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Ericsson L, Hjalmarsson A, Akbar MU, Ferdian E, Bonini M, Hardy B, Schollenberger J, Aristova M, Winter P, Burris N, Fyrdahl A, Sigfridsson A, Schnell S, Figueroa CA, Nordsletten D, Young AA, Marlevi D. Generalized super-resolution 4D Flow MRI-using ensemble learning to extend across the cardiovascular system. ARXIV 2023:arXiv:2311.11819v2. [PMID: 38045482 PMCID: PMC10690302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these efforts have predominantly been restricted to narrowly defined cardiovascular domains, with limited exploration of how SR performance extends across the cardiovascular system; a task aggravated by contrasting hemodynamic conditions apparent across the cardiovasculature. The aim of our study was to explore the generalizability of SR 4D Flow MRI using a combination of heterogeneous training sets and dedicated ensemble learning. With synthetic training data generated across three disparate domains (cardiac, aortic, cerebrovascular), varying convolutional base and ensemble learners were evaluated as a function of domain and architecture, quantifying performance on both in-silico and acquired in-vivo data from the same three domains. Results show that both bagging and stacking ensembling enhance SR performance across domains, accurately predicting high-resolution velocities from low-resolution input data in-silico. Likewise, optimized networks successfully recover native resolution velocities from downsampled in-vivo data, as well as show qualitative potential in generating denoised SR-images from clinicallevel input data. In conclusion, our work presents a viable approach for generalized SR 4D Flow MRI, with ensemble learning extending utility across various clinical areas of interest.
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Affiliation(s)
- Leon Ericsson
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Adam Hjalmarsson
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Muhammad Usman Akbar
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Edward Ferdian
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Mia Bonini
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Brandon Hardy
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Jonas Schollenberger
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Maria Aristova
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Patrick Winter
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Nicholas Burris
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Alexander Fyrdahl
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Andreas Sigfridsson
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Susanne Schnell
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - C Alberto Figueroa
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - David Nordsletten
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - Alistair A Young
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
| | - David Marlevi
- L.E., A.H., A.F., A.S., and D.M. are with Karolinska Institutet, Solna, Sweden. M.U.A. is with Linköping University, Linköping, Sweden. E.F. and A.A.Y. are with the University of Auckland, Auckland, New Zealand. M.B., B.H, N.B, C.A.F, and D.A.N. are with the University of Michigan, Ann Arbor, USA. J.S. is with the University of California San Francisco, San Francisco, CA, USA. M.A. ans S.S. are with Northwestern University, Chicago, USA. S.S. is also with the University of Greifswald, Germany. A.A.Y. is also with King's College London, London, UK. D.M. is also with Massachusetts Institute of Technology, Cambridge, USA
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Haslund LE, Jorgensen LT, Bo Stuart M, Traberg MS, Jensen JA. Precise Estimation of Intravascular Pressure Gradients. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:393-405. [PMID: 37028315 DOI: 10.1109/tuffc.2023.3255791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
This study presents a method for noninvasive pressure gradient estimation, which allows the detection of small pressure differences with higher precision compared to invasive catheters. It combines a new method for estimating the temporal acceleration of the flowing blood with the Navier-Stokes equation. The acceleration estimation is based on a double cross-correlation approach, which is hypothesized to minimize the influence of noise. Data are acquired using a 256-element, 6.5-MHz GE L3-12-D linear array transducer connected to a Verasonics research scanner. A synthetic aperture (SA) interleaved sequence with 2 ×12 virtual sources evenly distributed over the aperture and permuted in emission order is used in combination with recursive imaging. This enables a temporal resolution between correlation frames equal to the pulse repetition time at a frame rate of half the pulse repetition frequency. The accuracy of the method is evaluated against a computational fluid dynamic simulation. Here, the estimated total pressure difference complies with the CFD reference pressure difference, which yields an R -square of 0.985 and an RMSE of 3.03 Pa. The precision of the method is tested on experimental data, measured on a carotid phantom of the common carotid artery. The volume profile used during measurement was set to mimic flow in the carotid artery with a peak flow rate of 12.9 mL/s. The experimental setup showed that the measured pressure difference changes from -59.4 to 31 Pa throughout a single pulse cycle. This was estimated with a precision of 5.44% (3.22 Pa) across ten pulse cycles. The method was also compared to invasive catheter measurements in a phantom with a 60% cross-sectional area reduction. The ultrasound method detected a maximum pressure difference of 72.3 Pa with a precision of 3.3% (2.22 Pa). The catheters measured a maximum pressure difference of 105 Pa with a precision of 11.2% (11.4 Pa). This was measured over the same constriction and with a peak flow rate of 12.9 mL/s. The double cross-correlation approach revealed no improvement compared to a normal differential operator. The method's strength, thus, lies primarily in the ultrasound sequence, which allows precise and accurate velocity estimations, at which acceleration and pressure differences can be acquired.
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Ferdian E, Marlevi D, Schollenberger J, Aristova M, Edelman ER, Schnell S, Figueroa CA, Nordsletten DA, Young AA. Cerebrovascular super-resolution 4D Flow MRI - Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure. Med Image Anal 2023; 88:102831. [PMID: 37244143 DOI: 10.1016/j.media.2023.102831] [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: 12/09/2021] [Revised: 04/04/2023] [Accepted: 04/20/2023] [Indexed: 05/29/2023]
Abstract
The development of cerebrovascular disease is tightly coupled to regional changes in intracranial flow and relative pressure. Image-based assessment using phase contrast magnetic resonance imaging has particular promise for non-invasive full-field mapping of cerebrovascular hemodynamics. However, estimations are complicated by the narrow and tortuous intracranial vasculature, with accurate image-based quantification directly dependent on sufficient spatial resolution. Further, extended scan times are required for high-resolution acquisitions, and most clinical acquisitions are performed at comparably low resolution (>1 mm) where biases have been observed with regard to the quantification of both flow and relative pressure. The aim of our study was to develop an approach for quantitative intracranial super-resolution 4D Flow MRI, with effective resolution enhancement achieved by a dedicated deep residual network, and with accurate quantification of functional relative pressures achieved by subsequent physics-informed image processing. To achieve this, our two-step approach was trained and validated in a patient-specific in-silico cohort, showing good accuracy in estimating velocity (relative error: 15.0 ± 0.1%, mean absolute error (MAE): 0.07 ± 0.06 m/s, and cosine similarity: 0.99 ± 0.06 at peak velocity) and flow (relative error: 6.6 ± 4.7%, root mean square error (RMSE): 0.56 mL/s at peak flow), and with the coupled physics-informed image analysis allowing for maintained recovery of functional relative pressure throughout the circle of Willis (relative error: 11.0 ± 7.3%, RMSE: 0.3 ± 0.2 mmHg). Furthermore, the quantitative super-resolution approach is applied to an in-vivo volunteer cohort, effectively generating intracranial flow images at <0.5 mm resolution and showing reduced low-resolution bias in relative pressure estimation. Our work thus presents a promising two-step approach to non-invasively quantify cerebrovascular hemodynamics, being applicable to dedicated clinical cohorts in the future.
