BackgroundDuring the last decade, thromboelastography (TEG) has gained increasing acceptance as a diagnostic test in veterinary medicine for evaluation of haemostasis in dogs, however the use of TEG in cats has to date only been described in one previous study and a few abstracts. The objective of the present study was to evaluate and compare three different TEG assays in healthy cats, in order to establish which assay may be best suited for TEG analyses in cats.Methods90 TEG analyses were performed on citrated whole blood samples from 15 clinically healthy cats using assays without activator (native) or with human recombinant tissue factor (TF) or kaolin as activators. Results for reaction time (R), clotting time (K), angle (α), maximum amplitude (MA) and clot lysis (LY30; LY60) were recorded.ResultsCoefficients of variation (CVs) were highest in the native assay and comparable in TF and kaolin activated assays. Significant differences were observed between native and kaolin assays for all measured parameters, between kaolin and TF for all measured parameters except LY60 and between native and TF assays for R and K.ConclusionThe results indicate that TEG is a reproducible method for evaluation of haemostasis in clinically healthy cats. However, the three assays cannot be used interchangeably and the kaolin- and TF activated assays have the lowest analytical variation indicating that using an activator may be superior for performing TEG in cats.

There was a good aggregation response and acceptable analytical variation in both heparin- and hirudin-anticoagulated samples with all tested agonist at the concentrations recommended by the manufacturer. The results suggest that heparin may be superior as anticoagulant for Multiplate analyses in dogs and that short analyses times are preferable. Spontaneous platelet autoaggregation in hirudin samples warrants careful evaluation of results using this anticoagulant, especially at longer test times. The use of citrate is discouraged for Multiplate analyses in dogs due to a weak aggregation response.

A substantive influence of circulating serotonin on MMVD stages prior to CHF development in Cavalier King Charles Spaniels was not supported by the study findings. An FSSP of highly activated platelets with pronounced serotonin binding was strongly associated with thrombocytopenia but not MMVD.

BackgroundDiagnosis of pulmonary thromboembolism (PTE) in dogs relies on computed tomography pulmonary angiography (CTPA), but detailed interpretation of CTPA images is demanding for the radiologist and only large vessels may be evaluated. New approaches for better detection of smaller thrombi include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical classification analyses.CT images from healthy (n = 6) and diseased (n = 29) dogs with and without PTE confirmed on CTPA were segmented so that only tissue with CT numbers between −1024 and −250 Houndsfield Units (HU) was preserved. GLCM analysis and subsequent multivariate classification analyses were performed on texture parameters extracted from these images.ResultsLeave-one-dog-out cross validation and receiver operator characteristic (ROC) showed that the models generated from the texture analysis were able to predict healthy dogs with optimal levels of performance. Partial Least Square Discriminant Analysis (PLS-DA) obtained a sensitivity of 94% and a specificity of 96%, while Support Vector Machines (SVM) yielded a sensitivity of 99% and a specificity of 100%. The models, however, performed worse in classifying the type of disease in the diseased dog group: In diseased dogs with PTE sensitivities were 30% (PLS-DA) and 38% (SVM), and specificities were 80% (PLS-DA) and 89% (SVM). In diseased dogs without PTE the sensitivities of the models were 59% (PLS-DA) and 79% (SVM) and specificities were 79% (PLS-DA) and 82% (SVM).ConclusionThe results indicate that texture analysis of CTPA images using GLCM is an effective tool for distinguishing healthy from abnormal lung. Furthermore the texture of pulmonary parenchyma in dogs with PTE is altered, when compared to the texture of pulmonary parenchyma of healthy dogs. The models’ poorer performance in classifying dogs within the diseased group, may be related to the low number of dogs compared to texture variables, a lack of balanced number of dogs within each group or a real lack of difference in the texture features among the diseased dogs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12917-017-1117-1) contains supplementary material, which is available to authorized users.

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