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Published in: European Radiology 8/2022

Open Access 04-03-2022 | Stroke | Imaging Informatics and Artificial Intelligence

Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography

Authors: Lennard Wolff, Simone M. Uniken Venema, Sven P. R. Luijten, Jeannette Hofmeijer, Jasper M. Martens, Marie Louise E. Bernsen, Adriaan C. G. M. van Es, Pieter Jan van Doormaal, Diederik W. J. Dippel, Wim van Zwam, Theo van Walsum, Aad van der Lugt, on behalf of the MR CLEAN Registry investigators

Published in: European Radiology | Issue 8/2022

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Abstract

Objectives

Outcome of endovascular treatment in acute ischemic stroke patients depends on collateral circulation to provide blood supply to the ischemic territory. We evaluated the performance of a commercially available algorithm for assessing the collateral score (CS) in acute ischemic stroke patients.

Methods

Retrospectively, baseline CTA scans (≤ 3-mm slice thickness) with an intracranial carotid artery (ICA), middle cerebral artery segment M1 or M2 occlusion, from the MR CLEAN Registry (n = 1627) were evaluated. All CTA scans were evaluated for visual CS (0–3) by eight expert radiologists (reference standard). A Web-based AI algorithm quantified the collateral circulation (0–100%) for correctly detected occlusion sides. Agreement between visual CS and categorized automated CS (0: 0%, 1: > 0– ≤ 50%, 2: > 50– < 100%, 3: 100%) was assessed. Area under the curve (AUC) values for classifying patients in having good (CS: 2–3) versus poor (CS: 0–1) collaterals and for predicting functional independence (90-day modified Rankin Scale 0–2) were computed. Influence of CTA acquisition timing after contrast material administration was reported.

Results

In the analyzed scans (n = 1024), 59% agreement was found between visual CS and automated CS. An AUC of 0.87 (95% CI: 0.85–0.90) was found for discriminating good versus poor CS. Timing of CTA acquisition did not influence discriminatory performance. AUC for predicting functional independence was 0.66 (95% CI 0.62–0.69) for automated CS, similar to visual CS 0.64 (95% CI 0.61–0.68).

Conclusions

The automated CS performs similar to radiologists in determining a good versus poor collateral score and predicting functional independence in acute ischemic stroke patients with a large vessel occlusion.

Key Points

Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in determining a good versus poor collateral score.
Software for automated quantification of intracerebral collateral circulation on computed tomography angiography performs similar to expert radiologists in predicting functional independence in acute ischemic stroke patients with a large vessel occlusion.
The timing of computed tomography angiography acquisition after contrast material administration did not influence the performance of automated quantification of the collateral status.
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Metadata
Title
Diagnostic performance of an algorithm for automated collateral scoring on computed tomography angiography
Authors
Lennard Wolff
Simone M. Uniken Venema
Sven P. R. Luijten
Jeannette Hofmeijer
Jasper M. Martens
Marie Louise E. Bernsen
Adriaan C. G. M. van Es
Pieter Jan van Doormaal
Diederik W. J. Dippel
Wim van Zwam
Theo van Walsum
Aad van der Lugt
on behalf of the MR CLEAN Registry investigators
Publication date
04-03-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 8/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08627-4

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