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Garzia S, Scarpolini MA, Mazzoli M, Capellini K, Monteleone A, Cademartiri F, Positano V, Celi S. Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107790. [PMID: 37708583 DOI: 10.1016/j.cmpb.2023.107790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 08/07/2023] [Accepted: 09/01/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large vessels, such as the thoracic aorta. However, the segmentation of 4D flow MRI data is a complex and time-consuming task. In recent years, neural networks have shown great accuracy in segmentation tasks if large datasets are provided. Unfortunately, in the context of 4D flow MRI, the availability of these data is limited due to its recent adoption in clinical settings. In this study, we propose a pipeline for generating synthetic thoracic aorta phase contrast magnetic resonance angiography (PCMRA) to expand the limited dataset of patient-specific PCMRA images, ultimately improving the accuracy of the neural network segmentation even with a small real dataset. METHODS The pipeline involves several steps. First, a statistical shape model is used to synthesize new artificial geometries to improve data numerosity and variability. Secondly, computational fluid dynamics simulations are employed to simulate the velocity fields and, finally, after a downsampling and a signal-to-noise and velocity limit adjustment in both frequency and spatial domains, volumes are obtained using the PCMRA formula. These synthesized volumes are used in combination with real-world data to train a 3D U-Net neural network. Different settings of real and synthetic data are tested. RESULTS Incorporating synthetic data into the training set significantly improved the segmentation performance compared to using only real data. The experiments with synthetic data achieved a DICE score (DS) value of 0.83 and a better target reconstruction with respect to the case with only real data (DS = 0.65). CONCLUSION The proposed pipeline demonstrated the ability to increase the dataset in terms of numerosity and variability and to improve the segmentation accuracy for the thoracic aorta using PCMRA.
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Affiliation(s)
- Simone Garzia
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy; Department of Information Engineering, University of Pisa, Via Caruso, Pisa, 56122, Italy
| | - Martino Andrea Scarpolini
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy; Department of Industrial Engineering, University of Rome "Tor Vergata", Via del Politecnico, Roma, 00133, Italy
| | - Marilena Mazzoli
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy; Department of Information Engineering, University of Pisa, Via Caruso, Pisa, 56122, Italy
| | - Katia Capellini
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy
| | - Angelo Monteleone
- Department of Radiology, Fondazione Toscana G Monasterio, Via Moruzzi, Pisa, 56122, Italy
| | - Filippo Cademartiri
- Department of Radiology, Fondazione Toscana G Monasterio, Via Moruzzi, Pisa, 56122, Italy
| | - Vincenzo Positano
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy
| | - Simona Celi
- BioCardioLab, UOC Bioingegneria, Fondazione Toscana G Monasterio, Via Aurelia Sud, Massa, 54100, Italy.
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Mariotti A, Celi S, Antonuccio MN, Salvetti MV. Impact of the Spatial Velocity Inlet Distribution on the Hemodynamics of the Thoracic Aorta. Cardiovasc Eng Technol 2023; 14:713-725. [PMID: 37726567 DOI: 10.1007/s13239-023-00682-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 09/01/2023] [Indexed: 09/21/2023]
Abstract
The impact of the distribution in space of the inlet velocity in the numerical simulations of the hemodynamics in the thoracic aorta is systematically investigated. A real healthy aorta geometry, for which in-vivo measurements are available, is considered. The distribution is modeled through a truncated cone shape, which is a suitable approximation of the real one downstream of a trileaflet aortic valve during the systolic part of the cardiac cycle. The ratio between the upper and the lower base of the truncated cone and the position of the center of the upper base are selected as uncertain parameters. A stochastic approach is chosen, based on the generalized Polynomial Chaos expansion, to obtain accurate response surfaces of the quantities of interest in the parameter space. The selected parameters influence the velocity distribution in the ascending aorta. Consequently, effects on the wall shear stress are observed, confirming the need to use patient-specific inlet conditions if interested in the hemodynamics of this region. The surface base ratio is globally the most important parameter. Conversely, the impact on the velocity and wall shear stress in the aortic arch and descending aorta is almost negligible.
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Affiliation(s)
- Alessandro Mariotti
- Civil and Industrial Engineering Department, University of Pisa, Largo Lucio Lazzarino, 2, 56122, Pisa, Italy
| | - Simona Celi
- BioCardioLab, Bioengineering Unit, Heart Hospital, Fondazione CNR - Regione Toscana G. Monasterio, Via Aurelia Sud, 54100, Massa, Italy.
