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Updated: Jun 20, 2026

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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
PubMed
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This summary is machine-generated.

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).
Keywords:
NomogramPelvic dimensionsProstate cancerSingle-site robot-assisted radical prostatectomySurgical difficulty

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  • 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.