Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.


Journal

Journal of neurointerventional surgery
ISSN: 1759-8486
Titre abrégé: J Neurointerv Surg
Pays: England
ID NLM: 101517079

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 11 08 2020
revised: 26 10 2020
accepted: 03 11 2020
pubmed: 22 11 2020
medline: 12 5 2021
entrez: 21 11 2020
Statut: ppublish

Résumé

Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographic criteria. Consecutive patients with ≥6 months follow-up were included from 2008 to 2019 and retrospectively analyzed. Each IA was evaluated using the Raymond-Roy occlusion classification (RROC) and dichotomized as occluded (A) or residual (B/C); 80% of patients were randomly assigned to the training sample. Feature selection and binary outcome prediction relied on logistic regression and threshold maximizing class separation selected by a CART tree algorithm. The feature selection was addressed by a genetic algorithm selected from the 30 pretreatment available variables. The study included 146 patients with 154 IAs. Feature selection yielded a combination of six variables with a good cross-validated accuracy on the test sample, a combination we labeled DIANES score (IA diameter, indication, parent artery diameter ratio, neck ratio, side-branch artery, and sex). A score of more than -6 maximized the ability to predict RROC=A with sensitivity of 87% (95% CI 79% to 95%) and specificity of 82% (95% CI 64% to 96%) in the training sample. Accuracy was 86% (95% CI 79% to 94%). In the test sample, sensitivity and specificity were 89% (95% CI 77% to 98%) and 60% (95% CI 33% to 86%), respectively. Accuracy was 81% (95% CI 69% to 91%). A score was developed as a grading scale for prediction of the final occlusion status of IAs treated with a flow-diverter stent.

Sections du résumé

BACKGROUND BACKGROUND
Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographic criteria.
METHODS METHODS
Consecutive patients with ≥6 months follow-up were included from 2008 to 2019 and retrospectively analyzed. Each IA was evaluated using the Raymond-Roy occlusion classification (RROC) and dichotomized as occluded (A) or residual (B/C); 80% of patients were randomly assigned to the training sample. Feature selection and binary outcome prediction relied on logistic regression and threshold maximizing class separation selected by a CART tree algorithm. The feature selection was addressed by a genetic algorithm selected from the 30 pretreatment available variables.
RESULTS RESULTS
The study included 146 patients with 154 IAs. Feature selection yielded a combination of six variables with a good cross-validated accuracy on the test sample, a combination we labeled DIANES score (IA diameter, indication, parent artery diameter ratio, neck ratio, side-branch artery, and sex). A score of more than -6 maximized the ability to predict RROC=A with sensitivity of 87% (95% CI 79% to 95%) and specificity of 82% (95% CI 64% to 96%) in the training sample. Accuracy was 86% (95% CI 79% to 94%). In the test sample, sensitivity and specificity were 89% (95% CI 77% to 98%) and 60% (95% CI 33% to 86%), respectively. Accuracy was 81% (95% CI 69% to 91%).
CONCLUSION CONCLUSIONS
A score was developed as a grading scale for prediction of the final occlusion status of IAs treated with a flow-diverter stent.

Identifiants

pubmed: 33219150
pii: neurintsurg-2020-016748
doi: 10.1136/neurintsurg-2020-016748
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

341-346

Informations de copyright

© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: FC reports conflict of interest with Medtronic, Guerbet, Balt Extrusion (payment for readings), Codman Neurovascular (core lab). NS is consultant for Medtronic, Balt Extrusion, Microvention, Stock/Stock Options: Medina. The other authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper. The manuscript is not supported by industry.

Auteurs

Alexis Guédon (A)

Biosurgical Research Lab (Carpentier Foundation), European Georges-Pompidou Hospital, INSERM UMR_S 1140, University of Paris, Paris, France.
Department of Anatomy, University of Paris, Paris, France.

Cédric Thépenier (C)

French Armed Forces Biomedical Research Institute (IRBA), Brétigny-sur-Orge, France.
Department of Experimental Neuropathology, Institut Pasteur, Paris, France.

Eimad Shotar (E)

Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.

Joseph Gabrieli (J)

Department of Neuroradiology, University of Padova Faculty of Medicine and Surgery, Padova, Veneto, Italy.

Bertrand Mathon (B)

Department of Neurosurgery, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
Sorbonne University, Paris, Île-de-France, France.

Kévin Premat (K)

Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
Sorbonne University, Paris, Île-de-France, France.

Stéphanie Lenck (S)

Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.

Vincent Degos (V)

Sorbonne University, Paris, Île-de-France, France.
Department of Neuro-anesthesiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.

Nader Sourour (N)

Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.

Frédéric Clarençon (F)

Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France frederic.clarencon@aphp.fr.
Sorbonne University, Paris, Île-de-France, France.

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