, head and neck, liver, lung/mediastinum, prostate, and prostate with nodes.
  5. Upon review, an average of 88% of the KBP-generated plans were “acceptable as is” and 98% were “acceptable after minor edits,” the study authors wrote. 

Access the full study here.

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