NON-INVASIVE DIAGNOSIS OF DEEP VEIN THROMBOSIS TO EXPEDITE TREATMENT AND PREVENT PULMONARY EMBOLISM DURING GESTATION

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作者
Maiti, Dolly [1 ]
Arunachalam, Shivaram P. [2 ]
机构
[1] Mayo Clin, Dept Cardiovasc Med, Rochester, MN USA
[2] Mayo Clin, Dept Med & Radiol, Rochester, MN USA
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Q813 [细胞工程];
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摘要
Deep vein thrombosis (DVT) is the formation of thrombosis or blood clot in the deep veins of the body, usually in the lower extremities or pelvic vein. During this time, a hypercoagulable state results in a higher rate of deep vein thrombosis (DVT) and pulmonary embolism (PE) during gestation and the postnatal stage. PE is the leading cause of maternal death, making early diagnosis and clinical treatment vital to both the mother's and fetal life. The current technologies for the diagnosis of DVT reduced detection accuracy with increased depth, false negatives when parallel veins are present, and the incompetence of imaging due to factors such as obesity and edema. The drawback of compression ultrasound is that clots may emboli during diagnosis and travel to vital organs such as the heart. In this study a new technological advancement is explored to superior diagnostic methods, and a near infrared device will be able to provide relative measurements of the oxygenation levels of calf veins and can help identify excessive deoxygenation and specific locations. Oxyhemoglobin & deoxyhemoglobin absorbs red light and infra-red lights differently. Oxygenated blood gets absorbed by IR light while deoxygenated gets transmitted. When infrared light is emitted onto a vein, it gets absorbed by the oxygenated hemoglobin and gives an absorbance ratio of output to the input close to 1. Infrared radiation spectroscopy measurements can indicate Delta 1/2HbO2 and Delta 1/2Hb to show a comparison, helping to indicate the presence or absence of a clot.. The circuit is designed with capacitors, resistors, and transistors to act as filters and triggers to pulsate at 20Hz, to pick up biological signals. An Arduino Uno microcontroller helped to process data in order to analyze signal proximity to 0 or 1 to classify DVT and validate the efficacy of using IR for DVT detection Testing of the device allowed for a functionality check to understand whether it was able to pick up signals of oxygenation levels. The 3 tests have insight on the potential of the device; however, the results were inconclusive, due to a lack of sufficient testing. The limitation has been the inability to test on a large sample size and insufficient data, therefore it can't be said for now whether IR is an effective way of diagnosing DVT. However, since on localized testing, the device seems to be gathering programmed signals, the research can be furthered, and the efficacy can be proved by testing on expecting patients.
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