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Nair PJ, Pfaller MR, Dual SA, McElhinney DB, Ennis DB, Marsden AL. Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements. Ann Biomed Eng 2024; 52:1335-1346. [PMID: 38341399 DOI: 10.1007/s10439-024-03457-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/20/2024] [Indexed: 02/12/2024]
Abstract
Blood pressure gradient ( Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( ∼ 15 s computation time) compared to 3D simulations ( ∼ 30 h computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.
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Affiliation(s)
- Priya J Nair
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Martin R Pfaller
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Seraina A Dual
- Department of Biomedical Signaling and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Doff B McElhinney
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
| | - Daniel B Ennis
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Department of Radiology, Stanford University, Stanford, CA, USA
- Division of Radiology, VA Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Alison L Marsden
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA.
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA.
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
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Aslan S, Liu X, Wu Q, Mass P, Loke YH, Johnson J, Huddle J, Olivieri L, Hibino N, Krieger A. Virtual Planning and Patient-Specific Graft Design for Aortic Repairs. Cardiovasc Eng Technol 2024; 15:123-136. [PMID: 37985613 DOI: 10.1007/s13239-023-00701-2] [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: 10/19/2022] [Accepted: 11/07/2023] [Indexed: 11/22/2023]
Abstract
PURPOSE Patients presenting with coarctation of the aorta (CoA) may also suffer from co-existing transverse arch hypoplasia (TAH). Depending on the risks associated with the surgery and the severity of TAH, clinicians may decide to repair only CoA, and monitor the TAH to see if it improves as the patient grows. While acutely successful, eventually hemodynamics may become suboptimal if TAH is left untreated. The objective of this work aims to develop a patient-specific surgical planning framework for predicting and assessing postoperative outcomes of simple CoA repair and comprehensive repair of CoA and TAH. METHODS The surgical planning framework consisted of virtual clamp placement, stenosis resection, and design and optimization of patient-specific aortic grafts that involved geometrical modeling of the graft and computational fluid dynamics (CFD) simulation for evaluating various surgical plans. Time-dependent CFD simulations were performed using Windkessel boundary conditions at the outlets that were obtained from patient-specific non-invasive pressure and flow data to predict hemodynamics before and after the virtual repairs. We applied the proposed framework to investigate optimal repairs for six patients (n = 6) diagnosed with both CoA and TAH. Design optimization was performed by creating a combination of a tubular graft and a waterslide patch to reconstruct the aortic arch. The surfaces of the designed graft were parameterized to optimize the shape. RESULTS Peak systolic pressure drop (PSPD) and time-averaged wall shear stress (TAWSS) were used as performance metrics to evaluate surgical outcomes of various graft designs and implantation. The average PSPD improvements were 28% and 44% after the isolated CoA repair and comprehensive repair, respectively. Maximum values of TAWSS were decreased by 60% after CoA repair and further improved by 22% after the comprehensive repair. The oscillatory shear index was calculated and the values were confirmed to be in the normal range after the repairs. CONCLUSION The results showed that the comprehensive repair outperforms the simple CoA repair and may be more advantageous in the long term in some patients. We demonstrated that the surgical planning and patient-specific flow simulations could potentially affect the selection and outcomes of aorta repairs.
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Affiliation(s)
- Seda Aslan
- Department of Mechanical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA.
| | - Xiaolong Liu
- Department of Mechanical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
- Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, USA
| | - Qiyuan Wu
- Department of Mechanical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
| | - Paige Mass
- Division of Cardiology, Children's National Hospital, Washington, DC, USA
| | - Yue-Hin Loke
- Division of Cardiology, Children's National Hospital, Washington, DC, USA
| | | | | | - Laura Olivieri
- Division of Cardiology, Children's National Hospital, Washington, DC, USA
| | - Narutoshi Hibino
- Section of Cardiac Surgery, Department of Surgery, The University of Chicago Medicine, Chicago, IL, USA
| | - Axel Krieger
- Department of Mechanical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA
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Zhao TY, Johnson EMI, Elisha G, Halder S, Smith BC, Allen BD, Markl M, Patankar NA. Blood-wall fluttering instability as a physiomarker of the progression of thoracic aortic aneurysms. Nat Biomed Eng 2023; 7:1614-1626. [PMID: 38082182 DOI: 10.1038/s41551-023-01130-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 10/16/2023] [Indexed: 12/20/2023]
Abstract
The diagnosis of aneurysms is informed by empirically tracking their size and growth rate. Here, by analysing the growth of aortic aneurysms from first principles via linear stability analysis of flow through an elastic blood vessel, we show that abnormal aortic dilatation is associated with a transition from stable flow to unstable aortic fluttering. This transition to instability can be described by the critical threshold for a dimensionless number that depends on blood pressure, the size of the aorta, and the shear stress and stiffness of the aortic wall. By analysing data from four-dimensional flow magnetic resonance imaging for 117 patients who had undergone cardiothoracic imaging and for 100 healthy volunteers, we show that the dimensionless number is a physiomarker for the growth of thoracic ascending aortic aneurysms and that it can be used to accurately discriminate abnormal versus natural growth. Further characterization of the transition to blood-wall fluttering instability may aid the understanding of the mechanisms underlying aneurysm progression in patients.
