Lung cancer is the most common cause of cancer death and the second most common type of cancer in the world. Researchers from Brigham and Women’s Hospital have developed an AI algorithm capable of identifying and targeting lung cancer tumors on CT scans in a few seconds. The research team reported that radiation oncologists utilizing the AI algorithm work 65% quicker than those not using it.

Study results
For the study, the research team used CT images from 787 people to train their AI model on how to distinguish tumors from other tissues. They then tested the AI algorithm with scans from more than 1,400 patients.

“By training the AI algorithm on segmentations of lung cancer tumors that were generated by a clinician with expertise in this task, we can theoretically replicate the skills and experience of this clinician wherever we deploy the AI algorithm,” Mak explained.

Once training was complete, researchers had eight radiation oncologists perform segmentation tasksTrusted Source where they identify the specific areas for treatment. The radiation oncologists were also asked to rate and edit segmentations made by another physician or the AI algorithm, without knowing which had made each segmentation.

Upon analysis, the researchers found no significant difference in performance between the segmentations made between a human and AI algorithm team, compared to those made only by human medical professionals.

The research team also found clinicians worked 65% quicker with 32% less variation when editing a segmentation created by the AI algorithm, compared to those segmentations produced manually by doctors.

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Medical News Today