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PMID: 38759252 Published · ppublish English Journal Article

Modelling lower-limb peripheral arterial disease using clinically available datasets: impact of inflow boundary conditions on hemodynamic indices for restenosis prediction.

Computer methods and programs in biomedicine ·Vol. 251 ·2024-06-00 ·页码 108214

Ninno F, Chiastra C, Colombo M, Dardik A, Strosberg D, Aboian E, Tsui J, Bartlett M, Balabani S, Díaz-Zuccarini V

Abstract

The integration of hemodynamic markers as risk factors in restenosis prediction models for lower-limb peripheral arteries is hindered by fragmented clinical datasets. Computed tomography (CT) scans enable vessel geometry reconstruction and can be obtained at different times than the Doppler ultrasound (DUS) images, which provide information on blood flow velocity. Computational fluid dynamics (CFD) simulations allow the computation of near-wall hemodynamic indices, whose accuracy depends on the prescribed inlet boundary condition (BC), derived from the DUS images. This study aims to: (i) investigate the impact of different DUS-derived velocity waveforms on CFD results; (ii) test whether the same vessel areas, subjected to altered hemodynamics, can be detected independently of the applied inlet BC; (iii) suggest suitable DUS images to obtain reliable CFD results. CFD simulations were conducted on three patients treated with bypass surgery, using patient-specific DUS-derived inlet BCs recorded at either the same or different time points than the CT scan. The impact of the chosen inflow condition on bypass hemodynamics was assessed in terms of wall shear stress (WSS)-derived quantities. Patient-specific critical thresholds for the hemodynamic indices were applied to identify critical luminal areas and compare the results with a reference obtained with a DUS image acquired in close temporal proximity to the CT scan. The main findings indicate that: (i) DUS-derived inlet velocity waveforms acquired at different time points than the CT scan led to statistically significantly different CFD results (p<0.001); (ii) the same luminal surface areas, exposed to low time-averaged WSS, could be identified independently of the applied inlet BCs; (iii) similar outcomes were observed for the other hemodynamic indices if the prescribed inlet velocity waveform had the same shape and comparable systolic acceleration time to the one recorded in close temporal proximity to the CT scan. Despite a lack of standardised data collection for diseased lower-limb peripheral arteries, an accurate estimation of luminal areas subjected to altered near-wall hemodynamics is possible independently of the applied inlet BC. This holds if the applied inlet waveform shares some characteristics - derivable from the DUS report - as one matching the acquisition time of the CT scan.

Keywords
Computational fluid dynamics Doppler ultrasound Inlet boundary conditions Peripheral arterial disease Topological skeleton Uncertainty quantification Wall shear stress
MeSH 主题词
Humans Hemodynamics Peripheral Arterial Disease/physiopathology,diagnostic imaging Lower Extremity/blood supply,diagnostic imaging,physiopathology Computer Simulation Blood Flow Velocity Models, Cardiovascular Tomography, X-Ray Computed Hydrodynamics Ultrasonography, Doppler Stress, Mechanical
作者与单位
共 10 位作者,点击展开单位 / ORCID
Ninno Federica
Department of Medical Physics and Biomedical Engineering, University College London, London, UK; Wellcome-EPSRC Centre for Interventional Surgical Sciences, London, UK.
Chiastra Claudio
Polito(BIO)Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
Colombo Monika
Department of Mechanical and Production Engineering, Aarhus University, Aarhus, Denmark.
Dardik Alan
Vascular Biology and Therapeutics, Yale University School of Medicine, New Haven, Connecticut, USA; Division of Vascular Surgery and Endovascular Therapy, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut, USA.
Strosberg David
Department of Surgery, VA Connecticut Healthcare Systems, West Haven, Connecticut, USA; Department of Vascular Surgery, Royal Free Hospital NHS Foundation Trust, London, UK.
Aboian Edouard
Department of Surgery, VA Connecticut Healthcare Systems, West Haven, Connecticut, USA.
Tsui Janice
Department of Vascular Surgery, Royal Free Hospital NHS Foundation Trust, London, UK; Division of Surgery & Interventional Science, Department of Surgical Biotechnology, Faculty of Medical Sciences, University College London, London, UK.
Bartlett Matthew
Division of Surgery & Interventional Science, Department of Surgical Biotechnology, Faculty of Medical Sciences, University College London, London, UK; Department of Mechanical Engineering, University College London, London, UK.
Balabani Stavroula
Wellcome-EPSRC Centre for Interventional Surgical Sciences, London, UK; Department of Mechanical Engineering, University College London, London, UK.
Díaz-Zuccarini Vanessa
Wellcome-EPSRC Centre for Interventional Surgical Sciences, London, UK; Department of Mechanical Engineering, University College London, London, UK. Electronic address: [email protected].
Article Info
Journal
Computer methods and programs in biomedicine
Abbr.
Comput Methods Programs Biomed
ISSN
1872-7565
Corresponding email
Published
2024-06-00
电子出版
2024-00-05
页码
108214
Language
English
Country/Region
Ireland
NLM ID
8506513
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