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Affiliation(s)
- E Ferdian
- University of Auckland, Auckland 1142 New Zealand
| | - D Marlevi
- Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | | | - M Aristova
- Northwestern University, Chicago, IL 60611, USA
| | - E R Edelman
- Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - S Schnell
- Northwestern University, Chicago, IL 60611, USA; University of Greifswald, Greifswald 17489, Germany
| | - C A Figueroa
- University of Michigan, Ann Arbor, MI 48109, USA
| | - D A Nordsletten
- University of Michigan, Ann Arbor, MI 48109, USA; King's College London, London, SE1 7EH, UK
| | - A A Young
- University of Auckland, Auckland 1142 New Zealand; King's College London, London, SE1 7EH, UK
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Zhu Y, Xu XY, Rosendahl U, Pepper J, Mirsadraee S. Advanced risk prediction for aortic dissection patients using imaging-based computational flow analysis. Clin Radiol 2023; 78:e155-e165. [PMID: 36610929 DOI: 10.1016/j.crad.2022.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/28/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022]
Abstract
Patients with either a repaired or medically managed aortic dissection have varying degrees of risk of developing late complications. High-risk patients would benefit from earlier intervention to improve their long-term survival. Currently serial imaging is used for risk stratification, which is not always reliable. On the other hand, understanding aortic haemodynamics within a dissection is essential to fully evaluate the disease and predict how it may progress. In recent decades, computational fluid dynamics (CFD) has been extensively applied to simulate complex haemodynamics within aortic diseases, and more recently, four-dimensional (4D)-flow magnetic resonance imaging (MRI) techniques have been developed for in vivo haemodynamic measurement. This paper presents a comprehensive review on the application of image-based CFD simulations and 4D-flow MRI analysis for risk prediction in aortic dissection. The key steps involved in patient-specific CFD analyses are demonstrated. Finally, we propose a workflow incorporating computational modelling for personalised assessment to aid in risk stratification and treatment decision-making.
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Affiliation(s)
- Y Zhu
- Department of Chemical Engineering, Imperial College London, London, UK
| | - X Y Xu
- Department of Chemical Engineering, Imperial College London, London, UK
| | - U Rosendahl
- Department of Cardiac Surgery, Royal Brompton and Harefield Hospitals, London, UK; National Heart and Lung Institute, Imperial College London, London, UK
| | - J Pepper
- Department of Cardiac Surgery, Royal Brompton and Harefield Hospitals, London, UK; National Heart and Lung Institute, Imperial College London, London, UK
| | - S Mirsadraee
- National Heart and Lung Institute, Imperial College London, London, UK; Department of Radiology, Royal Brompton and Harefield Hospitals, London, UK.
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Long D, McMurdo C, Ferdian E, Mauger CA, Marlevi D, Nash MP, Young AA. Super-resolution 4D flow MRI to quantify aortic regurgitation using computational fluid dynamics and deep learning. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2023; 39:1189-1202. [PMID: 36820960 DOI: 10.1007/s10554-023-02815-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 02/10/2023] [Indexed: 02/24/2023]
Abstract
Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation (AR), a type of valvular heart disease. Metrics derived from blood flows are used to indicate AR onset and evaluate its severity. These metrics can be non-invasively obtained using four-dimensional (4D) flow magnetic resonance imaging (MRI), where accuracy is primarily dependent on spatial resolution. However, insufficient resolution often results from limitations in 4D flow MRI and complex aortic regurgitation hemodynamics. To address this, computational fluid dynamics simulations were transformed into synthetic 4D flow MRI data and used to train a variety of neural networks. These networks generated super-resolution, full-field phase images with an upsample factor of 4. Results showed decreased velocity error, high structural similarity scores, and improved learning capabilities from previous work. Further validation was performed on two sets of in vivo 4D flow MRI data and demonstrated success in de-noising flow images. This approach presents an opportunity to comprehensively analyse AR hemodynamics in a non-invasive manner.
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Affiliation(s)
- Derek Long
- Department of Engineering Science, University of Auckland, Auckland, New Zealand.
| | - Cameron McMurdo
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
| | - Edward Ferdian
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Charlène A Mauger
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - David Marlevi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Solna, Sweden
| | - Martyn P Nash
- Department of Engineering Science, University of Auckland, Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King's College London, London, UK
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6
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Gill H, Fernandes J, Chehab O, Prendergast B, Redwood S, Chiribiri A, Nordsletten D, Rajani R, Lamata P. Evaluation of aortic stenosis: From Bernoulli and Doppler to Navier-Stokes. Trends Cardiovasc Med 2023; 33:32-43. [PMID: 34920129 DOI: 10.1016/j.tcm.2021.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 12/07/2021] [Accepted: 12/07/2021] [Indexed: 02/01/2023]
Abstract
Uni-dimensional Doppler echocardiography data provide the mainstay of quantative assessment of aortic stenosis, with the transvalvular pressure drop a key indicator of haemodynamic burden. Sophisticated methods of obtaining velocity data, combined with improved computational analysis, are facilitating increasingly robust and reproducible measurement. Imaging modalities which permit acquisition of three-dimensional blood velocity vector fields enable angle-independent valve interrogation and calculation of enhanced measures of the transvalvular pressure drop. This manuscript clarifies the fundamental principles of physics that underpin the evaluation of aortic stenosis and explores modern techniques that may provide more accurate means to grade aortic stenosis and inform appropriate management.
