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.

Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease. To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment. "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," explained Laurent Dercle, associate research scientist at the Columbia University Irving Medical Center. Radiologists currently quantify changes in tumour size and the appearance of new tumour lesions. However, this type of evaluation can be limited, especially in patients treated with immunotherapy, who can display atypical patterns of response and progression.

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.