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Mandaltsi A, Grytsan A, Odudu A, Kadziela J, Morris PD, Witkowski A, Ellam T, Kalra P, Marzo A. Non-invasive Stenotic Renal Artery Haemodynamics by in silico Medicine. Front Physiol 2018; 9:1106. [PMID: 30174610 PMCID: PMC6107783 DOI: 10.3389/fphys.2018.01106] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 07/23/2018] [Indexed: 11/20/2022] Open
Abstract
Background: Measuring the extent to which renal artery stenosis (RAS) alters renal haemodynamics may permit precision medicine by physiologically guided revascularization. This currently requires invasive intra-arterial pressure measurement with associated risks and is rarely performed. The present proof-of-concept study investigates an in silico approach that uses computational fluid dynamic (CFD) modeling to non-invasively estimate renal artery haemodynamics from routine anatomical computed tomography (CT) imaging of RAS. Methods: We evaluated 10 patients with RAS by CT angiography. Intra-arterial renal haemodynamics were invasively measured by a transducing catheter under resting and hyperaemic conditions, calculating the translesional ratio of distal to proximal pressure (Pd/Pa). The diagnostic and quantitative accuracy of the CFD-derived virtual Pd/Pa ratio (vPd/Pa) was evaluated against the invasively measured Pd/Pa ratio (mPd/Pa). Results: Hyperaemic haemodynamics was infeasible and CT angiography in 4 patients had insufficient image resolution. Resting flow data is thus reported for 7 stenosed arteries from 6 patients (one patient had bilateral RAS). The comparison showed a mean difference of 0.015 (95% confidence intervals of ± 0.08), mean absolute error of 0.064, and a Pearson correlation coefficient of 0.6, with diagnostic accuracy for a physiologically significant Pd/Pa of ≤ 0.9 at 86%. Conclusion: We describe the first in silico estimation of renal artery haemodynamics from CT angiography in patients with RAS, showing it is feasible and diagnostically accurate. This provides a methodological framework for larger prospective studies to ultimately develop non-invasive precision medicine approaches for studies and interventions of RAS and resistant hypertension.
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Affiliation(s)
- Aikaterini Mandaltsi
- INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.,Mechanical Engineering Department, University of Sheffield, Sheffield, United Kingdom
| | - Andrii Grytsan
- INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.,Mechanical Engineering Department, University of Sheffield, Sheffield, United Kingdom
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, University of Manchester, Manchester, United Kingdom.,Salford Royal Hospital NHS Foundation Trust, Salford, United Kingdom
| | - Jacek Kadziela
- Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland
| | - Paul D Morris
- INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.,Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom.,Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom
| | - Adam Witkowski
- Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland
| | - Timothy Ellam
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Philip Kalra
- Division of Cardiovascular Sciences, University of Manchester, Manchester, United Kingdom.,Salford Royal Hospital NHS Foundation Trust, Salford, United Kingdom
| | - Alberto Marzo
- INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.,Mechanical Engineering Department, University of Sheffield, Sheffield, United Kingdom
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