Theranostics and artificial intelligence: new frontiers in personalized medicine
Authors
Gokce Belge Bilgin, Cem Bilgin, Brian J. Burkett, Jacob J. Orme, Daniel S. Childs, Matthew P. Thorpe, Thorvardur R Halfdanarson, Geoffrey B Johnson, Ayse Tuba Kendi, Oliver Sartor
Bilgin, Bilgin, Burkett, Orme, Childs, Thorpe, Halfdanarson, Johnson, Kendi, and Sartor review the impact of artificial intelligence (AI) in theranostics, particularly within nuclear medicine and precision oncology. They discuss AI’s role in automating tumor characterization, patient selection, dosimetry, and drug discovery. FDA-approved AI tools like Aview, designed for enhanced accuracy in image interpretation, aid in segmenting organs and tumors for more precise dosimetry calculations, advancing personalized treatment plans. The study highlights AI’s potential for predicting high-risk lesions, adjusting patient-specific radiation doses, and anticipating treatment side effects to improve safety and efficacy. Generative AI applications are also discussed for their role in radiopharmaceutical drug discovery and targeting. Despite its promise, AI in theranostics faces challenges, including limitations in data diversity, privacy concerns, and the need for broader generalizability. The authors emphasize further research to overcome these barriers, ensuring responsible and impactful integration of AI in clinical practice.