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Affiliation(s)
- Tom Y Zhao
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
| | - Ethan M I Johnson
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Guy Elisha
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Sourav Halder
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Ben C Smith
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Bradley D Allen
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Michael Markl
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Neelesh A Patankar
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
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Nair PJ, Pfaller MR, Dual SA, McElhinney DB, Ennis DB, Marsden AL. Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with in vivo measurements. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.05.23295066. [PMID: 37732242 PMCID: PMC10508787 DOI: 10.1101/2023.09.05.23295066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Purpose Blood pressure gradient (Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0 D and 3 D deformable wall simulations. Methods Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17 ). 0 D simulations were performed first and used to tune boundary conditions and initialize 3 D simulations. Δ P across the CoA estimated using both 0 D and 3 D simulations were compared to invasive catheter-based pressure measurements for validation. Results The 0 D simulations were extremely efficient (~15 secs computation time) compared to 3 D simulations (~30 hrs computation time on a cluster). However, the 0 D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3 D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0 D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0 D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3 D simulations improved this to 88%. Conclusion Overall, a combined approach, using 0 D models to efficiently tune and launch 3 D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.
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Affiliation(s)
- Priya J. Nair
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Martin R. Pfaller
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Seraina A. Dual
- Department of Biomedical Signaling and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Doff B. McElhinney
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
| | - Daniel B. Ennis
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Department of Radiology, Stanford University, Stanford, CA, USA
- Division of Radiology, VA Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Alison L. Marsden
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics - Cardiology, Stanford University, Stanford, CA, USA
- Maternal and Child Health Research Institute, Stanford University, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
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Antonuccio MN, Mariotti A, Fanni BM, Capellini K, Capelli C, Sauvage E, Celi S. Effects of Uncertainty of Outlet Boundary Conditions in a Patient-Specific Case of Aortic Coarctation. Ann Biomed Eng 2021; 49:3494-3507. [PMID: 34431017 PMCID: PMC8671284 DOI: 10.1007/s10439-021-02841-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 07/20/2021] [Indexed: 12/22/2022]
Abstract
Computational Fluid Dynamics (CFD) simulations of blood flow are widely used to compute a variety of hemodynamic indicators such as velocity, time-varying wall shear stress, pressure drop, and energy losses. One of the major advances of this approach is that it is non-invasive. The accuracy of the cardiovascular simulations depends directly on the level of certainty on input parameters due to the modelling assumptions or computational settings. Physiologically suitable boundary conditions at the inlet and outlet of the computational domain are needed to perform a patient-specific CFD analysis. These conditions are often affected by uncertainties, whose impact can be quantified through a stochastic approach. A methodology based on a full propagation of the uncertainty from clinical data to model results is proposed here. It was possible to estimate the confidence associated with model predictions, differently than by deterministic simulations. We evaluated the effect of using three-element Windkessel models as the outflow boundary conditions of a patient-specific aortic coarctation model. A parameter was introduced to calibrate the resistances of the Windkessel model at the outlets. The generalized Polynomial Chaos method was adopted to perform the stochastic analysis, starting from a few deterministic simulations. Our results show that the uncertainty of the input parameter gave a remarkable variability on the volume flow rate waveform at the systolic peak simulating the conditions before the treatment. The same uncertain parameter had a slighter effect on other quantities of interest, such as the pressure gradient. Furthermore, the results highlight that the fine-tuning of Windkessel resistances is not necessary to simulate the post-stenting scenario.
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Affiliation(s)
- Maria Nicole Antonuccio
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
| | - Alessandro Mariotti
- Civil and Industrial Engineering Department, University of Pisa, Pisa, Italy
| | - Benigno Marco Fanni
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
- Information Engineering Department, University of Pisa, Pisa, Italy
| | - Katia Capellini
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy
- Information Engineering Department, University of Pisa, Pisa, Italy
| | - Claudio Capelli
- Institute of Cardiovascular Science, University College of London, London, UK
| | - Emilie Sauvage
- Institute of Cardiovascular Science, University College of London, London, UK
| | - Simona Celi
- BioCardioLab, Bioengineering Unit - Heart Hospital, Fondazione Toscana "G. Monasterio", Massa, Italy.
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