Journal of Cardiovascular Development and Disease (Mar 2024)

Thrombus Imaging Characteristics to Predict Early Recanalization in Anterior Circulation Large Vessel Occlusion Stroke

  • Nerea Arrarte Terreros,
  • Jeffrey Stolp,
  • Agnetha A. E. Bruggeman,
  • Isabella S. J. Swijnenburg,
  • Ricardo R. Lopes,
  • Laura C. C. van Meenen,
  • Adrien E. D. Groot,
  • Manon Kappelhof,
  • Jonathan M. Coutinho,
  • Yvo B. W. E. M. Roos,
  • Bart J. Emmer,
  • Ludo F. M. Beenen,
  • Diederik W. J. Dippel,
  • Wim H. van Zwam,
  • Ed van Bavel,
  • Henk A. Marquering,
  • Charles B. L. M. Majoie

DOI
https://doi.org/10.3390/jcdd11040107
Journal volume & issue
Vol. 11, no. 4
p. 107

Abstract

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The early management of transferred patients with a large vessel occlusion (LVO) stroke could be improved by identifying patients who are likely to recanalize early. We aim to predict early recanalization based on patient clinical and thrombus imaging characteristics. We included 81 transferred anterior-circulation LVO patients with an early recanalization, defined as the resolution of the LVO or the migration to a distal location not reachable with endovascular treatment upon repeated radiological imaging. We compared their clinical and imaging characteristics with all (322) transferred patients with a persistent LVO in the MR CLEAN Registry. We measured distance from carotid terminus to thrombus (DT), thrombus length, density, and perviousness on baseline CT images. We built logistic regression models to predict early recanalization. We validated the predictive ability by computing the median area-under-the-curve (AUC) of the receiver operating characteristics curve for 100 5-fold cross-validations. The administration of intravenous thrombolysis (IVT), longer transfer times, more distal occlusions, and shorter, pervious, less dense thrombi were characteristic of early recanalization. After backward elimination, IVT administration, DT and thrombus density remained in the multivariable model, with an AUC of 0.77 (IQR 0.72–0.83). Baseline thrombus imaging characteristics are valuable in predicting early recanalization and can potentially be used to optimize repeated imaging workflow.

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