AI may help predict responses to non-small cell lung cancer systemic therapies

Using standard-of-care computed tomography (CT) scans in patients with advanced non-small cell lung cancer (NSCLC), researchers utilized artificial intelligence (AI) to train algorithms to predict tumor sensitivity to three systemic cancer therapies. The study is published in Clinical Cancer Research, a journal of the American Association for Cancer Research, by Laurent Dercle, MD, Ph.D., associate research scientist in the Department of Radiology at the Columbia University Irving Medical Center "Radiologists' interpretation of CT scans of cancer patients treated with systemic therapies is inherently subjective," said Dercle. "The purpose of this study was to train cutting-edge AI technologies to predict patients' responses to treatment, allowing radiologists to deliver more accurate and reproducible predictions of treatment efficacy at an early stage of the disease." To determine if patients with NSCLC are responding to systemic therapy, radiologists currently quantify changes in tumor size and the appearance of new tumor lesions, Dercle explained. However, this type of evaluation can be limited, especially in patients treated with immunotherapy, who can display atypical patterns of response and progression, he noted.