Rishitha Rao Ketineni, Bhanupriya Singh, Achsah Raj Chandralekha, Indurani M S, Kanak Soni, Niraj Lodha
This review explores the growing role of advanced radiological imaging in internal medicine, focusing on its applications in prognosis prediction, disease monitoring, and early diagnosis. It highlights how developments in computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), ultrasound, and the integration of artificial intelligence (AI) are reshaping clinical decision-making in fields such as neurology, cardiology, and oncology. Although progress has been substantial, widespread adoption is still limited by high costs, unequal access, and the absence of consistent protocols. The use of AI in combination with radiomics, the quantitative study of medical images, has enhanced diagnostic accuracy and expanded opportunities for outcome prediction and treatment planning. However, challenges remain, including inconsistencies in data quality, regulatory barriers, and the pressing need for validation through large-scale, multicenter studies. Hybrid technologies such as PET/MRI, which combine functional and anatomical imaging, hold particular promise for improving diagnostic precision in neurology and oncology. Together, these innovations illustrate the transformative potential of modern imaging to enable earlier interventions and support more personalized care strategies. The review emphasizes the need for validation, standardized frameworks, and international collaboration to overcome current limitations. Addressing these concerns will broaden the accessibility of these tools, fostering more equitable healthcare and improved outcomes worldwide. Finally, it provides practical guidance for clinicians, researchers, and policymakers who must adapt to the rapidly advancing landscape of radiological imaging.