A Novel Three-dimensional Planning Tool for Selective Clamping During Partial Nephrectomy: Validation of a Perfusion Zone Algorithm.


Journal

European urology
ISSN: 1873-7560
Titre abrégé: Eur Urol
Pays: Switzerland
ID NLM: 7512719

Informations de publication

Date de publication:
05 2023
Historique:
received: 18 09 2022
revised: 25 11 2022
accepted: 06 01 2023
medline: 18 4 2023
pubmed: 4 2 2023
entrez: 3 2 2023
Statut: ppublish

Résumé

Selective clamping during robot-assisted partial nephrectomy (RAPN) requires extensive knowledge on patient-specific renal vasculature, obtained through imaging. To validate an in-house developed perfusion zone algorithm that provides patient-specific three-dimensional (3D) renal perfusion information. Between October 2020 and June 2022, 25 patients undergoing RAPN at Ghent University Hospital were included. Three-dimensional models, based on preoperative computed tomography (CT) scans, showed the clamped artery's ischemic zone, as calculated by the algorithm. All patients underwent selective clamping during RAPN. Indocyanine green (ICG) was administered to visualize the true ischemic zone perioperatively. Surgery was recorded for a postoperative analysis. The true ischemic zone of the clamped artery was compared with the ischemic zone predicted by the algorithm through two metrics: (1) total ischemic zone overlap and (2) tumor ischemic zone overlap. Six urologists assessed metric 1; metric 2 was assessed objectively by the authors. In 92% of the cases, the algorithm was sufficiently accurate to plan a selective clamping strategy. Metric 1 showed an average score of 4.28 out of 5. Metric 2 showed an average score of 4.14 out of 5. A first limitation is that ICG can be evaluated only at the kidney surface. A second limitation is that mainly patients with impaired renal function are expected to benefit from this technology, but contrast-enhanced CT is required at present. The proposed new tool demonstrated high accuracy when planning selective clamping for RAPN. A follow-up prospective study is needed to determine the tool's clinical added value. In partial nephrectomy, the surgeon has no information on which specific arterial branches perfuse the kidney tumor. We developed a surgeon support system that visualizes the perfusion zones of all arteries on a three-dimensional model and indicates the correct arteries to clamp. In this study, we validate this tool.

Sections du résumé

BACKGROUND
Selective clamping during robot-assisted partial nephrectomy (RAPN) requires extensive knowledge on patient-specific renal vasculature, obtained through imaging.
OBJECTIVE
To validate an in-house developed perfusion zone algorithm that provides patient-specific three-dimensional (3D) renal perfusion information.
DESIGN, SETTING, AND PARTICIPANTS
Between October 2020 and June 2022, 25 patients undergoing RAPN at Ghent University Hospital were included. Three-dimensional models, based on preoperative computed tomography (CT) scans, showed the clamped artery's ischemic zone, as calculated by the algorithm.
SURGICAL PROCEDURE
All patients underwent selective clamping during RAPN. Indocyanine green (ICG) was administered to visualize the true ischemic zone perioperatively. Surgery was recorded for a postoperative analysis.
MEASUREMENTS
The true ischemic zone of the clamped artery was compared with the ischemic zone predicted by the algorithm through two metrics: (1) total ischemic zone overlap and (2) tumor ischemic zone overlap. Six urologists assessed metric 1; metric 2 was assessed objectively by the authors.
RESULTS AND LIMITATIONS
In 92% of the cases, the algorithm was sufficiently accurate to plan a selective clamping strategy. Metric 1 showed an average score of 4.28 out of 5. Metric 2 showed an average score of 4.14 out of 5. A first limitation is that ICG can be evaluated only at the kidney surface. A second limitation is that mainly patients with impaired renal function are expected to benefit from this technology, but contrast-enhanced CT is required at present.
CONCLUSIONS
The proposed new tool demonstrated high accuracy when planning selective clamping for RAPN. A follow-up prospective study is needed to determine the tool's clinical added value.
PATIENT SUMMARY
In partial nephrectomy, the surgeon has no information on which specific arterial branches perfuse the kidney tumor. We developed a surgeon support system that visualizes the perfusion zones of all arteries on a three-dimensional model and indicates the correct arteries to clamp. In this study, we validate this tool.

Identifiants

pubmed: 36737298
pii: S0302-2838(23)00002-7
doi: 10.1016/j.eururo.2023.01.003
pii:
doi:

Substances chimiques

Indocyanine Green IX6J1063HV

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

413-421

Informations de copyright

Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Pieter De Backer (P)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium; IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium; ORSI Academy, Melle, Belgium. Electronic address: pieter.de.backer@orsi.be.

Saar Vermijs (S)

IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium.

Charles Van Praet (C)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium.

Pieter De Visschere (P)

Department of Radiology and Nuclear Medicine, Ghent University Hospital, Ghent, Belgium.

Sarah Vandenbulcke (S)

IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium.

Angelo Mottaran (A)

ORSI Academy, Melle, Belgium; Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium.

Carlo A Bravi (CA)

ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy.

Camille Berquin (C)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium.

Edward Lambert (E)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium.

Stéphanie Dautricourt (S)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium.

Wouter Goedertier (W)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium.

Alexandre Mottrie (A)

ORSI Academy, Melle, Belgium; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium.

Charlotte Debbaut (C)

IBiTech-Biommeda, Department of Electronics and Information Systems, Faculty of Engineering and Architecture, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent, Ghent University, Ghent, Belgium.

Karel Decaestecker (K)

Department of Urology, ERN eUROGEN Accredited Centre, Ghent University Hospital, Ghent, Belgium; Department of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium; Department of Urology, AZ Maria Middelares Hospital, Ghent, Belgium.

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