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Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Sufficient collateral blood supply is crucial for favorable outcomes with endovascular treatment. The current practice of collateral scoring relies on visual inspection and thus can suffer from inter and intra-rater inconsistency. We present a robust and automatic method to score cerebral collateral blood supply to aid ischemic stroke treatment decision making. The developed method is based on 4D dynamic CT angiography (CTA) and the ASPECTS scoring protocol.

Methods

The proposed method, ACCESS (Automatic Collateral Circulation Evaluation in iSchemic Stroke), estimates a target patient’s unfilled cerebrovasculature in contrast-enhanced CTA using the lack of contrast agent due to clotting. To do so, the fast robust matrix completion algorithm with in-face extended Frank–Wolfe optimization is applied on a cohort of healthy subjects and a target patient, to model the patient’s unfilled vessels and the estimated full vasculature as sparse and low-rank components, respectively. The collateral score is computed as the ratio of the unfilled vessels to the full vasculature, mimicking existing clinical protocols.

Results

ACCESS was tested with 46 stroke patients and obtained an overall accuracy of 84.78%. The optimal threshold selection was evaluated using a receiver operating characteristics curve with the leave-one-out approach, and a mean area under the curve of 85.39% was obtained.

Conclusion

ACCESS automates collateral scoring to mitigate the shortcomings of the standard clinical practice. It is a robust approach, which resembles how radiologists score clinical scans, and can be used to help radiologists in clinical decisions of stroke treatment.

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Notes

  1. http://www.world-heart-federation.org/cardiovascular-health/stroke/.

  2. http://www.stnava.github.io/ANTs.

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Acknowledgements

This study was funded by NSERC Discovery Grant RGPIN 04136 and Fonds de recherche du Quebec—Nature et technologies (FRQNT Grant F01296). The author Y. Xiao is supported by BrainsCAN and CIHR fellowships. We would like to thank Dr. Ali Alamer and Dr. Johanna Ortiz Jimenez for facilitating data acquisition and annotation.

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Authors and Affiliations

  1. Department of Computer Science and Software Engineering, Concordia University, 1455 boul. De Maisonneuve O., Montreal, Québec, H3G 1M8, Canada

    Mumu Aktar & Marta Kersten-Oertel

  2. Department of Diagnostic Radiology, Kingston Health Sciences Centre, Kingston General Hospital, Kingston, Ontario, K7L 2V7, Canada

    Donatella Tampieri

  3. Department of Electrical and Computer Engineering, Concordia University, 1455 boul. De Maisonneuve O., Montreal, Québec, H3G 1M8, Canada

    Hassan Rivaz

  4. Robarts Research Institute, Western University, London, Ontario, N6A 5B7, Canada

    Yiming Xiao

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  1. Mumu Aktar
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  2. Donatella Tampieri
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  3. Hassan Rivaz
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  4. Marta Kersten-Oertel
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  5. Yiming Xiao
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Correspondence to Mumu Aktar.

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Aktar, M., Tampieri, D., Rivaz, H. et al. Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition. Int J CARS 15, 1501–1511 (2020). https://doi.org/10.1007/s11548-020-02216-w

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