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Fractal dimension (df) as a new structural biomarker of clot microstructure in different stages of lung cancer
Thrombosis and Haemostasis, Volume: 114, Issue: 6, Pages: 1251 - 1259
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Venous thromboembolism (VTE) is common in cancer patients, and is the second commonest cause of death associated with the disease. Patients with chronic inflammation, such as cancer, have been shown to have pathological clot structures with modulated mechanical properties. Fractal dimension (df) is...
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Venous thromboembolism (VTE) is common in cancer patients, and is the second commonest cause of death associated with the disease. Patients with chronic inflammation, such as cancer, have been shown to have pathological clot structures with modulated mechanical properties. Fractal dimension (df) is a new technique which has been shown to act as a marker of the microstructure and mechanical properties of blood clots, and can be performed more readily than current methods such as scanning electron microscopy (SEM). We measured df in 87 consecutive patients with newly diagnosed lung cancer prior to treatment and 47 matched-controls. Mean group values were compared for all patients with lung cancer vs controls and for limited disease vs extensive disease. Results were compared with conventional markers of coagulation, fibrinolysis and SEM images. Significantly higher values of df were observed in lung cancer patients compared with controls and patients with extensive disease had higher values than those with limited disease (p< 0.05), whilst conventional markers failed to distinguish between these groups. The relationship between df of the incipient clot and mature clot microstructure was confirmed by SEM and computational modelling: higher df was associated with highly dense clots formed of smaller fibrin fibres in lung cancer patients compared to controls. This study demonstrates that df is a sensitive technique which quantifies the structure and mechanical properties of blood clots in patients with lung cancer. Our data suggests that df has the potential to identify patients with an abnormal clot micro-structure and greatest VTE risk.
Swansea University Medical School