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Multiparametric magnetic resonance imaging and magnetic resonance imaging fusion-guided biopsy for the diagnosis of prostate cancer: current status

Authors :
Valentina Testini
Laura Eusebi
Francesco Saverio Guerra
Willy Giannubilo
Manuel Di Biase
Annunziata Russo
Giuseppe Guglielmi
Source :
Digital Diagnostics, Vol 5, Iss 2, Pp 283-302 (2024)
Publication Year :
2024
Publisher :
Eco-Vector, 2024.

Abstract

This review explains the role of multiparametric magnetic resonance imaging, particularly in prostate biopsy, in the detection of prostate cancer. The use of multiparametric magnetic resonance imaging in the diagnosis of prostate cancer has also allowed its use in magnetic resonance imaging-guided biopsies, which according to many studies present high sensitivity and specificity in early diagnosis and staging, in patients with persistently high prostate-specific antigen levels despite previous negative prostate biopsies, and in the follow-up of patients under active surveillance. To perform a targeted prostate biopsy, three types of magnetic resonance imaging guidance are available: cognitive fusion, direct magnetic resonance imaging-guided biopsy performed within a tomograph (in-bore biopsies), and software coregistration of stored magnetic resonance images with real-time ultrasound using a fusion device, with multiparametric magnetic resonance imaging findings digitally overlaid on real-time transrectal ultrasound images for targeted biopsy. Each method has its advantages and disadvantages. Magnetic resonance imaging-targeted biopsy improves the quality of histological results compared with other approaches, with approximately 90% correct detection of significant index lesions. Correct staging allows the selection of the best therapeutic options, adequate evaluation of the prognosis, and reduction of the incidence of new biopsies and complications. The current objective is to make magnetic resonance imaging-guided biopsy increasingly available and standardize the technique to minimize inter-operator variability depending on the available system.

Details

Language :
English, Russian, Chinese
ISSN :
27128490 and 27128962
Volume :
5
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Digital Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.f242b25e2a614f29a6fe82d770af701d
Document Type :
article
Full Text :
https://doi.org/10.17816/DD623183