Side-specific, Microultrasound-based Nomogram for the Prediction of Extracapsular Extension in Prostate Cancer

Abstract

Background: Prediction of extracapsular extension (ECE) is essential to achieve a balance between oncologic resection and neural tissue preservation. Microultrasound (MUS) is an attractive alternative to multiparametric magnetic resonance imaging (mpMRI) in the staging scenario.

Objective: To create a side-specific nomogram integrating clinicopathologic parameters and MUS findings to predict ipsilateral ECE and guide nerve sparing.

Design setting and participants: Prospective data were collected from consecutive patients who underwent robotic-assisted radical prostatectomy from June 2021 to May 2022 and had preoperative MUS and mpMRI. A total of 391 patients and 612 lobes were included in the analysis.

Outcome measurements and statistical analysis: ECE on surgical pathology was the primary outcome. Multivariate regression analyses were carried out to identify predictors for ECE. The resultant multivariable model's performance was visualized using the receiver-operating characteristic curve. A nomogram was developed based on the coefficients of the logit function for the MUS-based model. A decision curve analysis (DCA) was performed to assess clinical utility.

Results and limitations: The areas under the receiver-operating characteristic curve (AUCs) of the MUS-based model were 81.4% and 80.9% (95% confidence interval [CI] 75.6, 84.6) after internal validation. The AUC of the mpMRI-model was also 80.9% (95% CI 77.2, 85.7). The DCA demonstrated the net clinical benefit of the MUS-based nomogram and its superiority compared with MUS and MRI alone for detecting ECE. Limitations of our study included its sample size and moderate inter-reader agreement.

Conclusions: We developed a side-specific nomogram to predict ECE based on clinicopathologic variables and MUS findings. Its performance was comparable with that of a mpMRI-based model. External validation and prospective trials are required to corroborate our results.

Patient summary: The integration of clinical parameters and microultrasound can predict extracapsular extension with similar results to models based on magnetic resonance imaging findings. This can be useful for tailoring the preservation of nerves during surgery.

Keywords: Extracapsular extension; Microultrasound; Multiparametric magnetic resonance imaging; Prostate cancer.

Fig. 1

Examples of MRI-derived parameters to detect ECE with MUS: capsular contact length ≥15 mm, capsular bulging and irregularity (yellow dotted line), visible breach of the prostate (red arrow), and obliteration of the prostatic-seminal vesicle angle (green arrow). ECE = extracapsular extension; MRI = magnetic resonance imaging; MUS = microultrasound.

Fig. 1

Examples of MRI-derived parameters to detect ECE with MUS: capsular contact length ≥15 mm, capsular bulging and irregularity (yellow dotted line), visible breach of the prostate (red arrow), and obliteration of the prostatic-seminal vesicle angle (green arrow). ECE = extracapsular extension; MRI = magnetic resonance imaging; MUS = microultrasound.

Fig. 2

Nomogram for the prediction of ECE based on MUS. ECE = extracapsular extension; GGG = Gleason grading group; ISUP = International Society of Urological Pathology; MaxP = maximum percentage of core involvement in the core with the highest GGG; MUS = microultrasound; Prob = probability; PSAD = prostate-specific antigen density.

Fig. 3

Decision curve analysis showing net benefit of using our model based on MUS. ECE = extracapsular extension; MRI = magnetic resonance imaging; MUS = microultrasound.