First live case of augmented reality robot-assisted radical prostatectomy from 3D magnetic resonance imaging reconstruction integrated with PRECE model (Predicting Extracapsular extension of prostate cancer)

• Main Authors: Stefano Puliatti, Maria Chiara Sighinolfi, Bernardo Rocco, Vipul Patel, Porpiglia Francesco, Salvatore Micali, Ahmed Eissa, Pietro Torricelli, Giampaolo Bianchi
• Format: Article
• Language: English
• Published: Elsevier 2019-03-01
• Series: Urology Video Journal
• Subjects: Robotic Radical Prostatectomy; Augmented reality; Extracapsular extension; Nomograms
• Online Access: http://www.sciencedirect.com/science/article/pii/S2590089719300015

Objectives: To report the feasibility of a console integrated augmented reality model during robotic assisted radical prostatectomy (AR-RARP) developed from combining the results of prostate multiparametric magnetic-resonance-imaging (mpMRI) and a statistical tool for the prediction of the extent of extracapsular extension (ECE) of prostate cancer (based on clinical and biopsy pathological variables). The first live case was presented during the European Section of Uro-Technology (ESUT) Congress on May 2018. Materials and methods: We describe the case of a man (59-years) with PSA 4.6 ng/ml and GS3+3 involving up to 30% of the samples. The Predicting Extracapsular Extension of PCa (PRECE) tool – a side specific model anticipating the risk of ECE at different distances from the capsule- predicted a 1.8% and 2.1% ECE risk at 1 mm-distance from the prostatic capsule in the left and right lobes, respectively. These outputs were combined with the mpMRI images to develop a 3D-virtual model integrated in the DaVinci console (High Fidelity and Precision 3D Reconstructions HA3D program). Results: The location and the extent of the mpMRI detected lesions were superimposed on the prostate in a real time fashion allowing both the detection and the continuous control of the adequate plane of dissection. Pathological examination revealed a pT2c with negative surgical margins; functional outcomes were satisfactory at 2-months follow-up. Conclusion: AR-RARP based on mpMRI plus PRECE is a promising tool that may result in a more precise intraoperative navigation rather than other models based only on imaging, and ensuring the ideal of the precision surgery.