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Affiliation(s)
- Harminder Gill
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Joao Fernandes
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Omar Chehab
- Cardiology Department, Guy's and St. Thomas's Hospital NHS Foundation Trust, London, UK
| | - Bernard Prendergast
- Cardiology Department, Guy's and St. Thomas's Hospital NHS Foundation Trust, London, UK
| | - Simon Redwood
- Cardiology Department, Guy's and St. Thomas's Hospital NHS Foundation Trust, London, UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David Nordsletten
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Surgery and Biomedical Engineering, University of Michigan, 2800 Plymouth Rd, 48109, Ann Arbor, MI, USA
| | - Ronak Rajani
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Cardiology Department, Guy's and St. Thomas's Hospital NHS Foundation Trust, London, UK
| | - Pablo Lamata
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Kazemi A, Padgett DA, Callahan S, Stoddard M, Amini AA. Relative pressure estimation from 4D flow MRI using generalized Bernoulli equation in a phantom model of arterial stenosis. MAGMA (NEW YORK, N.Y.) 2022; 35:733-748. [PMID: 35175449 DOI: 10.1007/s10334-022-01001-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 01/09/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Arterial stenosis is a significant cardiovascular disease requiring accurate estimation of the pressure gradients for determining hemodynamic significance. In this paper, we propose Generalized Bernoulli Equation (GBE) utilizing interpolated-based method to estimate relative pressures using streamlines and pathlines from 4D Flow MRI. METHODS 4D Flow MRI data in a stenotic phantom model and computational fluid dynamics simulated velocities generated under identical flow conditions were processed by Generalized Bernoulli Equation (GBE), Reduced Bernoulli Equations (RBE), as well as the Simple Bernoulli Equation (SBE) which is clinically prevalent. Pressures derived from 4D flow MRI and noise corrupted CFD velocities were compared with pressures generated directly with CFD as well as pressures obtained using Millar catheters under identical flow conditions. RESULTS It was found that SBE and RBE methods underestimated the relative pressure for lower flow rates while overestimating the relative pressure at higher flow rates. Specifically, compared to the reference pressure, SBE underestimated the maximum relative pressure by 22[Formula: see text] for a pulsatile flow data with peak flow rate [Formula: see text] and overestimated by around 40[Formula: see text] when [Formula: see text]. In contrast, for GBE method the relative pressure values were overestimated by 15[Formula: see text] with [Formula: see text]and around 10[Formula: see text] with [Formula: see text]. CONCLUSION GBE methods showed robust performance to additive image noise compared to other methods. Our findings indicate that GBE pressure estimation over pathlines attains the highest level of accuracy compared to GBE over streamlines, and the SBE and RBE methods.
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Affiliation(s)
- Amirkhosro Kazemi
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | | | - Sean Callahan
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | - Marcus Stoddard
- Cardiovascular Division, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | - Amir A Amini
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA.
- Robley Rex VA Medical Center, Louisville, KY, USA.
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8
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Aliabadi S, Sojoudi A, Bandali MF, Bristow MS, Lydell C, Fedak PWM, White JA, Garcia J. Intra-cardiac pressure drop and flow distribution of bicuspid aortic valve disease in preserved ejection fraction. Front Cardiovasc Med 2022; 9:903277. [PMID: 36093173 PMCID: PMC9448951 DOI: 10.3389/fcvm.2022.903277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/08/2022] [Indexed: 12/01/2022] Open
Abstract
Background Bicuspid aortic valve (BAV) is more than a congenital defect since it is accompanied by several secondary complications that intensify induced impairments. Hence, BAV patients need lifelong evaluations to prevent severe clinical sequelae. We applied 4D-flow magnetic resonance imaging (MRI) for in detail visualization and quantification of in vivo blood flow to verify the reliability of the left ventricular (LV) flow components and pressure drops in the silent BAV subjects with mild regurgitation and preserved ejection fraction (pEF). Materials and methods A total of 51 BAV patients with mild regurgitation and 24 healthy controls were recruited to undergo routine cardiac MRI followed by 4D-flow MRI using 3T MRI scanners. A dedicated 4D-flow module was utilized to pre-process and then analyze the LV flow components (direct flow, retained inflow, delayed ejection, and residual volume) and left-sided [left atrium (LA) and LV] local pressure drop. To elucidate significant diastolic dysfunction in our population, transmitral early and late diastolic 4D flow peak velocity (E-wave and A-wave, respectively), as well as E/A ratio variable, were acquired. Results The significant means differences of each LV flow component (global measurement) were not observed between the two groups (p > 0.05). In terms of pressure analysis (local measurement), maximum and mean as well as pressure at E-wave and A-wave timepoints at the mitral valve (MV) plane were significantly different between BAV and control groups (p: 0.005, p: 0.02, and p: 0.04 and p: <0.001; respectively). Furthermore, maximum pressure and pressure difference at the A-wave timepoint at left ventricle mid and left ventricle apex planes were significant. Although we could not find any correlation between LV diastolic function and flow components, Low but statistically significant correlations were observed with local pressure at LA mid, MV and LV apex planes at E-wave timepoint (R: −0.324, p: 0.005, R: −0.327, p: 0.004, and R: −0.306, p: 0.008, respectively). Conclusion In BAV patients with pEF, flow components analysis is not sensitive to differentiate BAV patients with mild regurgitation and healthy control because flow components and EF are global parameters. Inversely, pressure (local measurement) can be a more reliable biomarker to reveal the early stage of diastolic dysfunction.
