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Research Papers

Patient-Specific Computational Analysis of Ventricular Mechanics in Pulmonary Arterial Hypertension

[+] Author and Article Information
Ce Xi, Candace Latnie

Department of Mechanical Engineering,
Michigan State University,
East Lansing, MI 48824-1226

Xiaodan Zhao, Ju Le Tan

National Heart Center Singapore,
Singapore, Singapore 169609

Samuel T. Wall

Simula Research Laboratory,
Fornebu 1364, Norway

Martin Genet

LMS,
École Polytechnique,
CNRS,
Université Paris-Saclay;
Inria,
Université Paris-Saclay,
Palaiseau 91128, France

Liang Zhong

National Heart Center Singapore,
Singapore, Singapore 169609;
Duke-NUS Medical School,
Singapore, Singapore 169857

Lik Chuan Lee

Department of Mechanical Engineering,
Michigan State University,
East Lansing, MI 48824-1226
e-mail: lclee@egr.msu.edu

1Corresponding author.

Manuscript received May 14, 2016; final manuscript received August 12, 2016; published online October 21, 2016. Assoc. Editor: Jessica E. Wagenseil.

J Biomech Eng 138(11), 111001 (Oct 21, 2016) (9 pages) Paper No: BIO-16-1200; doi: 10.1115/1.4034559 History: Received May 14, 2016; Revised August 12, 2016

Patient-specific biventricular computational models associated with a normal subject and a pulmonary arterial hypertension (PAH) patient were developed to investigate the disease effects on ventricular mechanics. These models were developed using geometry reconstructed from magnetic resonance (MR) images, and constitutive descriptors of passive and active mechanics in cardiac tissues. Model parameter values associated with ventricular mechanical properties and myofiber architecture were obtained by fitting the models with measured pressure–volume loops and circumferential strain calculated from MR images using a hyperelastic warping method. Results show that the peak right ventricle (RV) pressure was substantially higher in the PAH patient (65 mmHg versus 20 mmHg), who also has a significantly reduced ejection fraction (EF) in both ventricles (left ventricle (LV): 39% versus 66% and RV: 18% versus 64%). Peak systolic circumferential strain was comparatively lower in both the left ventricle (LV) and RV free wall (RVFW) of the PAH patient (LV: −6.8% versus −13.2% and RVFW: −2.1% versus −9.4%). Passive stiffness, contractility, and myofiber stress in the PAH patient were all found to be substantially increased in both ventricles, whereas septum wall in the PAH patient possessed a smaller curvature than that in the LV free wall. Simulations using the PAH model revealed an approximately linear relationship between the septum curvature and the transseptal pressure gradient at both early-diastole and end-systole. These findings suggest that PAH can induce LV remodeling, and septum curvature measurements may be useful in quantifying transseptal pressure gradient in PAH patients.

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References

Figures

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Fig. 1

(a) Biventricular geometry reconstructed from MR images with LV (right, light region) and RVFW (left, dark region) material regions. (b) Myofiber orientation prescribed using LDRB method with a transmural variation of 60 deg (endo) to −60 deg (epi) for the entire biventricular model. (c) Coupling the biventricular model to three-element Windkessel models. (d) Polar coordinate used to calculate local curvature κ in the LV endocardium.

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Fig. 3

Circumferential strain Ecc for (a) PAH patient and (b) normal subject. (c) Comparison of regional peak negative Ecc between the PAH patient and normal subject.

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Fig. 2

Measurements and model predictions of the PV loops for the (a) PAH patient and (b) normal subject (marker “*” denotes end-systole)

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Fig. 4

Peak myofiber stress in the PAH patient (left) and normal subject (right)

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Fig. 5

Regional curvature κ in the LV endocardial surface of (a) PAH patient and (b) normal subject. (c) Comparison of normalized septum curvature κn between PAH patient and normal subject.

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Fig. 6

Effects of afterload on septum curvature within a cardiac cycle. (a) Time course of κ with different RV afterload. (b) End-systolic curvature κmax,s versus end-systolic transseptal pressure gradient. (c) Corresponding PV loops.

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Fig. 7

Effects of preload on septum curvature within a cardiac cycle. (a) Time course of κ with different RV preload. (b) Early-diastolic curvature κmax,d versus early-diastolic transseptal pressure gradient. (c) Corresponding PV loops.

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Fig. 8

PV loops for perturbation of different model parameters in the normal case

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Fig. 9

PV loops of the normal case using fitted PAH model parameters

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