Radiation Oncologist Speaks to AI Potential in the Cancer Space

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Richard Bakst, MD, speaks to the potential use of artificial intelligence in the radiation oncology space, and how he hopes to see it evolve.

In the field of radiation oncology, artificial intelligence (AI) has emerged as a transformative force, that can help to redefine diagnostic and therapeutic approaches. In an interview with CancerNetwork®, Richard Bakst, MD, discussed the impact of AI in radiology, and how it has the potential to enhance patient care and medical practices.

Bakst, a radiation oncologist at Mount Sinai, highlighted AI's influence in diagnostic radiology, particularly in screening for lung cancer and assisting in demographic interpretations. He also mentioned AI's budding role in therapeutic radiology; its ability to detect microscopic disease on imaging scans and assist in contouring normal structures shows promise for optimizing treatment planning.

Looking toward the future, Bakst believes AI will become a valuable tool in radiotherapy, influencing volume design, assessing the risk of microscopic disease, and aiding in tumor volume elimination. This integration of AI is expected to significantly enhance the precision and effectiveness of cancer treatment.

With AI's ability to detect subtle abnormalities, optimize treatment planning, and enhance targeting precision, it is poised to influence the radiology space.

Transcript:

[AI] is taking a role in all spaces. It has a huge footprint in diagnostic radiology, screening for lung cancer, and assisting in demographic reads; [it has] a very strong foothold in the diagnostic space. It’s going to make its way into therapy space, and it already has in some instances in terms of our workflow. We have the ability to use AI to detect microscopic disease on our scans. [This helps] think about contouring normal structures. It will penetrate the therapeutic planning for radiotherapy. Definitely in the very short term, hopefully it will influence our volume design, assess the risk of microscopic disease, and help eliminate tumor volumes. It’s coming. It will enhance our ability to target cancer, risk stratify patients, and determine appropriate volumes.

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