Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging

Authors

Tricia Chinnery, Western University
Andrew Arifin, Western University
Keng Yeow Tay, Western University
Andrew Leung, Western University
Anthony C. Nichols, Western University
David A. Palma, Western University
Sarah A. Mattonen, Western University
Pencilla Lang, Western University

Document Type

Article

Publication Date

1-1-2020

Journal

Canadian Association of Radiologists Journal

URL with Digital Object Identifier

10.1177/0846537120942134

Abstract

© The Author(s) 2020. Artificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decision-making to improve patient outcomes. Imaging and radiomics play an increasingly important role in these models. This review summarizes recent developments in the field of radiomics for AI in head and neck cancer. Prediction models for oncologic outcomes, treatment toxicity, and pathological findings have all been created. Exploratory studies are promising; however, validation studies that demonstrate consistency, reproducibility, and prognostic impact remain uncommon. Prospective clinical trials with standardized procedures are required for clinical translation.