ArticlePeerJ2026
Preliminary evaluation of a fractal-based collateral biomarker for thrombectomy candidate selection in acute ischemic stroke: a retrospective study.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Background: Collateral circulation plays a supportive role in stroke recovery, particularly among patients undergoing endovascular thrombectomy (EVT). While multiphase computed tomography angiography (mCTA)-based visual collateral scoring (vCS-mCTA) is widely used, its subjectivity and interobserver variability limit consistency. This preliminary study aimed to evaluate whether the mean fractal dimension ratio (mFD), derived from single-phase CTA (sCTA)-equivalent images, could serve as an objective and reproducible biomarker for collateral status assessment. Materials and Methods: This study retrospectively analyzed 54 patients with acute ischemic stroke who underwent EVT. The mFD was calculated using semi-automated fractal analysis of segmented vessels from the first phase of mCTA images. Collateral status was assessed using both sCTA and mCTA Menon visual scoring systems. The primary outcome was favorable 90-day functional status (modified Rankin Scale ≤ 2). Results: The sCTA-based visual collateral score (vCS-sCTA) was not significantly associated with clinical outcome. In contrast, higher mFD were significantly associated with favorable outcomes and demonstrated concordance with vCS-mCTA. In multivariable analysis, mFD remained an independent predictor after adjusting for clinical covariates. Its predictive performance was comparable to vCS-mCTA and superior to single-phase visual scoring. Conclusion: The mFD derived from sCTA-equivalent images may offer a practical and reproducible imaging biomarker for collateral assessment, offering predictive performance comparable to vCS-mCTA. As it does not rely on multiphase acquisition or subjective interpretation, mFD may enhance thrombectomy candidate selection, particularly in resource-limited or time-constrained settings.
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