Simultaneous assessment of blood coagulation and hematocrit levels in dielectric blood coagulometry.

Background: In a whole blood coagulation test, the concentration of any in vitro diagnostic agent in plasma is dependent on the hematocrit level but its impact on the test result is unknown.

Objective: The aim of this work was to clarify the effects of reagent concentration, particularly Ca2+, and to find a method for hematocrit estimation compatible with the coagulation test.

Methods: Whole blood coagulation tests by dielectric blood coagulometry (DBCM) and rotational thromboelastometry were performed with various concentrations of Ca2+ or on samples with different hematocrit levels.

Principles of dielectric blood coagulometry as a comprehensive coagulation test.

Dielectric blood coagulometry (DBCM) is intended to support hemostasis management by providing comprehensive information on blood coagulation from automated, time-dependent measurements of whole blood dielectric spectra. We discuss the relationship between the series of blood coagulation reactions, especially the aggregation and deformation of erythrocytes, and the dielectric response with the help of clot structure electron microscope observations. Dielectric response to the spontaneous coagulation after recalcification presented three distinct phases that correspond to (P1) rouleau formation before the onset of clotting, (P2) erythrocyte aggregation and reconstitution of aggregates accompanying early fibrin formation, and (P3) erythrocyte shape transformation and/or structure changes within aggregates after the stable fibrin network is formed and platelet contraction occurs.

Contrast improvement of terahertz images of thin histopathologic sections.

We present terahertz images of 10 μm thick histopathologic sections obtained in reflection geometry with a time-domain spectrometer, and demonstrate improved contrast for sections measured in paraffin with water. Automated segmentation is applied to the complex refractive index data to generate clustered terahertz images distinguishing cancer from healthy tissues. The degree of classification of pixels is then evaluated using registered visible microscope images.