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Updated: Mar 2, 2026

Leveraging Turbidity and Thromboelastography for Complementary Clot Characterization
Published on: June 4, 2020
Differentiation of Clot Composition Using Conventional and Dual-Energy Computed Tomography
Jan Borggrefe1, Jonathan Kottlors2, Mahmood Mirza3
1Institut für Diagnostische und Interventionelle Radiologie, Uniklinik Köln, Kerpener Str. 62, 60937, Cologne, Germany. Jan.Borggrefe@uk-koeln.de.
Background And Purpose:
In unenhanced computed tomography (CT) of acute ischemic stroke, the density of occluding clots is associated with the content of red blood cells and successful recanalization with stent thrombectomy. However, no CT marker for fibrin content is established. In order to improve clot diagnostics, we conducted an in vitro study to investigate thrombus composition of histologically defined ovine blood clots with unenhanced and contrast-enhanced CT using spectral detector CT (SDCT).
Methods:
Ovine blood clot types containing defined amounts of red blood cells (RBC; pure fibrin clots: RBC 0% ± 0, fibrin 100% ± 0), mixed clots (RBC 35.1% ± 4.11, fibrin 79.2% ± 5.6) and red clots (RBC 99.05% ± 1.14, fibrin 0.95% ± 1.14) were scanned in a SDCT (IQon®, Philips, Amsterdam, The Netherlands) (a) in a tube containing saline, (b) 5 min and (c) 3 days after exposure to a 1:50 dilution of iohexol (Accupaque-350®, GE-Healthcare, Boston, MA, USA). The attenuation of the clots was measured in Hounsfield units (HU) in conventional CT datasets as well as virtual noncontrast reconstructions (VNC) of nonenhanced and contrast-enhanced SDCT in a blinded and randomized fashion. Statistical analysis was conducted with ANOVA, Spearman's correlation, linear and multivariable regression models.
Results:
In unenhanced scans, clots differed in density with linear interrelation (fibrin 23.6 ± 1.1, mixed 34.9 ± 1.6, red 46.7 ± 1.6, mean HU ± SD). The blood clots did not show any overlap of density in the native scans and VNC at different time points (p < 0.0001 for each setting and clot type). However, they could not be differentiated after initial contrast exposure (fibrin 108.5 ± 7.8, mixed 105.3 ± 3.5, red 104.8 ± 3.8, mean HU ± SD). After prolonged exposure, the fibrin rich clots showed a significant increase of density due to further uptake of contrast medium (fibrin 163.6 ± 3.6, mixed 138.3 ± 4.1, red 109.6 ± 5.4, mean HU ± SD). In multivariable models, native CT density and contrast enhancement were independent variables associated with thrombus type (p < 0.01 each).
Conclusion:
The fibrin content in blood clots is strongly associated with contrast uptake. As previously shown, the density of the clot formations in native CT scans is dependent on the RBC. Our data show that CT density and relative enhancement of clots are independent determinants of clot composition. Using both variables in the CT workup of acute ischemic stroke has the potential to have a decisive impact on patient stratification for treatment.
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