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1.
J Biomech Eng ; 134(3): 034501, 2012 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-22482691

RESUMO

Dynamic mechanical properties of placenta tissue are needed to develop computational models of pregnant occupants for use in designing restraint systems that protect the fetus and mother. Tests were performed on 21 samples obtained from five human placentas at a rate of 1200 %/s using a set of custom designed thermoelectrically cooled clamps. Approximately half of the samples from all five subjects were tested within 48 h of delivery. The remaining samples were frozen for 5-7 days and then thawed before testing. True failure stresses and strains were not significantly different between fresh and frozen samples (p-value = 0.858 and 0.551, respectively), suggesting that soft tissue may be stored frozen up to a week without adversely affecting dynamic material response.


Assuntos
Criopreservação , Teste de Materiais/instrumentação , Placenta/citologia , Resistência à Tração , Fenômenos Biomecânicos , Feminino , Humanos , Gravidez
2.
Ann Biomed Eng ; 39(3): 1074-83, 2011 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-21120694

RESUMO

Placental abruption is the most common cause of fetal deaths in motor-vehicle crashes, but studies on the mechanical properties of human placenta are rare. This study presents a new method of developing a stochastic visco-hyperelastic material model of human placenta tissue using a combination of uniaxial tensile testing, specimen-specific finite element (FE) modeling, and stochastic optimization techniques. In our previous study, uniaxial tensile tests of 21 placenta specimens have been performed using a strain rate of 12/s. In this study, additional uniaxial tensile tests were performed using strain rates of 1/s and 0.1/s on 25 placenta specimens. Response corridors for the three loading rates were developed based on the normalized data achieved by test reconstructions of each specimen using specimen-specific FE models. Material parameters of a visco-hyperelastic model and their associated standard deviations were tuned to match both the means and standard deviations of all three response corridors using a stochastic optimization method. The results show a very good agreement between the tested and simulated response corridors, indicating that stochastic analysis can improve estimation of variability in material model parameters. The proposed method can be applied to develop stochastic material models of other biological soft tissues.


Assuntos
Aceleração , Acidentes de Trânsito , Modelos Biológicos , Placenta/fisiologia , Simulação por Computador , Módulo de Elasticidade/fisiologia , Feminino , Análise de Elementos Finitos , Humanos , Modelos Estatísticos , Gravidez , Processos Estocásticos , Estresse Mecânico , Viscosidade
3.
J Biomech ; 42(15): 2528-34, 2009 Nov 13.
Artigo em Inglês | MEDLINE | ID: mdl-19665131

RESUMO

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.


Assuntos
Modelos Biológicos , Placenta/fisiologia , Simulação por Computador , Módulo de Elasticidade/fisiologia , Feminino , Análise de Elementos Finitos , Humanos , Placenta/anatomia & histologia , Gravidez , Resistência à Tração/fisiologia
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