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Predicting extraperitoneal ssRARP difficulty: an MRI-based nomogram
Jiapeng Liu1, Qiansheng Zhang1, Fuyang Lin1
1Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Journal of Robotic Surgery
|June 19, 2026
Summary
This study developed an MRI-clinical nomogram to predict surgical difficulty in robot-assisted radical prostatectomy. The nomogram helps optimize patient selection and reduce risks during extraperitoneal single-site procedures.
Area of Science:
- Urology
- Surgical Oncology
- Medical Imaging
Background:
- Extraperitoneal single-site robot-assisted radical prostatectomy (ssRARP) is a minimally invasive technique for prostate cancer treatment.
- Predicting surgical difficulty is crucial for optimizing patient outcomes and resource allocation.
- Current methods for assessing surgical difficulty in ssRARP are limited.
Purpose of the Study:
- To develop and validate a nomogram integrating MRI and clinical factors to predict surgical difficulty in extraperitoneal ssRARP.
- To identify independent predictors of high surgical difficulty in this patient cohort.
Main Methods:
- Retrospective analysis of 252 patients undergoing extraperitoneal ssRARP.
- Development of a multivariable logistic regression model to predict high difficulty (defined by console time or estimated blood loss).
- Validation using discrimination (AUC), calibration plots, bootstrap analysis, and decision curve analysis (DCA).
Main Results:
- High surgical difficulty was observed in 49.2% of patients.
- Independent predictors of difficulty included higher BMI, neoadjuvant therapy, larger prostate volume, narrower intertuberous distance, and greater symphysis pubis height.
- The developed nomogram demonstrated acceptable discrimination (AUC=0.675) and good calibration.
Conclusions:
- The novel MRI-clinical nomogram effectively predicts surgical difficulty in extraperitoneal ssRARP.
- This tool can aid in patient selection and perioperative risk mitigation.
- Recalibration is recommended for application in different clinical settings due to cohort-specific threshold calibration.
