Artery Research

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Volume 24, Issue C, December 2018, Pages 93 - 94

P52 ESTIMATING CENTRAL BLOOD PRESSURE FROM MRI DATA USING REDUCED-ORDER COMPUTATIONAL MODELS

Authors
Jorge Mariscal Harana1, 2, Peter H. Charlton2, Samuel Vennin2, Arna van Engelen3, Torben Schneider4, Mateusz Florkow2, 4, Hubrecht de Bliek5, Bram Ruijsink2, Israel Valverde2, Marietta Charakida2, Kuberan Pushparajah2, Spencer Sherwin1, Rene Botnar2, Jordi Alastruey2
1City and Guilds Building, Imperial College London, London, UK
2School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
3Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus, MC, the Netherlands
4Philips Healthcare, Guildford, UK
5HSDP Clinical Platforms, Philips Healthcare, Best, the Netherlands
Available Online 4 December 2018.
DOI
10.1016/j.artres.2018.10.105How to use a DOI?
Abstract

Purpose: Central Blood Pressure (CBP) is a better cardiovascular risk indicator than brachial pressure [1]. However, gold standard CBP measurements require an invasive catheter. We propose an approach to estimate CBP non-invasively from Magnetic Resonance Imaging (MRI) data coupled with a non-invasive brachial pressure measurement, using reduced-order (0-D/1-D) computational models. Our objectives were: identifying optimum model parameter estimation methods and comparing the performance of 0-D/1-D models for estimating CBP.

Methods: Populations of virtual (simulated) healthy subjects were generated based on [2]. Pressure and flow waveforms from these populations were used to develop and test Methods: for estimating model parameters. Two common clinical scenarios were considered: when a brachial pressure waveform is available; and when only systolic and diastolic blood pressures are available. Optimal parameter estimation Methods: were identified for each scenario and used with two 0-D Windkessel models and a 1-D aortic model. Results were compared with invasive CBP in a post-coarctation repair population (n = 10).

Results: Model parameters were best estimated by: fitting an exponential to the pressure waveform to estimate compliance and outflow pressure; using the least-squares method to estimate pulse wave velocity from flow data; assuming characteristic impedance was 5% of arterial resistance; and estimating end-systolic time from the second derivative of the pressure waveform. Average pulse and systolic CBP errors were <5 mmHg and <2 mmHg, respectively.

Conclusions: We have demonstrated the feasibility of estimating CBP from MRI and brachial pressure. Different reduced-order models provided similar performance, although the 1-D model reproduced pressure waveform morphology more accurately.

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<Previous Article In Issue
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Journal
Artery Research
Volume-Issue
24 - C
Pages
93 - 94
Publication Date
2018/12/04
ISSN (Online)
1876-4401
ISSN (Print)
1872-9312
DOI
10.1016/j.artres.2018.10.105How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

risenwbib
TY  - JOUR
AU  - Jorge Mariscal Harana
AU  - Peter H. Charlton
AU  - Samuel Vennin
AU  - Arna van Engelen
AU  - Torben Schneider
AU  - Mateusz Florkow
AU  - Hubrecht de Bliek
AU  - Bram Ruijsink
AU  - Israel Valverde
AU  - Marietta Charakida
AU  - Kuberan Pushparajah
AU  - Spencer Sherwin
AU  - Rene Botnar
AU  - Jordi Alastruey
PY  - 2018
DA  - 2018/12/04
TI  - P52 ESTIMATING CENTRAL BLOOD PRESSURE FROM MRI DATA USING REDUCED-ORDER COMPUTATIONAL MODELS
JO  - Artery Research
SP  - 93
EP  - 94
VL  - 24
IS  - C
SN  - 1876-4401
UR  - https://doi.org/10.1016/j.artres.2018.10.105
DO  - 10.1016/j.artres.2018.10.105
ID  - MariscalHarana2018
ER  -