Characterizing Clot Composition and Stroke Etiology Through Hounsfield Unit Analysis (P10-5.021)

Alexander Van Dam; Andres Gudino; Carlos Dier; Martin Cabarique; Elena Sagues; Arshaq Saleem; Navami Shenoy; Malik Ghannam; Edgar Samaniego

doi:10.1212/WNL.0000000000217694

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Characterizing Clot Composition and Stroke Etiology Through Hounsfield Unit Analysis (P10-5.021)

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Characterizing Clot Composition and Stroke Etiology Through Hounsfield Unit Analysis (P10-5.021)

Alexander Van Dam, Andres Gudino, Carlos Dier, Martin Cabarique, Elena Sagues, Arshaq Saleem, Navami Shenoy, Malik Ghannam and Edgar Samaniego

Neurology, Vol.106(11_Supplement_1)

06/09/2026

DOI: 10.1212/WNL.0000000000217694

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Abstract

Objective Analyze clot composition using Hounsfield units (HU) in non-enhanced computed tomography (NECT). Background Clot composition might offer insights about ischemic stroke mechanism. Hounsfield units (HU) characterizes tissues densities in non-enhanced computed tomography (NECT). Design/Methods A first phase involved a prospective cohort analyzing HU with histological composition of thrombus retrieved following mechanical thrombectomy (MT). The thrombi were imaged on micro-computed tomography (micro-CT) and subsequently analyzed histologically. Micro-CT slides were matched to histological sections. Regions composed of red blood cells (RBCs) and fibrin were isolated, and corresponding HU values were retrieved. Spearman’s rank correlation was performed to correlate micro-CT HU with percentage composition. The same clots were localized in the pre-MT NECT and NECT HU were obtained. Micro-CT HU and NECT HU were correlated to enable histologically-informed interpretation. Receiver operating characteristic analysis was performed to assess the accuracy of NECT HU in analyzing clot composition. In a second phase, a retrospective large dataset of NECT images of patients with different stroke etiologies were assessed using NECT HU. Results Ten clots were analyzed. Micro-CT HU were correlated with histological sections with >70% of RBCs (Rho 0.675) and with NECT HU of clots that had > 70% of RBCs (Rho 0.774). NECT HU of 44 had a sensitivity of 100% and specificity of 86% to determine clots with > 70% of RBCs composition in NECT. Consequently, 150 NECT images were analyzed including 50 cardioembolic, 50 large artery atherosclerosis (LAA) and 50 cryptogenic strokes. HU assessment showed that 74% cardioembolic, 32% LAA and 48% of cryptogenic clots had RBCs as main component. Conclusions NECT HU is promising to assess clot composition in NECT.

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Title: Subtitle: Characterizing Clot Composition and Stroke Etiology Through Hounsfield Unit Analysis (P10-5.021)
Creators: Alexander Van Dam - University of Iowa
Andres Gudino - University of Iowa Hospitals and Clinics
Carlos Dier - University of Iowa Hospitals and Clinics
Martin Cabarique - University of Iowa Hospitals and Clinics
Elena Sagues - University of Iowa Hospitals and Clinics
Arshaq Saleem - University of Iowa
Navami Shenoy - University of Iowa
Malik Ghannam - University of Iowa
Edgar Samaniego - University of Iowa
Resource Type: Abstract
Publication Details: Neurology, Vol.106(11_Supplement_1)
DOI: 10.1212/WNL.0000000000217694
ISSN: 0028-3878
eISSN: 1526-632X
Language: English
Date published: 06/09/2026
Academic Unit: Neurology; Radiology; Iowa Neuroscience Institute; Neurosurgery
Record Identifier: 9985180969302771

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