Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics
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...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-06-01
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| Series: | European Radiology Experimental |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s41747-022-00282-0 |
| _version_ | 1811343431027392512 |
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| author | 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 Désirée Deandreis |
| author_facet | 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 Désirée Deandreis |
| author_sort | Virginia Liberini |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T19:30:22Z |
| format | Article |
| id | doaj.art-bdac68b7a4dd4a06b1de7f196fff110a |
| institution | Directory Open Access Journal |
| issn | 2509-9280 |
| language | English |
| last_indexed | 2024-04-13T19:30:22Z |
| publishDate | 2022-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | European Radiology Experimental |
| spelling | doaj.art-bdac68b7a4dd4a06b1de7f196fff110a2022-12-22T02:33:13ZengSpringerOpenEuropean Radiology Experimental2509-92802022-06-016111510.1186/s41747-022-00282-0Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnosticsVirginia Liberini0Riccardo Laudicella1Michele Balma2Daniele G. Nicolotti3Ambra Buschiazzo4Serena Grimaldi5Leda Lorenzon6Andrea Bianchi7Simona Peano8Tommaso Vincenzo Bartolotta9Mohsen Farsad10Sergio Baldari11Irene A. Burger12Martin W. Huellner13Alberto Papaleo14Désirée Deandreis15Medical Physiopathology — A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of TorinoDepartment of Nuclear Medicine, University Hospital Zurich, University of ZurichNuclear Medicine Department, S. Croce e Carle HospitalNuclear Medicine Department, S. Croce e Carle HospitalNuclear Medicine Department, S. Croce e Carle HospitalMedical Physiopathology — A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of TorinoMedical Physics Department, Central Bolzano HospitalNuclear Medicine Department, S. Croce e Carle HospitalNuclear Medicine Department, S. Croce e Carle HospitalDepartment of Radiology, Fondazione Istituto G. Giglio, Ct.da PietrapollastraNuclear Medicine, Central Hospital BolzanoNuclear Medicine Unit, Department of Biomedical and Dental Sciences and of Morpho-Functional Imaging, University of MessinaDepartment of Nuclear Medicine, University Hospital Zurich, University of ZurichDepartment of Nuclear Medicine, University Hospital Zurich, University of ZurichNuclear Medicine Department, S. Croce e Carle HospitalMedical Physiopathology — A.O.U. Città della Salute e della Scienza di Torino, Division of Nuclear Medicine, Department of Medical Science, University of TorinoAbstract 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.https://doi.org/10.1186/s41747-022-00282-0Prostate cancerPositron emission tomographyArtificial intelligenceRadiomicsTheragnostics |
| spellingShingle | 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 Désirée Deandreis Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics European Radiology Experimental Prostate cancer Positron emission tomography Artificial intelligence Radiomics Theragnostics |
| title | Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics |
| title_full | Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics |
| title_fullStr | Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics |
| title_full_unstemmed | Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics |
| title_short | Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics |
| title_sort | radiomics and artificial intelligence in prostate cancer new tools for molecular hybrid imaging and theragnostics |
| topic | Prostate cancer Positron emission tomography Artificial intelligence Radiomics Theragnostics |
| url | https://doi.org/10.1186/s41747-022-00282-0 |
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