Evidence map›Paper›PMID 38024433›Full record

ArticleAsian journal of urology2023

Three-dimensional automatic artificial intelligence driven augmented-reality selective biopsy during nerve-sparing robot-assisted radical prostatectomy: A feasibility and accuracy study.

Enrico Checcucci, Alberto Piana, Gabriele Volpi, Pietro Piazzolla, Daniele Amparore, Sabrina De Cillis, Federico Piramide, Cecilia Gatti, Ilaria Stura, Enrico Bollito and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Asian journal of urology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 6 pooled it
7.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 6 syntheses or guidelines pooled it, 29 citations in OpenAlex.

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  4. Visual extended reality tools in image-guided surgery in urology: a systematic review.European journal of nuclear medicine and molecular imaging · 2024
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  12. Artificial intelligence in urology training Enhancing annotation, feedback, and evaluation in robotic, laparoscopic, and endoscopic surgery.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2026
    Review
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  14. The times they are (still) a-Changin'.Prostate cancer and prostatic diseases · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 1 country.

Enrico CheccucciDepartment of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy.
Alberto PianaDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Gabriele VolpiDepartment of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, Italy.
Pietro PiazzollaDepartment of Mechanical Engineering, Politecnico di Milano, Milan, Italy.
Daniele AmparoreDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Sabrina De CillisDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Federico PiramideDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Cecilia GattiDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Ilaria SturaDepartment of Public Health and Pediatric Sciences, School of Medicine, University of Turin, Italy.
Enrico BollitoDepartment of Pathology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Federica MassaDepartment of Pathology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Michele Di DioSS Annunziata Hospital, Department of Surgery, Division of Urology, Cosenza, Italy.
Cristian FioriDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Francesco PorpigliaDepartment of Oncology, Division of Urology, University of Turin, San Luigi Gonzaga Hospital, Orbassano, To, Italy.
Ospedale San Luigi Gonzaga · ITUniversity of Turin · ITCandiolo Cancer Institute · ITOspedale Annunziata di Cosenza · ITPolitecnico di Milano · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the accuracy of our new three-dimensional (3D) automatic augmented reality (AAR) system guided by artificial intelligence in the identification of tumour's location at the level of the preserved neurovascular bundle (NVB) at the end of the extirpative phase of nerve-sparing robot-assisted radical prostatectomy. Methods: In this prospective study, we enrolled patients with prostate cancer (clinical stages cT1c-3, cN0, and cM0) with a positive index lesion at target biopsy, suspicious for capsular contact or extracapsular extension at preoperative multiparametric magnetic resonance imaging. Patients underwent robot-assisted radical prostatectomy at San Luigi Gonzaga Hospital (Orbassano, Turin, Italy), from December 2020 to December 2021. At the end of extirpative phase, thanks to our new AAR artificial intelligence driven system, the virtual prostate 3D model allowed to identify the tumour's location at the level of the preserved NVB and to perform a selective excisional biopsy, sparing the remaining portion of the bundle. Perioperative and postoperative data were evaluated, especially focusing on the positive surgical margin (PSM) rates, potency, continence recovery, and biochemical recurrence. Results: Thirty-four patients were enrolled. In 15 (44.1%) cases, the target lesion was in contact with the prostatic capsule at multiparametric magnetic resonance imaging (Wheeler grade L2) while in 19 (55.9%) cases extracapsular extension was detected (Wheeler grade L3). 3D AAR guided biopsies were negative in all pathological tumour stage 2 (pT2) patients while they revealed the presence of cancer in 14 cases in the pT3 cohort (14/16; 87.5%). PSM rates were 0% and 7.1% in the pathological stages pT2 and pT3 (<3 mm, Gleason score 3), respectively. Conclusion: With the proposed 3D AAR system, it is possible to correctly identify the lesion's location on the NVB in 87.5% of pT3 patients and perform a 3D-guided tailored nerve-sparing even in locally advanced diseases, without compromising the oncological safety in terms of PSM rates.

Indexed as

Artificial intelligenceAugmented realityProstate cancerRadical prostatectomyRobotics

Identifiers

PMID38024433
PMCPMC10659972
OpenAlexW4385737327

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.