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

European Radiology, vol. 32, pp. 5711–5718

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.

Authors 12

1. Lennard Wolff corresponding

   Erasmus MC

   Affiliation as printed

   Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands. l.wolff.1@erasmusmc.nl

   Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands

2. Simone M. Uniken Venema

   University Medical Center Utrecht

   Affiliation as printed

   Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands

3. Sven P. R. Luijten

   Erasmus MC

   Affiliation as printed

   Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands

4. Jeannette Hofmeijer

   Rijnstate Hospital

   Affiliation as printed

   Department of Neurology, Rijnstate Hospital, Arnhem, The Netherlands

5. Jasper M. Martens

   Rijnstate Hospital

   Affiliation as printed

   Department of Radiology, Rijnstate Hospital, Arnhem, The Netherlands

6. Marie Louise E. Bernsen

   Rijnstate Hospital

   Affiliation as printed

   Department of Radiology, Rijnstate Hospital, Arnhem, The Netherlands

7. Adriaan C.G.M. van Es Aachen Department of Radiology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands

8. Pieter Jan van Doormaal

   Erasmus MC

   Affiliation as printed

   Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands

9. Diederik W.J. Dippel

   Erasmus MC

   Affiliation as printed

   Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands

10. Wim H. van Zwam

    Maastricht University Medical Centre · Maastricht University

    Affiliation as printed

    Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands

11. Theo van Walsum

    Erasmus MC

    Affiliation as printed

    Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands

12. Aad van der Lugt

    Erasmus MC

    Affiliation as printed

    Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands