The use of artificial intelligence in radiation oncology is expanding to support clinicians in multiple facets of treatment planning and delivery. This includes automated organ segmentation, dose calculation, and treatment response assessment. These AI-driven tools can act as an adjunct, working alongside radiation therapists, to improve accuracy and efficiency. For example, algorithms can delineate organs at risk, allowing radiation oncologists to focus on target volume definition and treatment optimization, potentially minimizing radiation exposure to healthy tissues.
The integration of these technologies offers several potential benefits. It streamlines workflows, reducing the time required for crucial steps like contouring, and aids in standardization, leading to more consistent treatment plans across different institutions. Historically, such tasks were time-consuming and subject to inter-observer variability. The introduction of AI aims to enhance the quality and precision of radiation therapy, contributing to improved patient outcomes and reduced side effects. This also provides therapists with decision support tools, improving treatment accuracy and allowing them to focus on direct patient care.
