Integrating AI and Human Expertise: Exploring the Role of Radiomics in Multidisciplinary Tumor Boards

Abstract

Abstract In the ever-evolving landscape of oncology, the integration of artificial intelligence (AI) with radiomics has transformed the decision-making processes within multidisciplinary tumor boards (MDTs). MDTs serve as forums where specialists collaboratively discuss and recommend comprehensive treatment plans for patients with cancer, considering various clinical perspectives. This narrative review explores the synergistic relationship between AI and radiomics in oncology decision-making. We discuss the fundamentals of AI-powered radiomics, its workflow, and the role of radiomic features. Moreover, we delve into the integration of AI in radiology, radiation oncology, and medical oncology, emphasizing its impact on MDT decision-making, treatment planning, and predicting treatment responses, prognosis, and disease progression. Furthermore, we highlight the role of machine learning algorithms and their impact on MDT decision-making. We discuss the challenges and future implications of AI-driven radiomics in MDTs, considering ethical, financial, and regulatory aspects. Finally, we emphasize the transformative potential of AI-powered radiomics in reshaping oncology decision-making, facilitating more personalized and effective treatment strategies within MDTs.