Research Papers

Infarcted Left Ventricles Have Stiffer Material Properties and Lower Stiffness Variation: Three-Dimensional Echo-Based Modeling to Quantify In Vivo Ventricle Material Properties

[+] Author and Article Information
Longling Fan

Department of Mathematics,
Southeast University,
Nanjing 210096, China

Jing Yao

Department of Cardiology,
First Affiliated Hospital
of Nanjing Medical University,
Nanjing 210029, China

Chun Yang

Network Technology Research Institute,
China United Network
Communications Co., Ltd.,
Beijing 100048, China

Dalin Tang

School of Biological Science & Medical
Southeast University,
Nanjing 210096, China
Mathematical Sciences Department,
Worcester Polytechnic Institute,
Worcester, MA 01609

Di Xu

Department of Cardiology,
First Affiliated Hospital
of Nanjing Medical University,
Nanjing 210029, China

1Corresponding authors.

Manuscript received December 11, 2014; final manuscript received May 11, 2015; published online June 9, 2015. Assoc. Editor: Hai-Chao Han.

J Biomech Eng 137(8), 081005 (Aug 01, 2015) (10 pages) Paper No: BIO-14-1620; doi: 10.1115/1.4030668 History: Received December 11, 2014; Revised May 11, 2015; Online June 09, 2015

Methods to quantify ventricle material properties noninvasively using in vivo data are of great important in clinical applications. An ultrasound echo-based computational modeling approach was proposed to quantify left ventricle (LV) material properties, curvature, and stress/strain conditions and find differences between normal LV and LV with infarct. Echo image data were acquired from five patients with myocardial infarction (I-Group) and five healthy volunteers as control (H-Group). Finite element models were constructed to obtain ventricle stress and strain conditions. Material stiffening and softening were used to model ventricle active contraction and relaxation. Systolic and diastolic material parameter values were obtained by adjusting the models to match echo volume data. Young's modulus (YM) value was obtained for each material stress–strain curve for easy comparison. LV wall thickness, circumferential and longitudinal curvatures (C- and L-curvature), material parameter values, and stress/strain values were recorded for analysis. Using the mean value of H-Group as the base value, at end-diastole, I-Group mean YM value for the fiber direction stress–strain curve was 54% stiffer than that of H-Group (136.24 kPa versus 88.68 kPa). At end-systole, the mean YM values from the two groups were similar (175.84 kPa versus 200.2 kPa). More interestingly, H-Group end-systole mean YM was 126% higher that its end-diastole value, while I-Group end-systole mean YM was only 29% higher that its end-diastole value. This indicated that H-Group had much greater systole–diastole material stiffness variations. At beginning-of-ejection (BE), LV ejection fraction (LVEF) showed positive correlation with C-curvature, stress, and strain, and negative correlation with LV volume, respectively. At beginning-of-filling (BF), LVEF showed positive correlation with C-curvature and strain, but negative correlation with stress and LV volume, respectively. Using averaged values of two groups at BE, I-Group stress, strain, and wall thickness were 32%, 29%, and 18% lower (thinner), respectively, compared to those of H-Group. L-curvature from I-Group was 61% higher than that from H-Group. Difference in C-curvature between the two groups was not statistically significant. Our results indicated that our modeling approach has the potential to determine in vivo ventricle material properties, which in turn could lead to methods to infer presence of infarct from LV contractibility and material stiffness variations. Quantitative differences in LV volume, curvatures, stress, strain, and wall thickness between the two groups were provided.

Copyright © 2015 by ASME
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Fig. 1

Echo images from a patient (P5) with infarct, and reconstructed geometry. Infarct locations were marked by thick circles on the echo images: (a) end-systolic echo images, (b) end-diastolic echo images, (c) reconstructed end-systolic LV geometry, and (d) reconstructed end-diastolic LV geometry

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Fig. 2

Echo images of a healthy volunteer (P6), contours and reconstructed geometries: (a) end-systolic echo, healthy volunteer, (b) end-diastolic echo, healthy volunteer, (c) reconstructed end-systolic LV geometry, and (d) reconstructed end-diastolic LV geometry

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Fig. 3

A sample of recorded and imposed LV blood pressure profile: (a) recorded LV blood pressure profile and (b) imposed LV blood pressure profile

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Fig. 4

Modeling fiber orientation: (a) fiber orientation from a pig model; (b) fiber orientation from a human heart; (c) fiber orientation from our two-layer LV model, end-systolic; and (d) end-diastolic condition

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Fig. 5

LV geometries corresponding to no-load, end-systolic, and end-diastolic conditions: (a) no-load geometry, (b) end-systolic geometry, and (c) end-diastolic geometry

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Fig. 6

Material stress–stretch curves (in fiber coordinate) for P5 (infarct group) and P6 (healthy group). Tff: stress in fiber direction and Tcc: stress in circumferential direction of the fiber: (a) P5, end-systole, (b) P5, end-diastole, (c) P6, end-systole, and (d) P6, end-diastole.

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Fig. 7

Stress-P1 (maximum principal stress) and strain-P1 (maximum principal strain) plots from P5 (with infarct) and P6 (healthy) showing stress/strain distribution patterns corresponding to maximum and minimum pressure conditions: (a) P5, stress-P1, BF; (b) P5, strain-P1, BF; (c) P5, stress-P1, BE; (d) P5, strain-P1, BE; (e) P6, stress-P1, BF; (f) P6, strain-P1, BF; (g) P6, stress-P1, BE; and (h) P6, strain-P1, BE




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