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9
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Nolte D, Bertoglio C. Inverse problems in blood flow modeling: A review. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2022; 38:e3613. [PMID: 35526113 PMCID: PMC9541505 DOI: 10.1002/cnm.3613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 12/29/2021] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
Mathematical and computational modeling of the cardiovascular system is increasingly providing non-invasive alternatives to traditional invasive clinical procedures. Moreover, it has the potential for generating additional diagnostic markers. In blood flow computations, the personalization of spatially distributed (i.e., 3D) models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature. In the last years, the development and application of inverse methods has rapidly expanded most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decade. We review the current state of the art of inverse problems in blood flows, focusing on studies considering fully dimensional fluid and fluid-solid models. The relevant physical models and hemodynamic measurement techniques are introduced, followed by a survey of mathematical data assimilation approaches used to solve different kinds of inverse problems, namely state and parameter estimation. An exhaustive discussion of the literature of the last decade is presented, structured by types of problems, models and available data.
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Affiliation(s)
- David Nolte
- Bernoulli InstituteUniversity of GroningenGroningenThe Netherlands
- Center for Mathematical ModelingUniversidad de ChileSantiagoChile
- Department of Fluid DynamicsTechnische Universität BerlinBerlinGermany
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10
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Marlevi D, Mariscal-Harana J, Burris NS, Sotelo J, Ruijsink B, Hadjicharalambous M, Asner L, Sammut E, Chabiniok R, Uribe S, Winter R, Lamata P, Alastruey J, Nordsletten D. Altered Aortic Hemodynamics and Relative Pressure in Patients with Dilated Cardiomyopathy. J Cardiovasc Transl Res 2022; 15:692-707. [PMID: 34882286 PMCID: PMC9622552 DOI: 10.1007/s12265-021-10181-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 10/20/2021] [Indexed: 12/05/2022]
Abstract
Ventricular-vascular interaction is central in the adaptation to cardiovascular disease. However, cardiomyopathy patients are predominantly monitored using cardiac biomarkers. The aim of this study is therefore to explore aortic function in dilated cardiomyopathy (DCM). Fourteen idiopathic DCM patients and 16 controls underwent cardiac magnetic resonance imaging, with aortic relative pressure derived using physics-based image processing and a virtual cohort utilized to assess the impact of cardiovascular properties on aortic behaviour. Subjects with reduced left ventricular systolic function had significantly reduced aortic relative pressure, increased aortic stiffness, and significantly delayed time-to-pressure peak duration. From the virtual cohort, aortic stiffness and aortic volumetric size were identified as key determinants of aortic relative pressure. As such, this study shows how advanced flow imaging and aortic hemodynamic evaluation could provide novel insights into the manifestation of DCM, with signs of both altered aortic structure and function derived in DCM using our proposed imaging protocol.
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Affiliation(s)
- David Marlevi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Huddinge, Sweden
- Department of Clinical Sciences, Karolinska Institutet, Danderyd, Sweden
| | - Jorge Mariscal-Harana
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | | | - Julio Sotelo
- School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, Cardio MR, Chile
| | - Bram Ruijsink
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Myrianthi Hadjicharalambous
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
| | - Liya Asner
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Eva Sammut
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Faculty of Health Science, Bristol Heart Institute and Translational Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Radomir Chabiniok
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Inria, Palaiseau, France
- LMS, Ecole Polytechnique, CNRS, Institut Polytechnique de Paris, Paris, France
- Department of Mathematics, Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, , Prague, Czech Republic
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, Cardio MR, Chile
- Department of Radiology, School of Medicine, Pontifica Universidad Católica de Chile, Santiago, Chile
| | - Reidar Winter
- Department of Clinical Sciences, Karolinska Institutet, Danderyd, Sweden
| | - Pablo Lamata
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Jordi Alastruey
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- World-Class Research Center "Digital Biodesign and Personlized Healthcare", Sechenov University, Moscow, Russia
| | - David Nordsletten
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Department of Cardiac Surgery and Biomedical Engineering, University of Michigan, Plymouth Rd, Ann Arbor, MI, 48109, USA.
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11
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Sadeghi R, Tomka B, Khodaei S, Daeian M, Gandhi K, Garcia J, Keshavarz-Motamed Z. Impact of extra-anatomical bypass on coarctation fluid dynamics using patient-specific lumped parameter and Lattice Boltzmann modeling. Sci Rep 2022; 12:9718. [PMID: 35690596 PMCID: PMC9188592 DOI: 10.1038/s41598-022-12894-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/11/2022] [Indexed: 01/28/2023] Open
Abstract
Accurate hemodynamic analysis is not only crucial for successful diagnosis of coarctation of the aorta (COA), but intervention decisions also rely on the hemodynamics assessment in both pre and post intervention states to minimize patient risks. Despite ongoing advances in surgical techniques for COA treatments, the impacts of extra-anatomic bypass grafting, a surgical technique to treat COA, on the aorta are not always benign. Our objective was to investigate the impact of bypass grafting on aortic hemodynamics. We investigated the impact of bypass grafting on aortic hemodynamics using a patient-specific computational-mechanics framework in three patients with COA who underwent bypass grafting. Our results describe that bypass grafting improved some hemodynamic metrics while worsened the others: (1) Doppler pressure gradient improved (decreased) in all patients; (2) Bypass graft did not reduce the flow rate substantially through the COA; (3) Systemic arterial compliance increased in patients #1 and 3 and didn't change (improve) in patient 3; (4) Hypertension got worse in all patients; (5) The flow velocity magnitude improved (reduced) in patient 2 and 3 but did not improve significantly in patient 1; (6) There were elevated velocity magnitude, persistence of vortical flow structure, elevated turbulence characteristics, and elevated wall shear stress at the bypass graft junctions in all patients. We concluded that bypass graft may lead to pseudoaneurysm formation and potential aortic rupture as well as intimal hyperplasia due to the persistent abnormal and irregular aortic hemodynamics in some patients. Moreover, post-intervention, exposures of endothelial cells to high shear stress may lead to arterial remodeling, aneurysm, and rupture.