| | - Maria Nicole Antonuccio
- BioCardioLab, Bioengineering Unit, Heart Hospital, Fondazione CNR - Regione Toscana G. Monasterio, Via Aurelia Sud, 54100, Massa, Italy
| | - Maria Vittoria Salvetti
- Civil and Industrial Engineering Department, University of Pisa, Largo Lucio Lazzarino, 2, 56122, Pisa, Italy
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Scarpolini MA, Mazzoli M, Celi S. Enabling supra-aortic vessels inclusion in statistical shape models of the aorta: a novel non-rigid registration method. Front Physiol 2023; 14:1211461. [PMID: 37637150 PMCID: PMC10450506 DOI: 10.3389/fphys.2023.1211461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 07/11/2023] [Indexed: 08/29/2023] Open
Abstract
Statistical Shape Models (SSMs) are well-established tools for assessing the variability of 3D geometry and for broadening a limited set of shapes. They are widely used in medical imaging due to their ability to model complex geometries and their high efficiency as generative models. The principal step behind these techniques is a registration phase, which, in the case of complex geometries, can be a critical issue due to the correspondence problem, as it necessitates the development of correspondence mapping between shapes. The thoracic aorta, with its high level of morphological complexity, poses a multi-scale deformation problem due to the presence of several branch vessels with varying diameters. Moreover, branch vessels exhibit significant variability in shape, making the correspondence optimization even more challenging. Consequently, existing studies have focused on developing SSMs based only on the main body of the aorta, excluding the supra-aortic vessels from the analysis. In this work, we present a novel non-rigid registration algorithm based on optimizing a differentiable distance function through a modified gradient descent approach. This strategy enables the inclusion of custom, domain-specific constraints in the objective function, which act as landmarks during the registration phase. The algorithm's registration performance was tested and compared to an alternative Statistical Shape modeling framework, and subsequently used for the development of a comprehensive SSM of the thoracic aorta, including the supra-aortic vessels. The developed SSM was further evaluated against the alternative framework in terms of generalisation, specificity, and compactness to assess its effectiveness.
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Affiliation(s)
- Martino Andrea Scarpolini
- BioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, Ospedale del Cuore, Massa, Italy
- Department of Industrial Engineering, University of Rome “Tor Vergata”, Roma, Italy
| | - Marilena Mazzoli
- BioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, Ospedale del Cuore, Massa, Italy
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Simona Celi
- BioCardioLab, Bioengineering Unit, Fondazione Toscana G. Monasterio, Ospedale del Cuore, Massa, Italy
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Li X, Simakov S, Liu Y, Liu T, Wang Y, Liang F. The Influence of Aortic Valve Disease on Coronary Hemodynamics: A Computational Model-Based Study. Bioengineering (Basel) 2023; 10:709. [PMID: 37370640 DOI: 10.3390/bioengineering10060709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/31/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
Aortic valve disease (AVD) often coexists with coronary artery disease (CAD), but whether and how the two diseases are correlated remains poorly understood. In this study, a zero-three dimensional (0-3D) multi-scale modeling method was developed to integrate coronary artery hemodynamics, aortic valve dynamics, coronary flow autoregulation mechanism, and systemic hemodynamics into a unique model system, thereby yielding a mathematical tool for quantifying the influences of aortic valve stenosis (AS) and aortic valve regurgitation (AR) on hemodynamics in large coronary arteries. The model was applied to simulate blood flows in six patient-specific left anterior descending coronary arteries (LADs) under various aortic valve conditions (i.e., control (free of AVD), AS, and AR). Obtained results showed that the space-averaged oscillatory shear index (SA-OSI) was significantly higher under the AS condition but lower under the AR condition in comparison with the control condition. Relatively, the overall magnitude of wall shear stress was less affected by AVD. Further data analysis revealed that AS induced the increase in OSI in LADs mainly through its role in augmenting the low-frequency components of coronary flow waveform. These findings imply that AS might increase the risk or progression of CAD by deteriorating the hemodynamic environment in coronary arteries.
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Affiliation(s)
- Xuanyu Li
- Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Sergey Simakov
- Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow 119991, Russia
| | - Youjun Liu
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China
| | - Taiwei Liu
- Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yue Wang
- Department of Cardiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
| | - Fuyou Liang
- Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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Calò K, Capellini K, De Nisco G, Mazzi V, Gasparotti E, Gallo D, Celi S, Morbiducci U. Impact of wall displacements on the large-scale flow coherence in ascending aorta. J Biomech 2023; 154:111620. [PMID: 37178494 DOI: 10.1016/j.jbiomech.2023.111620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023]
Abstract
In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.
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Affiliation(s)
- Karol Calò
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy
| | - Katia Capellini
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
| | - Giuseppe De Nisco
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy
| | - Valentina Mazzi
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy
| | - Emanuele Gasparotti
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
| | - Diego Gallo
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy
| | - Simona Celi
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
| | - Umberto Morbiducci
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy; PoliTo(BIO)Med Lab, Politecnico di Torino, Turin, Italy.
