In vivo estimation of normal left ventricular stiffness and contractility based on routine cine MR acquisition
Introduction
Ischemic heart disease occurs due to the constriction of the coronary arteries, causing reduced supply of blood and oxygen to the heart muscles. This eventually leads to myocardial functional impairment and scarring. Post-infarction remodeling modifies the mechanical behavior of the myocardium [1], making stiffness and contractility good potential prognostic parameters. Unfortunately, clinicians normally lack information on these biomechanical parameters, since direct measurement is very challenging, if not impossible. Mechanical models capable of predicting subject-specific stiffness and contractility would be a useful tool to assess the condition of an ischemic patient. However, before performing any measurement on ischemic hearts, it is necessary to first establish the range of normal LV stiffness and contractility.
The determination of subject-specific constitutive material parameters is a challenging inverse problem involving several key components: heart’s shape, tissue structure and motion representation, myocardial material modeling, definition of appropriate boundary and loading conditions and optimization strategy [2]. Cardiac imaging modalities such as cardiac magnetic resonance (CMR) now provide access to several of the complementary information needed to build cardiac models e.g. geometry, tissue characteristics, and motion. Several finite element (FE)-based studies have addressed the identification of diastolic mechanical parameters of the myocardium within an optimization process in reference to myocardial displacement [3], [4], strains [5], strains and volumes either simultaneously [6] or separately [7], [8]. Estimation of myocardial contractility requires the incorporation of subject-specific active contraction, which often results in the estimation of one active parameter of various active tension formulations. Table 1 presents a non-exhaustive list of models (with initial geometry, active and passive constitutive laws, and boundary conditions used) developed to estimate the passive and active mechanical properties of the myocardium. The variety of estimated passive parameters in various conditions is visible in Table 4 for human studies. Genet et al. proposed a personalization method to construct a reference left ventricular stress map [7]. Their study managed to find a normal range of myocardial contractility, but it was limited to five healthy subjects who underwent extensive CMR acquisitions, which are time-consuming, costly, and not suitable for every individual.
In this study, we aim to estimate left ventricular stiffness and contractility of 21 healthy subjects based on routine cardiac cine CMR acquisition. These biomechanical parameters are quantified by personalizing a FE mechanical model of the LV. The models were validated individually through comparison against measured strains and other clinically relevant measurements, i.e. end-diastolic wall thickness, systolic fractional thickening, global circumferential and longitudinal strains. The main goal of this study is to propose an initial step toward estimating and verifying subject-specific left ventricular stiffness and contractility based on routine CMR acquisitions.
Section snippets
Subjects datasets
Two cardiac MR datasets of healthy volunteers were used in this study. The first dataset (n=11, 9 males) is open-access, available within the context of a MICCAI STACOM Challenge [13]. The second dataset was part of the MARVEL cohort run by CHU Saint-Etienne, France (n=10, 4 males). The MARVEL study (ID RCB 2016-A00913-48) was approved by the local institutional review board (IRB #16/052) and is registered at ClinicalTrials.gov (NCT03064503). All patients provided written informed consent.
Subject-specific MR data
Table 2 displays the LV metrics for all subjects. ’Measured’ lists the metrics obtained from the MR data. ED wall thickness is established to be different between male and female: in our study we found ED wall thickness of 8.1 ± 1.3 mm and 6.1 ± 0.8 mm for male and female subjects, respectively.
Model personalization evaluation
The one-parameter (CI) personalization process conducted to the targeted ES pressure of 16kPa for all the cases. The average optimized ED pressure in the SI identification process was 1.28kPa. Fig. 5
Discussion
Despite the clear advantages for clinicians and biomedical engineers in estimating the in vivo left ventricular mechanical properties, no studies on a non-invasive estimation method have been developed and validated solely based on data acquired from routine clinical data. The present work is one of the first that use inverse FE modeling and measurements from routine cine CMR acquisitions to estimate subject-specific left ventricular stiffness and contractility on twenty-one healthy subjects.
Statements
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Conflicts of Interest: None
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Funding: European Commission H2020 MSCA Training Network VPH-CaSE (www.vph-case.eu), grant agreement No 642612.
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Ethical Approval: Not required
Declaration of Competing Interest
No conflict of interest exists.
Acknowledgements
GK Rumindo was supported by the European Commission H2020 MSCA Training Network VPH-CaSE (www.vph-case.eu), grant agreement No 642612. This work was performed within the LABEX PRIMES (ANR-11-LABX-0063) of Université de Lyon, within the program Investissements d’ Avenir (ANR-11-IDEX-0007), and the SIMR project operated by the French National Research Agency. We thank Circle Cardiovascular Imaging (Calgary, Canada) for making available CVI42 software for research purposes and for their technical
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