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Affiliation(s)
- Reza Sadeghi
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Benjamin Tomka
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Seyedvahid Khodaei
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - MohammadAli Daeian
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Krishna Gandhi
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Julio Garcia
- grid.489011.50000 0004 0407 3514Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, Calgary, AB Canada ,grid.22072.350000 0004 1936 7697Department of Radiology, University of Calgary, Calgary, AB Canada ,grid.22072.350000 0004 1936 7697Department of Cardiac Sciences, University of Calgary, Calgary, AB Canada ,grid.413571.50000 0001 0684 7358Alberta Children’s Hospital Research Institute, Calgary, AB Canada
| | - Zahra Keshavarz-Motamed
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON ,grid.25073.330000 0004 1936 8227School of Biomedical Engineering, McMaster University, Hamilton, ON Canada ,grid.25073.330000 0004 1936 8227School of Computational Science and Engineering, McMaster University, Hamilton, ON Canada
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12
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Pacheco DRQ. On the numerical treatment of viscous and convective effects in relative pressure reconstruction methods. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2022; 38:e3562. [PMID: 34873867 PMCID: PMC9286393 DOI: 10.1002/cnm.3562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/29/2021] [Accepted: 12/01/2021] [Indexed: 06/13/2023]
Abstract
The mechanism of many cardiovascular diseases can be understood by studying the pressure distribution in blood vessels. Direct pressure measurements, however, require invasive probing and provide only single-point data. Alternatively, relative pressure fields can be reconstructed from imaging-based velocity measurements by considering viscous and inertial forces. Both contributions can be potential troublemakers in pressure reconstruction: the former due to its higher-order derivatives, and the latter because of the quadratic nonlinearity in the convective acceleration. Viscous and convective terms can be treated in various forms, which, although equivalent for ideal measurements, can perform differently in practice. In fact, multiple versions are often used in literature, with no apparent consensus on the more suitable variants. In this context, the present work investigates the performance of different versions of relative pressure estimators. For viscous effects, in particular, two new modified estimators are presented to circumvent second-order differentiation without requiring surface integrals. In-silico and in-vitro data in the typical regime of cerebrovascular flows are considered, allowing a systematic noise sensitivity study. Convective terms are shown to be the main source of error, even for flows with pronounced viscous component. Moreover, the conservation (often integrated) form of convection exhibits higher noise sensitivity than the standard convective description, in all three families of estimators considered here. For the classical pressure Poisson estimator, the present modified version of the viscous term tends to yield better accuracy than the (recently introduced) integrated form, although this effect is in most cases negligible when compared to convection-related errors.
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Affiliation(s)
- Douglas R. Q. Pacheco
- Institute of Applied MathematicsGraz University of TechnologyGrazAustria
- Present address:
Graz Center of Computational EngineeringGraz University of TechnologyGrazAustria
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13
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de Vecchi A, Faraci A, Fernandes JF, Marlevi D, Bellsham-Revell H, Hussain T, Laji N, Ruijsink B, Wong J, Razavi R, Anderson D, Salih C, Pushparajah K, Nordsletten D, Lamata P. Unlocking the Non-invasive Assessment of Conduit and Reservoir Function in the Aorta. J Cardiovasc Transl Res 2022; 15:1075-1085. [PMID: 35199256 PMCID: PMC9622527 DOI: 10.1007/s12265-022-10221-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/14/2022] [Indexed: 11/06/2022]
Abstract
Aortic surgeries in congenital conditions, such as hypoplastic left heart syndrome (HLHS), aim to restore and maintain the conduit and reservoir functions of the aorta. We proposed a method to assess these two functions based on 4D flow MRI, and we applied it to study the aorta in pre-Fontan HLHS. Ten pre-Fontan HLHS patients and six age-matched controls were studied to derive the advective pressure difference and viscous dissipation for conduit function, and pulse wave velocity and elastic modulus for reservoir function. The reconstructed neo-aorta in HLHS subjects achieved a good conduit function at a cost of an impaired reservoir function (69.7% increase of elastic modulus). The native descending HLHS aorta displayed enhanced reservoir (elastic modulus being 18.4% smaller) but impaired conduit function (three-fold increase in peak advection). A non-invasive and comprehensive assessment of aortic conduit and reservoir functions is feasible and has potentially clinical relevance in congenital vascular conditions.
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Affiliation(s)
- Adelaide de Vecchi
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - Alessandro Faraci
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - Joao Filipe Fernandes
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - David Marlevi
- Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hannah Bellsham-Revell
- Department of Congenital Heart Disease, Evelina London Children's Hospital, Guy's & St Thomas' Hospitals, London, SE1 7EH, UK
| | - Tarique Hussain
- Pediatric Cardiology, UT Southwestern, Children's Medical Center Dallas, 1935 Medical District Dr, Dallas, TX, 75235, USA
| | - Nidhin Laji
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - Bram Ruijsink
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - James Wong
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - David Anderson
- Department of Congenital Heart Disease, Evelina London Children's Hospital, Guy's & St Thomas' Hospitals, London, SE1 7EH, UK
| | - Caner Salih
- Department of Congenital Heart Disease, Evelina London Children's Hospital, Guy's & St Thomas' Hospitals, London, SE1 7EH, UK
| | - Kuberan Pushparajah
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK
| | - David Nordsletten
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK.,Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Pablo Lamata
- School of Biomedical Engineering and Imaging Sciences, King's College London, 5th Floor Becket House, Lambeth Palace Road, London, SE1 7EU, UK.
