Evidence map›Paper›PMID 39960493›Full record

ArticleWorld journal of urology2025

Comparing different 3D virtual models generations for the planning of robotic partial nephrectomy: the added value of perfusion volumes implement.

Daniele Amparore, Federico Piramide, Mariano Burgio, Martina Mandaletti, Marco Colombo, Alexandru Turcan, Federico Rubat Baleuri, Enrico Checcucci, Sabrina De Cillis, Alberto Piana and 4 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in World journal of urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Daniele AmparoreDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Federico PiramideDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Mariano BurgioDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Martina MandalettiDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Marco ColomboDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Alexandru TurcanDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Federico Rubat BaleuriDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Enrico CheccucciDepartment of Surgery, Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Turin, 10060, Italy.
Sabrina De CillisDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Alberto PianaDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Michele Di DioDepartment of Surgery, Division of Urology, SS Annunziata Hospital, Cosenza, Italy.
Matteo ManfrediDivision of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Cristian Fiori *Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy.
Francesco Porpiglia *Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Italy. porpiglia@libero.it.ORCID http://orcid.org/0000-0001-8567-6795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe aim of the study is to evaluate the role of a new generation of 3D virtual models (3DVM) implemented with perfusion volumes algorithm, in influencing perioperative and functional outcomes after robotic partial nephrectomy (RAPN).

methodsA perfusion volume 3DVM was built using Voronoi diagram-based algorithm for all the organ-confined renal masses candidate for RAPN from 12/2019 to 12/2022. On its basis, a selective or super-selective clamping was planned. A sub-cohort of patients underwent renal scintigraphy (RS), evaluating estimated renal plasmatic flow (ERPF). Data were compared with a retrospectively selected control group in which the surgery was assisted by 3DVM without perfusion volume assessment.

results116 and 217 were considered. In 77 (67.5%) and 81 (37.3%) patients a selective or super-selective clamping was performed, in the study and control group respectively (p < 0.001). A higher rate of third-order artery clamping was recorded in the study group (42/77 vs. 26/81, p 0.004). No difference was found in terms of postoperative complications (overall postoperative: 17.2% and 19.3%; major complications: 3.4% and 3.2%). Clamping strategy failure was recorded in 5 (4.3%) and 26 (11.9%) (p 0.02). A significant ERPF drop (> 20%) was recorded in 3/51 (5.8%) and 16/82 (19.5%) patients in study and control group, respectively (p 0.04). Similarly, median delta ERPF resulted different between the groups (-10.69% vs. -18.92%, p < 0.001).

conclusionsPerfusional volumes 3DVMs, lead the surgeon to perform a higher rate of effective selective and super-selective clampings, translating in higher rates of renal units functionally saved.

Indexed as

Imaging, Three-DimensionalNephrectomyRobotic Surgical ProceduresAgedAlgorithmsConstrictionHumansMiddle AgedModels, AnatomicTreatment Outcome3d reconstructionKidney cancerNephron-sparing surgeryRenal cell carcinomaRobotic surgeryThree-dimensional imaging

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.