The Evolving Role of Artificial Intelligence in Radiation Therapy: From Clinical Applications to Future Perspectives

Abstract

Artificial intelligence (AI) is rapidly changing many medical specialties, and Radiation Therapy is one of them. This paper deals with the adoption of AI in Radiation Therapy, its benefits and its challenges. Artificial intelligence can improve the accuracy, speed, and results of radiation therapy and may also aid in adaptive radiation therapy, predictive analytics, optimized treatment planning, and improved image analysis. Artificial intelligence can help cut planning times and boost accuracy by analyzing large data sets to determine the best treatment settings and automate difficult tasks. AI-driven methods are increasingly improving tumor detection and segmentation in image analysis by analyzing data from CT, MRI, and PET imaging, leading to precise delineation of the tumor. Adaptive radiation therapy uses AI to improve the accuracy and efficacy of treatment by adjusting treatment regimens in real time as a patient’s anatomy and tumor growth change. Using previous patient data for predictive analytics in order to predict treatment outcomes and potential complications make clinical decision making and more personalized treatment strategies possible. Barriers to AI implementation in radiotherapy include: - Data quality and quantity - Interoperability and standardization - Ethical and regulatory issues - Resistance to clinical implementation to meet these challenges, researchers, clinicians, data scientists, and business stakeholders must collaborate. AI could help overcome these barriers to advance radiation treatment, better patient care and streamline operations. This study provides an overview of the state of the art of the integration of AI in radiation therapy and recommendations for future lines of research and clinical application.