The application of artificial intelligence in the IMRT planning process for head and neck cancer

Abstract

Artificial intelligence (AI) is beginning to transform IMRT treatment planning for head and neck patients. However, the complexity and novelty of AI algorithms make them susceptible to misuse by researchers and clinicians. Understanding nuances of new technologies could serve to mitigate potential clinical implementation pitfalls. This article is intended to facilitate integration of AI into the radiotherapy clinic by providing an overview of AI algorithms, including support vector machines (SVMs), random forests (RF), gradient boosting (GB), and several variations of deep learning. This document describes current AI algorithms that have been applied to head and neck IMRT planning and identifies rapidly growing branches of AI in industry that have potential applications to head and neck cancer patients receiving IMRT. AI algorithms have great clinical potential if used correctly but can also cause harm if misused, so it is important to raise the level of AI competence within radiation oncology so that the benefits can be realized in a controlled and safe manner.

Keywords: Artificial intelligence; Automated treatment planning; Convolutional neural networks; Deep learning; Head and neck; Intensity modulated radiation therapy; Machine learning; Predictive medicine; Radiation oncology; Treatment planning.