Quantifying dynamic mechanical properties of human placenta tissue using optimization techniques with specimen-specific finite-element models

被引:41
作者
Hu, Jingwen [1 ]
Klinich, Kathleen D. [1 ]
Miller, Carl S. [1 ]
Nazmi, Giseli [2 ]
Pearlman, Mark D. [2 ]
Schneider, Lawrence W. [1 ,3 ]
Rupp, Joanthan D. [1 ,4 ]
机构
[1] Univ Michigan, Transportat Res Inst, Ann Arbor, MI 48109 USA
[2] Univ Michigan Hlth Syst, Ann Arbor, MI USA
[3] Univ Michigan, Dept Biomed Engn, Ann Arbor, MI 48109 USA
[4] Univ Michigan, Dept Emergency Med, Ann Arbor, MI 48109 USA
关键词
Placental abruption; Fetal loss; Dynamic tissue testing; Specimen-specific finite-element model; Optimization; PREGNANT-WOMEN; INJURY;
D O I
10.1016/j.jbiomech.2009.07.003
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Motor-vehicle crashes are the leading cause of fetal deaths resulting from maternal trauma in the United States, and placental abruption is the most common cause of these deaths. To minimize this injury, new assessment tools, such as crash-test dummies and computational models of pregnant women, are needed to evaluate vehicle restraint systems with respect to reducing the risk of placental abruption. Developing these models requires accurate material properties for tissues in the pregnant abdomen under dynamic loading conditions that can occur in crashes. A method has been developed for determining dynamic material properties of human soft tissues that combines results from uniaxial tensile tests, specimen-specific finite-element models based on laser scans that accurately capture non-uniform tissue-specimen geometry, and optimization techniques. The current study applies this method to characterizing material properties of placental tissue. For 21 placenta specimens tested at a strain rate of 12/s, the mean failure strain is 0.472 +/- 0.097 and the mean failure stress is 34.80 +/- 12.62 kPa. A first-order Ogden material model with ground-state shear modulus (mu) of 23.97 +/- 5.52 kPa and exponent (alpha(1)) of 3.66 +/- 1.90 best fits the test results. The new method provides a nearly 40% error reduction (p<0.001) compared to traditional curve-fitting methods by considering detailed specimen geometry, loading conditions, and dynamic effects from high-speed loading. The proposed method can be applied to determine mechanical properties of other soft biological tissues. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2528 / 2534
页数:7
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