Estimating Central Blood Pressure from MRI data using reduced-order computational models

Jorge Mariscal Harana; Peter Harcourt Charlton; Samuel Michel Laurent Vennin; Arna van Engelen; Torben Schneider; Mateusz Florkow; Hubrecht de Bliek; Jacobus Bernardus Ruijsink; Israel Valverde Perez; Marietta Charakida; Kuberan E Pushparajah; Spencer J. Sherwin; Rene Michael Botnar; Jordi Alastruey-Arimon

doi:10.1016/j.artres.2018.10.105

Estimating Central Blood Pressure from MRI data using reduced-order computational models

Jorge Mariscal Harana, Peter Harcourt Charlton, Samuel Michel Laurent Vennin, Arna van Engelen, Torben Schneider, Mateusz Florkow, Hubrecht de Bliek, Jacobus Bernardus Ruijsink, Israel Valverde Perez, Marietta Charakida, Kuberan E Pushparajah, Spencer J. Sherwin, Rene Michael Botnar, Jordi Alastruey-Arimon

Research output: Contribution to journal › Meeting abstract › peer-review

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.

Original language	English
Article number	P52
Pages (from-to)	93-94
Journal	Artery Research
Volume	24
DOIs	https://doi.org/10.1016/j.artres.2018.10.105
Publication status	Published - 4 Dec 2018
Event	ARTERY18 - Guimaraes, Portugal Duration: 18 Oct 2018 → 20 Oct 2018 http://www.arterysociety.org/our-activities/our-conference/

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10.1016/j.artres.2018.10.105

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Mariscal Harana, J., Charlton, P. H., Vennin, S. M. L., van Engelen, A., Schneider, T., Florkow, M., de Bliek, H., Ruijsink, J. B., Valverde Perez, I., Charakida, M., Pushparajah, K. E., Sherwin, S. J., Botnar, R. M., & Alastruey-Arimon, J. (2018). Estimating Central Blood Pressure from MRI data using reduced-order computational models. Artery Research, 24, 93-94. Article P52. https://doi.org/10.1016/j.artres.2018.10.105

@article{0deb371f09c64d64a6bcd84b1f30afae,

title = "Estimating Central Blood Pressure from MRI data using reduced-order computational models",

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.",

author = "{Mariscal Harana}, Jorge and Charlton, {Peter Harcourt} and Vennin, {Samuel Michel Laurent} and {van Engelen}, Arna and Torben Schneider and Mateusz Florkow and {de Bliek}, Hubrecht and Ruijsink, {Jacobus Bernardus} and {Valverde Perez}, Israel and Marietta Charakida and Pushparajah, {Kuberan E} and Sherwin, {Spencer J.} and Botnar, {Rene Michael} and Jordi Alastruey-Arimon",

year = "2018",

month = dec,

day = "4",

doi = "10.1016/j.artres.2018.10.105",

language = "English",

volume = "24",

pages = "93--94",

journal = "Artery Research",

issn = "1872-9312",

publisher = "Elsevier BV",

note = "ARTERY18 ; Conference date: 18-10-2018 Through 20-10-2018",

url = "http://www.arterysociety.org/our-activities/our-conference/",

}

Mariscal Harana, J , Charlton, PH , Vennin, SML , van Engelen, A, Schneider, T, Florkow, M, de Bliek, H, Ruijsink, JB , Valverde Perez, I , Charakida, M , Pushparajah, KE, Sherwin, SJ, Botnar, RM & Alastruey-Arimon, J 2018, 'Estimating Central Blood Pressure from MRI data using reduced-order computational models', Artery Research, vol. 24, P52, pp. 93-94. https://doi.org/10.1016/j.artres.2018.10.105

TY - JOUR

T1 - Estimating Central Blood Pressure from MRI data using reduced-order computational models

AU - Mariscal Harana, Jorge

AU - Charlton, Peter Harcourt

AU - Vennin, Samuel Michel Laurent

AU - van Engelen, Arna

AU - Schneider, Torben

AU - Florkow, Mateusz

AU - de Bliek, Hubrecht

AU - Ruijsink, Jacobus Bernardus

AU - Valverde Perez, Israel

AU - Charakida, Marietta

AU - Pushparajah, Kuberan E

AU - Sherwin, Spencer J.

AU - Botnar, Rene Michael

AU - Alastruey-Arimon, Jordi

PY - 2018/12/4

Y1 - 2018/12/4

N2 - 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.

AB - 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.

U2 - 10.1016/j.artres.2018.10.105

DO - 10.1016/j.artres.2018.10.105

M3 - Meeting abstract

SN - 1872-9312

VL - 24

SP - 93

EP - 94

JO - Artery Research

JF - Artery Research

M1 - P52

T2 - ARTERY18

Y2 - 18 October 2018 through 20 October 2018

ER -

Estimating Central Blood Pressure from MRI data using reduced-order computational models

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