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.