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14
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Sadeghi R, Tomka B, Khodaei S, Garcia J, Ganame J, Keshavarz‐Motamed Z. Reducing Morbidity and Mortality in Patients With Coarctation Requires Systematic Differentiation of Impacts of Mixed Valvular Disease on Coarctation Hemodynamics. J Am Heart Assoc 2022; 11:e022664. [PMID: 35023351 PMCID: PMC9238522 DOI: 10.1161/jaha.121.022664] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Background Despite ongoing advances in surgical techniques for coarctation of the aorta (COA) repair, the long-term results are not always benign. Associated mixed valvular diseases (various combinations of aortic and mitral valvular pathologies) are responsible for considerable postoperative morbidity and mortality. We investigated the impact of COA and mixed valvular diseases on hemodynamics. Methods and Results We developed a patient-specific computational framework. Our results demonstrate that mixed valvular diseases interact with COA fluid dynamics and contribute to speed up the progression of the disease by amplifying the irregular flow patterns downstream of COA (local) and exacerbating the left ventricular function (global) (N=26). Velocity downstream of COA with aortic regurgitation alone was increased, and the situation got worse when COA and aortic regurgitation coexisted with mitral regurgitation (COA with normal valves: 5.27 m/s, COA with only aortic regurgitation: 8.8 m/s, COA with aortic and mitral regurgitation: 9.36 m/s; patient 2). Workload in these patients was increased because of the presence of aortic stenosis alone, aortic regurgitation alone, mitral regurgitation alone, and when they coexisted (COA with normal valves: 1.0617 J; COA with only aortic stenosis: 1.225 J; COA with only aortic regurgitation: 1.6512 J; COA with only mitral regurgitation: 1.3599 J; patient 1). Conclusions Not only the severity of COA, but also the presence and the severity of mixed valvular disease should be considered in the evaluation of risks in patients. The results suggest that more aggressive surgical approaches may be required, because regularly chosen current surgical techniques may not be optimal for such patients.
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Affiliation(s)
- Reza Sadeghi
- Department of Mechanical EngineeringMcMaster UniversityHamiltonOntarioCanada
| | - Benjamin Tomka
- Department of Mechanical EngineeringMcMaster UniversityHamiltonOntarioCanada
| | - Seyedvahid Khodaei
- Department of Mechanical EngineeringMcMaster UniversityHamiltonOntarioCanada
| | - Julio Garcia
- Stephenson Cardiac Imaging CentreLibin Cardiovascular Institute of AlbertaCalgaryAlbertaCanada,Department of RadiologyUniversity of CalgaryCalgaryAlbertaCanada,Department of Cardiac SciencesUniversity of CalgaryCalgaryAlbertaCanada,Alberta Children’s Hospital Research InstituteCalgaryAlbertaCanada
| | - Javier Ganame
- Division of CardiologyDepartment of MedicineMcMaster UniversityHamiltonOntarioCanada
| | - Zahra Keshavarz‐Motamed
- Department of Mechanical EngineeringMcMaster UniversityHamiltonOntarioCanada,School of Biomedical EngineeringMcMaster UniversityHamiltonOntarioCanada,School of Computational Science and EngineeringMcMaster UniversityHamiltonOntarioCanada,The Thrombosis & Atherosclerosis Research InstituteMcMaster UniversityHamiltonOntarioCanada
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15
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Marlevi D, Schollenberger J, Aristova M, Ferdian E, Ma Y, Young AA, Edelman ER, Schnell S, Figueroa CA, Nordsletten DA. Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI. Magn Reson Med 2021; 86:3096-3110. [PMID: 34431550 DOI: 10.1002/mrm.28928] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 05/24/2021] [Accepted: 06/25/2021] [Indexed: 12/28/2022]
Abstract
PURPOSE Hemodynamic alterations are indicative of cerebrovascular disease. However, the narrow and tortuous cerebrovasculature complicates image-based assessment, especially when quantifying relative pressure. Here, we present a systematic evaluation of image-based cerebrovascular relative pressure mapping, investigating the accuracy of the routinely used reduced Bernoulli (RB), the extended unsteady Bernoulli (UB), and the full-field virtual work-energy relative pressure ( ν WERP) method. METHODS Patient-specific in silico models were used to generate synthetic cerebrovascular 4D Flow MRI, with RB, UB, and ν WERP performance quantified as a function of spatiotemporal sampling and image noise. Cerebrovascular relative pressures were also derived in 4D Flow MRI from healthy volunteers ( n = 8 ), acquired at two spatial resolutions (dx = 1.1 and 0.8 mm). RESULTS The in silico analysis indicate that accurate relative pressure estimations are inherently coupled to spatial sampling: at dx = 1.0 mm high errors are reported for all methods; at dx = 0.5 mm ν WERP recovers relative pressures at a mean error of 0.02 ± 0.25 mm Hg, while errors remain higher for RB and UB (mean error of -2.18 ± 1.91 and -2.18 ± 1.87 mm Hg, respectively). The dependence on spatial sampling is also indicated in vivo, albeit with higher correlative dependence between resolutions using ν WERP (k = 0.64, R2 = 0.81 for dx = 1.1 vs. 0.8 mm) than with RB or UB (k = 0.04, R2 = 0.03, and k = 0.07, R2 = 0.07, respectively). CONCLUSION Image-based full-field methods such as ν WERP enable cerebrovascular relative pressure mapping; however, accuracy is directly dependent on utilized spatial resolution.
