A novel pathway to detect muscle-invasive bladder cancer based on integrated clinical features and VI-RADS score on MRI: results of a prospective multicenter study

Purpose To determine the clinical, pathological, and radiological features, including the Vesical Imaging-Reporting and Data System (VI-RADS) score, independently correlating with muscle-invasive bladder cancer (BCa), in a multicentric national setting. Method and Materials Patients with BCa suspici...

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Veröffentlicht in:Radiologia medica 2022-08, Vol.127 (8), p.881-890
Hauptverfasser: Bicchetti, Marco, Simone, Giuseppe, Giannarini, Gianluca, Girometti, Rossano, Briganti, Alberto, Brunocilla, Eugenio, Cardone, Gianpiero, De Cobelli, Francesco, Gaudiano, Caterina, Del Giudice, Francesco, Flammia, Simone, Leonardo, Costantino, Pecoraro, Martina, Schiavina, Riccardo, Catalano, Carlo, Panebianco, Valeria
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Sprache:eng
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Zusammenfassung:Purpose To determine the clinical, pathological, and radiological features, including the Vesical Imaging-Reporting and Data System (VI-RADS) score, independently correlating with muscle-invasive bladder cancer (BCa), in a multicentric national setting. Method and Materials Patients with BCa suspicion were offered magnetic resonance imaging (MRI) before trans-urethral resection of bladder tumor (TURBT). According to VI-RADS, a cutoff of ≥ 3 or ≥ 4 was assumed to define muscle-invasive bladder cancer (MIBC). Trans-urethral resection of the tumor (TURBT) and/or cystectomy reports were compared with preoperative VI-RADS scores to assess accuracy of MRI for discriminating between non-muscle-invasive versus MIBC. Performance was assessed by ROC curve analysis. Two univariable and multivariable logistic regression models were implemented including clinical, pathological, radiological data, and VI-RADS categories to determine the variables with an independent effect on MIBC. Results A final cohort of 139 patients was enrolled (median age 70 [IQR: 64, 76.5]). MRI showed sensitivity, specificity, PPV, NPV, and accuracy for MIBC diagnosis ranging from 83–93%, 80–92%, 67–81%, 93–96%, and 84–89% for the more experienced readers. The area under the curve (AUC) was 0.95 (0.91–0.99). In the multivariable logistic regression model, the VI-RADS score, using both a cutoff of 3 and 4 ( P  
ISSN:1826-6983
0033-8362
1826-6983
DOI:10.1007/s11547-022-01513-5