1. Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics
- Author
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Virginia Liberini, Riccardo Laudicella, Michele Balma, Daniele G. Nicolotti, Ambra Buschiazzo, Serena Grimaldi, Leda Lorenzon, Andrea Bianchi, Simona Peano, Tommaso Vincenzo Bartolotta, Mohsen Farsad, Sergio Baldari, Irene A. Burger, Martin W. Huellner, Alberto Papaleo, and Désirée Deandreis
- Subjects
Prostate cancer ,Positron emission tomography ,Artificial intelligence ,Radiomics ,Theragnostics ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 - Abstract
Abstract In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients’ risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these “big data” in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.
- Published
- 2022
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