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DOI 10.1016/j.ultrasmedbio.2017.11.010

Медицинская библиотека · Ultrasound in medicine & biology · 2017

Quantitative Analysis of Helical Flow with Accuracy Using Ultrasound Speckle Image Velocimetry: In Vitro and in Vivo Feasibility Studies.

Lee Sang Joon, Park Jun Hong, Kim Jeong Ju, Yeom Eunseop

Оценочное исследованиеСтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Venous valve dysfunction and induced secondary abnormal flows are closely associated with venous diseases. Thus, detailed analysis of venous valvular flow is invaluable from biological and medical perspectives. However, most of the previous studies on venous perivalvular flows were based on qualitative analysis. On the contrary, quantitative analysis of perivalvular flows has not been fully understood. In this study, we used the ultrasound speckle image velocimetry (SIV) technique, which utilizes the speckle patterns of red blood cells (RBCs) created by ultrasound waves to measure 3-D valvular flows quantitatively. The flow structures obtained with the proposed SIV technique for an in vitro model were compared with those obtained by numerical simulation and the color Doppler method to validate the measurement accuracy of the ultrasound SIV technique. Blood flow in the human great saphenous vein was then measured at various distances from the valve with and without exercise. 3-D valvular flow was analyzed in accordance with the dimensionless index, helical intensity. The results obtained by the proposed method matched well with those obtained by numerical simulation and the color Doppler method. The hemodynamic characteristics of 3-D valvular helical flow which were analyzed experimentally using the SIV method would be used for quantitative diagnosis of venous valvular diseases.

Для цитирования: Lee Sang Joon, Park Jun Hong, Kim Jeong Ju, Yeom Eunseop. Quantitative Analysis of Helical Flow with Accuracy Using Ultrasound Speckle Image Velocimetry: In Vitro and in Vivo Feasibility Studies.. Ultrasound in medicine & biology. 2017. DOI: 10.1016/j.ultrasmedbio.2017.11.010.

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