In the present report we aimed to analyze the incremental value of preoperative magnetic resonance imaging (MRI), in addition to clinical variables and clinically-derived nomograms, in predicting outcomes radical prostatectomy (RP). All Mayo Clinic RP patients who underwent preoperative 1.5-Tesla MRI with endo-rectal coil from 2003 to 2013 were identified. Clinical and histopathological variables were used to calculate Partin estimates and Cancer of the Prostate Risk Assessment (CAPRA) score. MRI results in terms of extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph-node invasion (N+) were recorded. Using RP pathology as gold standard, we developed multivariate logistic regression models based on clinical variables, Partin Tables, and CAPRA score, and assessed their predictive accuracy before and after the addition of MRI results. Five hundred and one patients were included. MRI + clinical models outperformed clinical-based models alone for all outcomes. Comparing Partin and Partin + MRI predictive models, the areas under the curve were 0.61 versus 0.73 for ECE, 0.75 versus 0.82 for SVI, and 0.82 versus 0.85 for N+. Comparing CAPRA and CAPRA + MRI models, the areas under the curve were 0.69 versus 0.77 for ECE, 0.75 versus 0.83 for SVI, and 0.82 versus 0.85 for N+. Our data show that MRI can improve clinical-based models in prediction of nonorgan confined disease, particularly for ECE and SVI.

The Incremental Role of Magnetic Resonance Imaging for Prostate Cancer Staging before Radical Prostatectomy

Morlacco, Alessandro
Writing – Original Draft Preparation
;
2017

Abstract

In the present report we aimed to analyze the incremental value of preoperative magnetic resonance imaging (MRI), in addition to clinical variables and clinically-derived nomograms, in predicting outcomes radical prostatectomy (RP). All Mayo Clinic RP patients who underwent preoperative 1.5-Tesla MRI with endo-rectal coil from 2003 to 2013 were identified. Clinical and histopathological variables were used to calculate Partin estimates and Cancer of the Prostate Risk Assessment (CAPRA) score. MRI results in terms of extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph-node invasion (N+) were recorded. Using RP pathology as gold standard, we developed multivariate logistic regression models based on clinical variables, Partin Tables, and CAPRA score, and assessed their predictive accuracy before and after the addition of MRI results. Five hundred and one patients were included. MRI + clinical models outperformed clinical-based models alone for all outcomes. Comparing Partin and Partin + MRI predictive models, the areas under the curve were 0.61 versus 0.73 for ECE, 0.75 versus 0.82 for SVI, and 0.82 versus 0.85 for N+. Comparing CAPRA and CAPRA + MRI models, the areas under the curve were 0.69 versus 0.77 for ECE, 0.75 versus 0.83 for SVI, and 0.82 versus 0.85 for N+. Our data show that MRI can improve clinical-based models in prediction of nonorgan confined disease, particularly for ECE and SVI.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3291119
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