PURPOSE: We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery. METHODS: Patients with biopsy-proven PCa scheduled for robot-assisted radical prostatectomy (RARP) were prospectively recruited. The following MRI-derived microUS features were evaluated: capsular bulging, visible breach of the prostate capsule (visible extracapsular extension; ECE), presence of hypoechoic halo, and obliteration of the vesicle-prostatic angle. The ability of each feature to predict EPE was determined. RESULTS: Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p < 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) ≥ pT3. Rate of non-organ-confined disease increased from 44% in those individuals with only 1 predictor (OR 7.71) to 92.3% in those where 4 predictors (OR 72.00) were simultaneously observed. The multivariate logistic regression model including clinical parameters showed an area under the curve (AUC) of 82.3% as compared to an AUC of 87.6% for the model including both clinical and microUS parameters. Presence of ECE at microUS predicted EPE with a sensitivity of 72.1% and a specificity of 88%, a negative predictive value of 80.5% and positive predictive value of 83.0%, with an AUC of 80.4%. CONCLUSIONS: MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.
PURPOSE: We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery. METHODS: Patients with biopsy-proven PCa scheduled for robot-assisted radical prostatectomy (RARP) were prospectively recruited. The following MRI-derived microUS features were evaluated: capsular bulging, visible breach of the prostate capsule (visible extracapsular extension; ECE), presence of hypoechoic halo, and obliteration of the vesicle-prostatic angle. The ability of each feature to predict EPE was determined. RESULTS: Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p < 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) ≥ pT3. Rate of non-organ-confined disease increased from 44% in those individuals with only 1 predictor (OR 7.71) to 92.3% in those where 4 predictors (OR 72.00) were simultaneously observed. The multivariate logistic regression model including clinical parameters showed an area under the curve (AUC) of 82.3% as compared to an AUC of 87.6% for the model including both clinical and microUS parameters. Presence of ECE at microUS predicted EPE with a sensitivity of 72.1% and a specificity of 88%, a negative predictive value of 80.5% and positive predictive value of 83.0%, with an AUC of 80.4%. CONCLUSIONS: MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.
Authors: Giovanni Lughezzani; Alberto Saita; Massimo Lazzeri; Marco Paciotti; Davide Maffei; Giuliana Lista; Rodolfo Hurle; Nicolò Maria Buffi; Giorgio Guazzoni; Paolo Casale Journal: Eur Urol Oncol Date: 2018-10-25
Authors: Marc A Bjurlin; Peter R Carroll; Scott Eggener; Pat F Fulgham; Daniel J Margolis; Peter A Pinto; Andrew B Rosenkrantz; Jonathan N Rubenstein; Daniel B Rukstalis; Samir S Taneja; Baris Turkbey Journal: J Urol Date: 2019-10-23 Impact factor: 7.450
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Authors: Annika Herlemann; Maya R Overland; Samuel L Washington; Janet E Cowan; Antonio C Westphalen; Peter R Carroll; Hao G Nguyen; Katsuto Shinohara; Matthew R Cooperberg Journal: Eur Urol Focus Date: 2020-08-28
Authors: Sangeet Ghai; Gregg Eure; Vincent Fradet; Matthew E Hyndman; Theresa McGrath; Brian Wodlinger; Christian P Pavlovich Journal: J Urol Date: 2016-01-12 Impact factor: 7.450
Authors: Sherif Mehralivand; Joanna H Shih; Stephanie Harmon; Clayton Smith; Jonathan Bloom; Marcin Czarniecki; Samuel Gold; Graham Hale; Kareem Rayn; Maria J Merino; Bradford J Wood; Peter A Pinto; Peter L Choyke; Baris Turkbey Journal: Radiology Date: 2019-01-22 Impact factor: 11.105