Novel Software-Derived Workflow in Extracranial-Intracranial Bypass Surgery Validated by Transdural Indocyanine Green Videoangiography.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
Feb 2020
Historique:
received: 24 08 2019
revised: 05 11 2019
accepted: 06 11 2019
pubmed: 17 11 2019
medline: 11 3 2020
entrez: 17 11 2019
Statut: ppublish

Résumé

The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial-intracranial (EC-IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA). We performed a retrospective review at a single tertiary referral center from 2011 to 2018. A novel software-derived workflow was applied for 25 of 92 bypass procedures during the study period. The precision and accuracy were assessed using tICG-VA identification of the cortical recipients and a comparison of the virtual and actual data. The data from a control group of 25 traditionally planned procedures were also matched. The intraoperative transfer time of the calculated coordinates averaged 0.8 minute (range, 0.4-1.9 minutes). The definitive recipients matched the targeted branches in 80%, and a neighboring branch was used in 16%. Our workflow led to a significant craniotomy size reduction in the study group compared with that in the control group (P = 0.005). tICG-VA was successfully applied in 19 cases. An average of 2 potential recipient arteries were identified transdurally, resulting in tailored durotomy and 3 craniotomy adjustments. Follow-up patency results were available for 49 bypass surgeries, comprising 54 grafts. The overall patency rate was 91% at a median follow-up period of 26 months. No significant difference was found in the patency rate between the study and control groups (P = 0.317). Our clinical results have validated the presented planning and surgical workflow and support the routine implementation of tICG-VA for recipient identification before durotomy.

Sections du résumé

BACKGROUND BACKGROUND
The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial-intracranial (EC-IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA).
METHODS METHODS
We performed a retrospective review at a single tertiary referral center from 2011 to 2018. A novel software-derived workflow was applied for 25 of 92 bypass procedures during the study period. The precision and accuracy were assessed using tICG-VA identification of the cortical recipients and a comparison of the virtual and actual data. The data from a control group of 25 traditionally planned procedures were also matched.
RESULTS RESULTS
The intraoperative transfer time of the calculated coordinates averaged 0.8 minute (range, 0.4-1.9 minutes). The definitive recipients matched the targeted branches in 80%, and a neighboring branch was used in 16%. Our workflow led to a significant craniotomy size reduction in the study group compared with that in the control group (P = 0.005). tICG-VA was successfully applied in 19 cases. An average of 2 potential recipient arteries were identified transdurally, resulting in tailored durotomy and 3 craniotomy adjustments. Follow-up patency results were available for 49 bypass surgeries, comprising 54 grafts. The overall patency rate was 91% at a median follow-up period of 26 months. No significant difference was found in the patency rate between the study and control groups (P = 0.317).
CONCLUSIONS CONCLUSIONS
Our clinical results have validated the presented planning and surgical workflow and support the routine implementation of tICG-VA for recipient identification before durotomy.

Identifiants

pubmed: 31733380
pii: S1878-8750(19)32874-8
doi: 10.1016/j.wneu.2019.11.038
pii:
doi:

Substances chimiques

Coloring Agents 0
Indocyanine Green IX6J1063HV

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e892-e902

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Philippe Dodier (P)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria. Electronic address: philippe.dodier@meduniwien.ac.at.

Thomas Auzinger (T)

Computer Graphics and Digital Fabrication Group, Institute of Science and Technology Austria, Klosterneuburg, Austria.

Gabriel Mistelbauer (G)

Institute for Simulation and Graphics, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.

Wei-Te Wang (WT)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria.

Heber Ferraz-Leite (H)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria.

Andreas Gruber (A)

University Clinic for Neurosurgery, Kepler University Hospital, Linz, Austria.

Wolfgang Marik (W)

Department of Radiology, Medical University Vienna, Vienna, Austria.

Fabian Winter (F)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria.

Gerrit Fischer (G)

Department of Neurosurgery, University Hospital of the Saarland and Medical Faculty of the University of the Saarland, Homburg, Germany.

Josa M Frischer (JM)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria.

Gerhard Bavinzski (G)

Department of Neurosurgery, Medical University Vienna, Vienna, Austria.

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Classifications MeSH