Vascular Cross‐Section, Rather Than Tortuosity, Can Classify First‐Pass Outcome of Mechanical Thrombectomy for Ischemic Stroke

Author:

Mousavi Janbeh Sarayi Seyyed Mostafa12,Santo Briana A.134,Waqas Muhammad135,Monterio Andre15,Veeturi Sricharan S.12,Jenkins TaJania D.14,Levy Elad I.15,Siddiqui Adnan H.15,Tutino Vincent M.12345

Affiliation:

1. Canon Stroke and Vascular Research Center University at Buffalo Buffalo NY

2. Department of Mechanical and Aerospace Engineering University at Buffalo Buffalo NY

3. Department of Biomedical Engineering University at Buffalo Buffalo NY

4. Department of Pathology and Anatomical Sciences University at Buffalo Buffalo NY

5. Department of Neurosurgery University at Buffalo Buffalo NY

Abstract

Background Vascular geometry plays an important role in stroke thrombectomy outcomes, but few studies have examined complex characteristics of vessel morphology. The authors hypothesized that engineered vessel cross‐section features could be used to predict thrombectomy first‐pass effect (FPE). Methods The authors analyzed computed tomography angiography and noncontrast computed tomagraphy from 50 patients with anterior circulation stroke thrombectomy. After segmentation, traditional metrics (vessel tortuosity and angulation) were calculated from vessel centerlines that were transformed into the same coordinate system and same region of interest. Univariate statistical analysis and geometric morphometrics were used to interrogate differences in geometry between cases that did and did not achieve FPE, which classical angulation and tortuosity did not quantify. To describe these differences, complex cross‐section features were engineered and quantified using a semiautomatic pipeline. Machine learning was used to train predictive models of FPE based on significant cross‐section features. Results Only one local tortuosity metric was significantly different ( q =0.019) between FPE and first‐pass failure cases. The most significant principal component score ( q =0.012) from geometric morphometrics highlighted the M1 segment of the middle cerebral artery and upper cavernous internal carotid artery variation as morphological indicators of first‐pass outcome. Fifteen cross‐section features, corresponding to internal carotid artery and middle cerebral artery regions, were significantly different between cases that did and did not achieve FPE. Predictive models exhibited a strong prediction of FPE (area under the curve=0.98±0.05) and outperformed models using traditional tortuosity and angulation features. Conclusion Cross‐section features are a novel class of powerful and interpretable predictors of FPE, which could assist in treatment decision‐making.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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