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Affiliation(s)
- David Marlevi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonas Schollenberger
- Department of Surgery and Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Maria Aristova
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Edward Ferdian
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Yue Ma
- Department of Radiology, Northwestern University, Chicago, IL, USA
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, UK
| | - Elazer R Edelman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Susanne Schnell
- Department of Radiology, Northwestern University, Chicago, IL, USA
- Department of Medical Physics, Institute of Physics, University of Greifswald, Greifswald, Germany
| | - C Alberto Figueroa
- Department of Surgery and Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - David A Nordsletten
- Department of Surgery and Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, UK
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16
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Nolte D, Urbina J, Sotelo J, Sok L, Montalba C, Valverde I, Osses A, Uribe S, Bertoglio C. Validation of 4D Flow based relative pressure maps in aortic flows. Med Image Anal 2021; 74:102195. [PMID: 34419837 DOI: 10.1016/j.media.2021.102195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 06/11/2021] [Accepted: 07/22/2021] [Indexed: 12/18/2022]
Abstract
While the clinical gold standard for pressure difference measurements is invasive catheterization, 4D Flow MRI is a promising tool for enabling a non-invasive quantification, by linking highly spatially resolved velocity measurements with pressure differences via the incompressible Navier-Stokes equations. In this work we provide a validation and comparison with phantom and clinical patient data of pressure difference maps estimators. We compare the classical Pressure Poisson Estimator (PPE) and the new Stokes Estimator (STE) against catheter pressure measurements under a variety of stenosis severities and flow intensities. Specifically, we use several 4D Flow data sets of realistic aortic phantoms with different anatomic and hemodynamic severities and two patients with aortic coarctation. The phantom data sets are enriched by subsampling to lower resolutions, modification of the segmentation and addition of synthetic noise, in order to study the sensitivity of the pressure difference estimators to these factors. Overall, the STE method yields more accurate results than the PPE method compared to catheterization data. The superiority of the STE becomes more evident at increasing Reynolds numbers with a better capacity of capturing pressure gradients in strongly convective flow regimes. The results indicate an improved robustness of the STE method with respect to variation in lumen segmentation. However, with heuristic removal of the wall-voxels, the PPE can reach a comparable accuracy for lower Reynolds' numbers.
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Affiliation(s)
- David Nolte
- Bernoulli Institute, University of Groningen, Groningen, 9747AG, The Netherlands; Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile
| | - Jesús Urbina
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, 7820436, Chile; Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, 833002, Chile; Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile
| | - Julio Sotelo
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, 7820436, Chile; Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile; School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile; Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, 7820436, Chile
| | - Leo Sok
- Bernoulli Institute, University of Groningen, Groningen, 9747AG, The Netherlands
| | - Cristian Montalba
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, 7820436, Chile; Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile
| | - Israel Valverde
- Hospital Universitario Virgen del Rocío, Sevilla, 41013, Spain
| | - Axel Osses
- Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile; Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, 7820436, Chile; Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, 833002, Chile; Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, 7820436, Chile
| | - Cristóbal Bertoglio
- Bernoulli Institute, University of Groningen, Groningen, 9747AG, The Netherlands; Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile.
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Burris NS, Nordsletten DA, Sotelo JA, Grogan-Kaylor R, Houben IB, Figueroa CA, Uribe S, Patel HJ. False lumen ejection fraction predicts growth in type B aortic dissection: preliminary results. Eur J Cardiothorac Surg 2021; 57:896-903. [PMID: 31821480 DOI: 10.1093/ejcts/ezz343] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/06/2019] [Accepted: 11/13/2019] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES Current risk assessment strategies in type B aortic dissection are focused on anatomic parameters, although haemodynamic abnormalities that result in false lumen (FL) pressurization are thought to play a significant role in aortic growth. The objective of this study was to evaluate blood flow of the FL using 4D flow magnetic resonance imaging (MRI) and identify haemodynamic and anatomic factors that independently predict the rate of aortic growth. METHODS Patients with dissection of the descending thoraco-abdominal aorta (n = 18) were enrolled in a prospective observational study and underwent 4D flow MRI for haemodynamic assessment of the entry tear and FL. Anatomic parameters were obtained by magnetic resonance angiography and baseline computed tomography. False lumen ejection fraction (FL EF) was defined the ratio of retrograde flow rate at the dominant entry tear during diastole over the antegrade systolic flow rate. RESULTS The median aortic growth rate was 3.5 mm/year (interquartile range 0.5-8.1 mm/year). Entry tear peak velocity was lower in patients with enlarging aortic dimensions (95.5 ± 24.1 vs 128.1 ± 37.4 cm/s, P = 0.039). After adjusting for co-variates FL EF (β = 0.15, P = 0.004), baseline maximal aortic diameter (β = 0.37, P = 0.001) and the entry tear distance from the left subclavian artery (β = 0.07, P = 0.016) were significant predictors of aortic growth rate. CONCLUSIONS Beyond standard anatomic risk factors, FL EF is an independent predictor of aortic growth rate and may represent an intuitive, non-invasive method to estimate FL pressurization and improve patient-specific risk assessment in patients with type B aortic dissection.
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Affiliation(s)
| | - David A Nordsletten
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA.,Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Julio A Sotelo
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile.,Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.,Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | | | - Ignas B Houben
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
| | - C Alberto Figueroa
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Department of Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile.,Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile.,Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Himanshu J Patel
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
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18
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Marlevi D, Sotelo JA, Grogan-Kaylor R, Ahmed Y, Uribe S, Patel HJ, Edelman ER, Nordsletten DA, Burris NS. False lumen pressure estimation in type B aortic dissection using 4D flow cardiovascular magnetic resonance: comparisons with aortic growth. J Cardiovasc Magn Reson 2021; 23:51. [PMID: 33980249 PMCID: PMC8117268 DOI: 10.1186/s12968-021-00741-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 03/16/2021] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Chronic type B aortic dissection (TBAD) is associated with poor long-term outcome, and accurate risk stratification tools remain lacking. Pressurization of the false lumen (FL) has been recognized as central in promoting aortic growth. Several surrogate imaging-based metrics have been proposed to assess FL hemodynamics; however, their relationship to enlarging aortic dimensions remains unclear. We investigated the association between aortic growth and three cardiovascular magnetic resonance (CMR)-derived metrics of FL pressurization: false lumen ejection fraction (FLEF), maximum systolic deceleration rate (MSDR), and FL relative pressure (FL ΔPmax). METHODS CMR/CMR angiography was performed in 12 patients with chronic dissection of the descending thoracoabdominal aorta, including contrast-enhanced CMR angiography and time-resolved three-dimensional phase-contrast CMR (4D Flow CMR). Aortic growth rate was calculated as the change in maximal aortic diameter between baseline and follow-up imaging studies over the time interval, with patients categorized as having either 'stable' (< 3 mm/year) or 'enlarging' (≥ 3 mm/year) growth. Three metrics relating to FL pressurization were defined as: (1) FLEF: the ratio between retrograde and antegrade flow at the TBAD entry tear, (2) MSDR: the absolute difference between maximum and minimum systolic acceleration in the proximal FL, and (3) FL ΔPmax: the difference in absolute pressure between aortic root and distal FL. RESULTS FLEF was higher in enlarging TBAD (49.0 ± 17.9% vs. 10.0 ± 11.9%, p = 0.002), whereas FL ΔPmax was lower (32.2 ± 10.8 vs. 57.2 ± 12.5 mmHg/m, p = 0.017). MSDR and conventional anatomic variables did not differ significantly between groups. FLEF showed positive (r = 0.78, p = 0.003) correlation with aortic growth rate whereas FL ΔPmax showed negative correlation (r = - 0.64, p = 0.026). FLEF and FL ΔPmax remained as independent predictors of aortic growth rate after adjusting for baseline aortic diameter. CONCLUSION Comparative analysis of three 4D flow CMR metrics of TBAD FL pressurization demonstrated that those that focusing on retrograde flow (FLEF) and relative pressure (FL ΔPmax) independently correlated with growth and differentiated patients with enlarging and stable descending aortic dissections. These results emphasize the highly variable nature of aortic hemodynamics in TBAD patients, and suggest that 4D Flow CMR derived metrics of FL pressurization may be useful to separate patients at highest and lowest risk for progressive aortic growth and complications.
