

Femoro-popliteal 'by-pass' is indicated in the advanced stage of peripheral arterial occlusive disease. Indications for surgical treatment are set on the basis of the clinical picture, 'ankle-brachial index' and angiographic findings. By the method of finite element analysis, three-dimensional models can be made on the basis of scanning angiography, on which we can measure different physical quantities and calculate the value of the 'ankle-brachial index'. The aim is to show the hemodynamics of arteries by the method of finite element analysis (FEA) based on preoperative and postoperative scan angiography as well as physical quantities that can be measured in this way. In this review, the hemodynamics of femoro-popliteal 'by-pass' on the preoperative and postoperative model are presented. The models obtained by FEA show: pressure, shear stress, velocities, and streamlines. Pressure, 'ankle-brachial index', compared with the values measured on the patient, with FEA results preoperatively and postoperatively. Postoperatively, higher values of pressure and 'ankle-brachial index' were measured on the patient and on the models. The values shown in the models are significantly correlated with the values measured on the patient. Shear stress and velocity values are significantly reduced on postoperative models. The streamlines show a dominant anterior tibial artery. The values of physical quantities measured on the patient and on the models obtained by the FEA method correlate to a significant extent. © 2021 IEEE.
| Engineering controlled terms: | AngiographyHemodynamicsShear flowShear stressSurgery |
|---|---|
| Engineering uncontrolled terms | Ankle-brachial indicesBy passFemoro-popliteal by-passFinite element analyseFinite-element analysis methodsHaemodynamicsMethod of finite elementsPeripheral arterial occlusive diseasePhysical quantities |
| Engineering main heading: | Finite element method |
| Funding sponsor | Funding number | Acronym |
|---|---|---|
| Horizon 2020 Framework Programme See opportunities by H2020 | 952603 | H2020 |
| Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja | 451-03-9/2021-14/200378 | MPNTR |
ACKNOWLEDGMENT This research is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952603 (http://sgabu.eu/). This article reflects only the author's view. The Commission is not responsible for any use that may be made of the information it contains. The research is also funded by the Serbian Ministry of Education, Science and Technological Development [451-03-9/2021-14/200378 (Institute for Information Technologies, University of Kragujevac)].
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