Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions

Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions

The risk of misclassifying clinically significant prostate cancer (csPCa) by multiparametric magnetic resonance imaging is consistent, also using the updated PIRADS score and although different definitions of csPCa, patients with Gleason Grade group (GG) ≥ 3 have a significantly worse prognosis. Thi...

Full description

Bibliographic Details
Main Authors: Caterina Gaudiano, Margherita Mottola, Lorenzo Bianchi, Beniamino Corcioni, Arrigo Cattabriga, Maria Adriana Cocozza, Antonino Palmeri, Francesca Coppola, Francesca Giunchi, Riccardo Schiavina, Michelangelo Fiorentino, Eugenio Brunocilla, Rita Golfieri, Alessandro Bevilacqua
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Cancers
Subjects:
cancer staging
machine learning
multiparametric magnetic resonance imaging
prostate cancer
radiomics
Online Access:https://www.mdpi.com/2072-6694/14/24/6156

Similar Items

Similar Items