ArticleProstate cancer and prostatic diseases2025
Augmented Reality PSMA-3D guided robotic pelvic lymph node dissection (PLND) in prostate cancer patients.
Article in Prostate cancer and prostatic diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Real-time surgical navigation for intraoperative lymph node localization during targeted robot-assisted pelvic and retroperitoneal lymph node dissection.Surgical endoscopy · 2026Article
- Early detection and localization of recurrent prostate cancer using [Formula: see text]F-DCFPyL PET/CT in patients with low and ultra-low PSA levels.EJNMMI research · 2026Article
- The evolution of radical prostatectomy: a scoping review on surgical techniques and integration of surgeon-assisting concepts into the surgical workflow.Frontiers in surgery · 2026Review
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Authors and funding
22 authors.
Funding
Abstract
BACKGROUND AND
objectiveIntraoperative identification of suspicious lymph node metastases (LNM) detected at PSMA-PET is key to achieve optimal surgical outcomes of robot-assisted radical prostatectomy (RARP) with pelvic lymph node dissection (PLND). We aim to describe a novel technique of augmented reality (AR)-PSMA-3D guided PLND based on preoperative PSMA-PET for real-time identification of LNM.
methodsThirteen patients with high-risk PCa and miN1-2 or miM1a disease at PSMA-PET were prospectively enrolled. 3D segmentation model including suspicious LNM was created from PSMA-PET images.
interventionPatients underwent RARP with AR-PSMA-3D guided PLND for real-time intraoperative identification of suspicious LNM. Pathologic examination was used as reference standard. KEY FINDINGS AND LIMITATIONS: Four (30%) men had suspicious LNM at PSMA-PET outside the field of the PLND template. The AR-PSMA-3D guided PLND allow to dissect each region with suspected LNM at PSMA-PET with no intraoperative complications. Nine (69%) patients had pN1 disease and three (23%) men had nodal metastases outside the PLND template. The sensitivity, specificity, PPV, NPV and AUC of AR-PSMA-3D guided PLND at a per-region analysis were 69%, 90%, 52%, 95% and 0.79, respectively. LIMITATIONS: low spatial resolution of PSMA-PET for micro-metastases and the need for manual alignment of the 3D model. CONCLUSIONS AND CLINICAL IMPLICATIONS: AR-PSMA-3D guidance for PLND in patients with miN1-N2-M1a disease at PSMA-PET allows to facilitate the resection of suspicious LNM including those outside the PLND template. We propose a novel technique combining AR and PSMA-PET 3D models to guide PLND during RARP in PCa patients. The AR-PSMA-3D guidance for PLND allows a promising real-time identification of suspicious nodes, even outside the PLND template.
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