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Hemodynamic Evaluation of a Centrifugal Left Atrial Decompression Pump for Heart Failure with Preserved Ejection Fraction. Bioengineering (Basel) 2023; 10:bioengineering10030366. [PMID: 36978757 PMCID: PMC10044772 DOI: 10.3390/bioengineering10030366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/08/2023] [Accepted: 03/12/2023] [Indexed: 03/19/2023] Open
Abstract
This article discusses a new continuous flow mini pump that has been developed to improve symptoms and prognosis in patients with Heart Failure with Preserved Ejection Fraction (HFpEF), for which there are currently no established treatments. The pump is designed to discharge a reduced percentage of blood volume from the left atrium to the subclavian artery, clamped at the bifurcation with the aortic arch. The overall specifications, design parameters, and hemodynamics of this new device are discussed, along with data from in vitro circulation loop tests and numerical simulations. The article also compares the results for two configurations of the pump with respect to key indicators of hemocompatibility used in blood pump development.
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Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls. J Cardiovasc Dev Dis 2023; 10:jcdd10030109. [PMID: 36975873 PMCID: PMC10058982 DOI: 10.3390/jcdd10030109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/15/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Introduction: Patient-specific computational models are a powerful tool for planning cardiovascular interventions. However, the in vivo patient-specific mechanical properties of vessels represent a major source of uncertainty. In this study, we investigated the effect of uncertainty in the elastic module (E) on a Fluid–Structure Interaction (FSI) model of a patient-specific aorta. Methods: The image-based χ-method was used to compute the initial E value of the vascular wall. The uncertainty quantification was carried out using the generalized Polynomial Chaos (gPC) expansion technique. The stochastic analysis was based on four deterministic simulations considering four quadrature points. A deviation of about ±20% on the estimation of the E value was assumed. Results: The influence of the uncertain E parameter was evaluated along the cardiac cycle on area and flow variations extracted from five cross-sections of the aortic FSI model. Results of stochastic analysis showed the impact of E in the ascending aorta while an insignificant effect was observed in the descending tract. Conclusions: This study demonstrated the importance of the image-based methodology for inferring E, highlighting the feasibility of retrieving useful additional data and enhancing the reliability of in silico models in clinical practice.
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Krzesiński P, Marczyk J, Wolszczak B, Gielerak GG, Accardi F. Quantitative Complexity Theory (QCT) in Integrative Analysis of Cardiovascular Hemodynamic Response to Posture Change. Life (Basel) 2023; 13:life13030632. [PMID: 36983787 PMCID: PMC10052206 DOI: 10.3390/life13030632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/19/2023] [Accepted: 02/22/2023] [Indexed: 03/30/2023] Open
Abstract
The explanation of physiological mechanisms involved in adaptation of the cardiovascular system to intrinsic and environmental demands is crucial for both basic science and clinical research. Computational algorithms integrating multivariable data that comprehensively depict complex mechanisms of cardiovascular reactivity are currently being intensively researched. Quantitative Complexity Theory (QCT) provides quantitative and holistic information on the state of multi-functional dynamic systems. The present paper aimed to describe the application of QCT in an integrative analysis of the cardiovascular hemodynamic response to posture change. Three subjects that underwent head-up tilt testing under beat-by-beat hemodynamic monitoring (impedance cardiography) were discussed in relation to the complexity trends calculated using QCT software. Complexity has been shown to be a sensitive marker of a cardiovascular hemodynamic response to orthostatic stress and vasodilator administration, and its increase has preceded changes in standard cardiovascular parameters. Complexity profiling has provided a detailed assessment of individual hemodynamic patterns of syncope. Different stimuli and complexity settings produce results of different clinical usability.
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Affiliation(s)
- Paweł Krzesiński
- Departament of Cardiology and Internal Diseases, Military Institute of Medicine, 04-141 Warsaw, Poland
| | | | | | - Grzegorz Gerard Gielerak
- Departament of Cardiology and Internal Diseases, Military Institute of Medicine, 04-141 Warsaw, Poland
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Antonuccio MN, Morales HG, This A, Capellini K, Avril S, Celi S, Rouet L. Towards the 2D velocity reconstruction in abdominal aorta from Color-Doppler Ultrasound. Med Eng Phys 2022; 107:103873. [DOI: 10.1016/j.medengphy.2022.103873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 08/02/2022] [Accepted: 08/05/2022] [Indexed: 10/16/2022]
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Introduction of a Novel Image-Based and Non-Invasive Method for the Estimation of Local Elastic Properties of Great Vessels. ELECTRONICS 2022. [DOI: 10.3390/electronics11132055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: In the context of a growing demand for the use of in silico models to meet clinical requests, image-based methods play a crucial role. In this study, we present a parametric equation able to estimate the elasticity of vessel walls, non-invasively and indirectly, from information uniquely retrievable from imaging. Methods: A custom equation was iteratively refined and tuned from the simulations of a wide range of different vessel models, leading to the definition of an indirect method able to estimate the elastic modulus E of a vessel wall. To test the effectiveness of the predictive capability to infer the E value, two models with increasing complexity were used: a U-shaped vessel and a patient-specific aorta. Results: The original formulation was demonstrated to deviate from the ground truth, with a difference of 89.6%. However, the adoption of our proposed equation was found to significantly increase the reliability of the estimated E value for a vessel wall, with a mean percentage error of 9.3% with respect to the reference values. Conclusion: This study provides a strong basis for the definition of a method able to estimate local mechanical information of vessels from data easily retrievable from imaging, thus potentially increasing the reliability of in silico cardiovascular models.
