AI could enhance prediction of treatment response among patients with non-small cell lung cancer

Deep learning algorithms trained using artificial intelligence (AI) may help to determine how patients will respond to systemic treatments for non-small cell lung cancer (NSCLC), according to new research published in the journal Clinical Cancer Research. For the study, associate research scientist Laurent Dercle (Department of Radiology, Columbia University Irving Medical Center) and colleagues applied AI to standard-of-care (SoC) computed tomography (CT) scans of advanced NSCLC and trained deep learning algorithms to predict how sensitive tumors would be to three types of systemic treatments. Deep learning is a type of machine learning where algorithms called artificial neural networks learn from large datasets and solve problems in a way that mimics how the human brain works and without requiring human supervision. Dercle says that currently, the way radiologists interpret CT scans of patients with cancer who are receiving systemic therapy is essentially subjective. 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," Currently, to check how NSCLC patients' respond to systemic therapies, radiologists assess differences in the size of existing tumors and in the appearance of new tumors that have formed.