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Systematic Review

The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness

by
Luca Urso
1,2,
Ilham Badrane
1,2,†,
Luigi Manco
3,†,
Angelo Castello
4,*,
Federica Lancia
5,
Jeanlou Collavino
6,
Alessandro Crestani
6,7,
Massimo Castellani
4,
Corrado Cittanti
1,2,
Mirco Bartolomei
2 and
Gianluca Giannarini
6
1
Department of Translational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy
2
Nuclear Medicine Unit, Onco-Hematology Department, University Hospital of Ferrara, 44124 Ferrara, Italy
3
Medical Physics Unit, University Hospital of Ferrara, 44124 Ferrara, Italy
4
Nuclear Medicine Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
5
Oncology Unit, University Hospital of Ferrara, 44124 Ferrara, Italy
6
Urology Unit, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
7
Department of Medicine, University of Udine, 33100 Udine, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Clin. Med. 2025, 14(10), 3318; https://doi.org/10.3390/jcm14103318
Submission received: 8 March 2025 / Revised: 24 April 2025 / Accepted: 3 May 2025 / Published: 9 May 2025
(This article belongs to the Section Nuclear Medicine & Radiology)
Versions Notes

Abstract

Background: PSMA PET is essential tool in the management of prostate cancer (PCa) patients in various clinical settings of disease. The tremendous growth of the implementation of radiomics and artificial intelligence (AI) in medical imaging techniques has led to an increasing interest in their application in prostate-specific membrane antigen (PSMA) PET. The aim of this article is to systemically review the current literature that explores radiomics and AI analyses of staging PSMA PET towards its potential application in clinical practice. Methods: A systematic research of the literature on three international databases (PubMed, Scopus, and Web of Science) identified a total of 166 studies. An initial screening excluded 68 duplicates and 72 articles relevant to other topics. Finally, 21 studies met the inclusion criteria. Conclusions: The literature suggests that radiomic analysis could improve the characterization of tumor aggressiveness, the prediction of extra-capsular extension, and seminal vesicles involvement. Moreover, AI models could contribute to predicting BCR after radical treatment. Limitations regarding heterogeneous objectives of investigation, and methodological standardization of radiomics analysis still represent the main obstacle to overcome in order to see these technology break through into daily clinical practice.
Keywords: radiomic; radiomic features; artificial intelligence; PET; PSMA; prostate cancer (PCa); staging; biochemical recurrence; prognosis radiomic; radiomic features; artificial intelligence; PET; PSMA; prostate cancer (PCa); staging; biochemical recurrence; prognosis

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MDPI and ACS Style

Urso, L.; Badrane, I.; Manco, L.; Castello, A.; Lancia, F.; Collavino, J.; Crestani, A.; Castellani, M.; Cittanti, C.; Bartolomei, M.; et al. The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness. J. Clin. Med. 2025, 14, 3318. https://doi.org/10.3390/jcm14103318

AMA Style

Urso L, Badrane I, Manco L, Castello A, Lancia F, Collavino J, Crestani A, Castellani M, Cittanti C, Bartolomei M, et al. The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness. Journal of Clinical Medicine. 2025; 14(10):3318. https://doi.org/10.3390/jcm14103318

Chicago/Turabian Style

Urso, Luca, Ilham Badrane, Luigi Manco, Angelo Castello, Federica Lancia, Jeanlou Collavino, Alessandro Crestani, Massimo Castellani, Corrado Cittanti, Mirco Bartolomei, and et al. 2025. "The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness" Journal of Clinical Medicine 14, no. 10: 3318. https://doi.org/10.3390/jcm14103318

APA Style

Urso, L., Badrane, I., Manco, L., Castello, A., Lancia, F., Collavino, J., Crestani, A., Castellani, M., Cittanti, C., Bartolomei, M., & Giannarini, G. (2025). The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness. Journal of Clinical Medicine, 14(10), 3318. https://doi.org/10.3390/jcm14103318

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