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The Hemodynamic Effect of Modified Blalock–Taussig Shunt Morphologies: A Computational Analysis Based on Reduced Order Modeling. ELECTRONICS 2022. [DOI: 10.3390/electronics11131930] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The Modified Blalock Taussig Shunt (MBTS) is one of the most common palliative operations in case of cyanotic heart diseases. Thus far, the decision on the position, size, and geometry of the implant relies on clinicians’ experience. In this paper, a Medical Digital Twin pipeline based on reduced order modeling is presented for fast and interactive evaluation of the hemodynamic parameters of MBTS. An infant case affected by complete pulmonary atresia was selected for this study. A three-dimensional digital model of the infant’s MBTS morphology was generated. A wide spectrum of MBTS geometries was explored by introducing twelve Radial Basis Function mesh modifiers. The combination of these modifiers allowed for analysis of various MBTS shapes. The final results proved the potential of the proposed approach for the investigation of significant hemodynamic features such as velocity, pressure, and wall shear stress as a function of the shunt’s morphology in real-time. In particular, it was demonstrated that the modifications of the MBTS morphology had a profound effect on the hemodynamic indices. The adoption of reduced models turned out to be a promising path to follow for MBTS numerical evaluation, with the potential to support patient-specific preoperative planning.
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He Y, Northrup H, Le H, Cheung AK, Berceli SA, Shiu YT. Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases. Front Bioeng Biotechnol 2022; 10:855791. [PMID: 35573253 PMCID: PMC9091352 DOI: 10.3389/fbioe.2022.855791] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 04/08/2022] [Indexed: 01/17/2023] Open
Abstract
Hemodynamic factors, induced by pulsatile blood flow, play a crucial role in vascular health and diseases, such as the initiation and progression of atherosclerosis. Computational fluid dynamics, finite element analysis, and fluid-structure interaction simulations have been widely used to quantify detailed hemodynamic forces based on vascular images commonly obtained from computed tomography angiography, magnetic resonance imaging, ultrasound, and optical coherence tomography. In this review, we focus on methods for obtaining accurate hemodynamic factors that regulate the structure and function of vascular endothelial and smooth muscle cells. We describe the multiple steps and recent advances in a typical patient-specific simulation pipeline, including medical imaging, image processing, spatial discretization to generate computational mesh, setting up boundary conditions and solver parameters, visualization and extraction of hemodynamic factors, and statistical analysis. These steps have not been standardized and thus have unavoidable uncertainties that should be thoroughly evaluated. We also discuss the recent development of combining patient-specific models with machine-learning methods to obtain hemodynamic factors faster and cheaper than conventional methods. These critical advances widen the use of biomechanical simulation tools in the research and potential personalized care of vascular diseases.
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Affiliation(s)
- Yong He
- Division of Vascular Surgery and Endovascular Therapy, University of Florida, Gainesville, FL, United States
| | - Hannah Northrup
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
| | - Ha Le
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
| | - Alfred K. Cheung
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
- Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, UT, United States
| | - Scott A. Berceli
- Division of Vascular Surgery and Endovascular Therapy, University of Florida, Gainesville, FL, United States
- Vascular Surgery Section, Malcom Randall Veterans Affairs Medical Center, Gainesville, FL, United States
| | - Yan Tin Shiu
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
- Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, UT, United States
- *Correspondence: Yan Tin Shiu,
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Special Issue of the VPH2020 Conference: "Virtual Physiological Human: When Models, Methods and Experiments Meet the Clinic". Ann Biomed Eng 2022; 50:483-484. [PMID: 35334017 DOI: 10.1007/s10439-022-02943-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 02/28/2022] [Indexed: 11/01/2022]
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Rowson B, Duma SM. Annals of Biomedical Engineering 2021 Year in Review. Ann Biomed Eng 2022; 50:361-364. [PMID: 35212856 DOI: 10.1007/s10439-022-02933-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 11/28/2022]
Affiliation(s)
- Bethany Rowson
- Institute for Critical Technology and Applied Science, Virginia Tech, Blacksburg, VA, USA.
| | - Stefan M Duma
- Institute for Critical Technology and Applied Science, Virginia Tech, Blacksburg, VA, USA
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