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. 2018 May:115:184.
doi: 10.1016/j.urology.2018.01.028. Epub 2018 Mar 13.

Augmented Reality Robot-assisted Radical Prostatectomy: Preliminary Experience

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Augmented Reality Robot-assisted Radical Prostatectomy: Preliminary Experience

Francesco Porpiglia et al. Urology. 2018 May.

Abstract

Objective: To present our preliminary experience with augmented reality robot-assisted radical prostatectomy (AR-RARP).

Materials: From June to August 2017, patients candidate to RARP were enrolled and underwent high-resolution multi-parametric magnetic resonance imaging (1-mm slices) according to dedicated protocol. The obtained three-dimensional (3D) reconstruction was integrated in the robotic console to perform AR-RARP. According to the staging at magnetic resonance imaging or reconstruction, in case of cT2 prostate cancer, intrafascial nerve sparing (NS) was performed: a mark was placed on the prostate capsule to indicate the virtual underlying intraprostatic lesion; in case of cT3, standard NS AR-RARP was scheduled with AR-guided biopsy at the level of suspected extracapsular extension (ECE). Prostate specimens were scanned to assess the 3D model concordance.

Results: Sixteen patients underwent intrafascial NS technique (cT2), whereas 14 underwent standard NS+ selective biopsy of suspected ECE (cT3). Final pathology confirmed clinical staging. Positive surgical margins' rate was 30% (no positive surgical margins in pT2). In patients whose intraprostatic lesions were marked, final pathology confirmed lesion location. In patients with suspected ECE, AR-guided selective biopsies confirmed the ECE location, with 11 of 14 biopsies (78%) positive for prostate cancer. Prostate specimens were scanned with finding of a good overlap. The mismatch between 3D reconstruction and scanning ranged from 1 to 5 mm. In 85% of the entire surface, the mismatch was <3 mm.

Conclusion: In our preliminary experience, AR-RARP seems to be safe and effective. The accuracy of 3D reconstruction seemed to be promising. This technology has still limitations: the virtual models are manually oriented and rigid. Future collaborations with bioengineers will allow overcoming these limitations.

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