Development and validation of a nomogram based on multiparametric magnetic resonance imaging and elastography-derived data for the stratification of patients with prostate cancer

Abstract

Background: This study sought to develop and validate a nomogram combining the elastographic Q-analysis score (EQS), the Prostate Imaging Reporting and Data System (PI-RADS) score, and clinical parameters for the stratification of patients with prostate cancer (PCa). Methods: A retrospective study was conducted of 375 patients with 375 lesions who underwent volumenavigation transrectal ultrasound (TRUS) and multiparametric magnetic resonance imaging (MP-MRI)fusion targeted biopsies between April 2017 and January 2020. Based on a multivariate logistic regression model, a nomogram was created to assess any PCa and high-risk PCa [Gleason score (GS) ≥4+3] using data from patients diagnosed between April 2017 and June 2019 (n=271), and was validated in patients diagnosed after July 2019 (n=104). The nomogram's performance was evaluated based on its discrimination, calibration, and clinical usefulness.Results: The areas under the curve (AUCs) of the nomogram for predicting any PCa and high-risk PCa were 0.949 [95% confidence interval (CI), 0.921 to 0.978] and 0.936 (95% CI, 0.906 to 0.965), respectively, in the training cohort, and 0.946 (95% CI, 0.894 to 0.997) and 0.971 (95% CI, 0.9331 to 1), respectively, in the validation cohort. The nomogram was well calibrated, and no significant difference was found between the predicted and observed probabilities. A decision curve analysis (DCA) for the nomogram with and without the EQS showed that the threshold probability of for any PCa was <67%. Conclusions:The nomogram that combined elastography-derived and MP-MRI data was more clinically useful than the model based on PI-RADS and clinical parameters alone. Our nomogram could aid urologists to make decisions and avoid unnecessary biopsies.

A novel model incorporating quantitative contrast-enhanced ultrasound into PI-RADSv2-based nomogram detecting clinically significant prostate cancer

“…Wang 26 et al combined PI-RADS score with PSAD to detect clinically significant prostate cancer, the specificity and positive predictive values of which were 93.5% and 82.4%, respectively. Ding 27 et al combined PI-RADSv2 score and ultrasonic elastography-derived data to stratify prostate cancer, and found that the nomogram they constructed combing elastography-derived and mp-MRI data was more clinically useful than the model based on PI-RADS score and clinical parameters alone.…”

Detection of intermediate- and high-risk prostate cancer with biparametric magnetic resonance imaging: a systematic review and meta-analysis

“…Most of the included studies used a threshold of PI-RADS ≥3, but several studies used PI-RADS ≥4. According to PI-RADS v.2 ( 36 ), a score of 3 means that PCa is suspected, whereas a score of 4 means that cancer is more likely. In addition, we showed that the diagnostic sensitivity of PI-RADS ≥3 (93%; 95% CI: 90–96%) was higher than that of PI-RADS ≥4 (85%; 95% CI: 77–93%).…”

Alternatives for MRI in Prostate Cancer Diagnostics—Review of Current Ultrasound-Based Techniques

“…Nevertheless, the fusion of these imaging modalities was associated with even higher sensitivity (97%), specificity (88%), PPV (85%), and NPV (95%). Furthermore, the same researchers developed and then validated a nomogram combining the elastographic Q analysis score, PI-RADS score, and clinical parameters for the stratification of patients with PCa [117]. The areas under the curve for predicting csPCa in the training cohort (n = 271) and in the validation cohort (104) were 0.936 (95% CI 0.906-0.965) and 0.971 (95% CI 0.9331-1), respectively.…”