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Affiliation(s)
- David Marlevi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Julio A Sotelo
- School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile
- ANID-Millennium Science Initiative Program-Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Ross Grogan-Kaylor
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Yunus Ahmed
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile
- ANID-Millennium Science Initiative Program-Millennium Nucleus in Cardiovascular Magnetic Resonance, Santiago, Chile
- Department of Radiology, Schools of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Himanshu J Patel
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
| | - Elazer R Edelman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - David A Nordsletten
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, MI, USA
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Nicholas S Burris
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
- Department of Radiology, University of Michigan, 1500 E. Medical Center Drive, Cardiovascular Center 5588, SPC-5030, Ann Arbor, MI, 48109-5030, USA.
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19
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Non-invasive estimation of relative pressure for intracardiac flows using virtual work-energy. Med Image Anal 2020; 68:101948. [PMID: 33383332 DOI: 10.1016/j.media.2020.101948] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 12/10/2020] [Accepted: 12/11/2020] [Indexed: 01/18/2023]
Abstract
Intracardiac blood flow is driven by differences in relative pressure, and assessing these is critical in understanding cardiac disease. Non-invasive image-based methods exist to assess relative pressure, however, the complex flow and dynamically moving fluid domain of the intracardiac space limits assessment. Recently, we proposed a method, νWERP, utilizing an auxiliary virtual field to probe relative pressure through complex, and previously inaccessible flow domains. Here we present an extension of νWERP for intracardiac flow assessments, solving the virtual field over sub-domains to effectively handle the dynamically shifting flow domain. The extended νWERP is validated in an in-silico benchmark problem, as well as in a patient-specific simulation model of the left heart, proving accurate over ranges of realistic image resolutions and noise levels, as well as superior to alternative approaches. Lastly, the extended νWERP is applied on clinically acquired 4D Flow MRI data, exhibiting realistic ventricular relative pressure patterns, as well as indicating signs of diastolic dysfunction in an exemplifying patient case. Summarized, the extended νWERP approach represents a directly applicable implementation for intracardiac flow assessments.
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20
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Obi AT, Figueroa CA. Flow dynamics, false lumens and implications for endografting. J Vasc Surg 2020; 71:2119-2120. [PMID: 32446517 DOI: 10.1016/j.jvs.2019.06.223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 06/30/2019] [Indexed: 11/30/2022]
Affiliation(s)
- Andrea T Obi
- Section of Vascular Surgery, Department of Surgery, University of Michigan Health System, Ann Arbor, Mich
| | - C Alberto Figueroa
- Section of Vascular Surgery, Department of Surgery, University of Michigan Health System, Ann Arbor, Mich; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Mich
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21
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Marlevi D, Ha H, Dillon-Murphy D, Fernandes JF, Fovargue D, Colarieti-Tosti M, Larsson M, Lamata P, Figueroa CA, Ebbers T, Nordsletten DA. Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy. Med Image Anal 2020; 60:101627. [PMID: 31865280 DOI: 10.1016/j.media.2019.101627] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 10/11/2019] [Accepted: 12/05/2019] [Indexed: 10/25/2022]
Abstract
Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, νWERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: νWERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. νWERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patient-specific in-silico model of an acute aortic dissection. Over all tests νWERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original νWERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended νWERP-t further enlarges the method's clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo.
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Affiliation(s)
- David Marlevi
- Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Hälsovägen 11, 14152, Huddinge, Sweden; Department of Clinical Sciences, Karolinska Institutet, Danderyds sjukhus, Mörbygårdsvägen, Danderyd, 18288, Sweden.
| | - Hojin Ha
- Department of Medical and Health Sciences and Center for Medical Image Science and Visualization (CMIV), Linköping Unversity, Linköping, SE-58185, Sweden; Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, 24341, Republic of Korea.
| | - Desmond Dillon-Murphy
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom.
| | - Joao F Fernandes
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom.
| | - Daniel Fovargue
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom.
| | - Massimiliano Colarieti-Tosti
- Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Hälsovägen 11, 14152, Huddinge, Sweden.
| | - Matilda Larsson
- Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Hälsovägen 11, 14152, Huddinge, Sweden.
| | - Pablo Lamata
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom.
| | - C Alberto Figueroa
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom; Department of Surgery and Biomedical Engineering, University of Michigan, 2800 Plymouth Rd, 48109, Ann Arbor, MI, USA.
| | - Tino Ebbers
- Department of Medical and Health Sciences and Center for Medical Image Science and Visualization (CMIV), Linköping Unversity, Linköping, SE-58185, Sweden.
| | - David A Nordsletten
- School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, London, SE1 7EH, United Kingdom; Department of Surgery and Biomedical Engineering, University of Michigan, 2800 Plymouth Rd, 48109, Ann Arbor, MI, USA
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