Annals of Biomedical Engineering

, Volume 40, Issue 10, pp 2255–2265 | Cite as

Stress State and Strain Rate Dependence of the Human Placenta

  • Benjamin C. Weed
  • Ali Borazjani
  • Sourav S. Patnaik
  • R. Prabhu
  • M. F. Horstemeyer
  • Peter L. Ryan
  • Thomas Franz
  • Lakiesha N. Williams
  • Jun Liao
Article

Abstract

Maternal trauma (MT) in automotive collisions is a source of injury, morbidity, and mortality for both mothers and fetuses. The primary associated pathology is placental abruption in which the placenta detaches from the uterus leading to hemorrhaging and termination of pregnancy. In this study, we focused on the differences in placental tissue response to different stress states (tension, compression, and shear) and different strain rates. Human placentas were obtained (n = 11) for mechanical testing and microstructure analysis. Specimens (n = 4+) were tested in compression, tension, and shear, each at three strain rates (nine testing protocols). Microstructure analysis included scanning electron microscopy, histology, and interrupted mechanical tests to observe tissue response to various loading states. Our data showed the greatest stiffness in tension, followed by compression, and then by shear. The study concludes that mechanical behavior of human placenta tissue (i) has a strong stress state dependence and (ii) behaves in a rate dependent manner in all three stress states, which had previously only been shown in tension. Interrupted mechanical tests revealed differences in the morphological microstructure evolution that was driven by the kinematic constraints from the different loading states. Furthermore, these structure–property data can be used to develop high fidelity constitutive models for MT simulations.

Keywords

Human placenta biomechanics Stress state dependence Strain rate dependence Maternal traumatic injury Placental abruption 

Introduction

Maternal trauma (MT) affects 5–8% of all pregnancies and is the leading nonobstetric cause of maternal death in the United States.7,10,31,33 It is also a source of serious injury and mortality for the unborn fetus with many life-long consequences caused by both explicit trauma and emergency preterm delivery.2,23 The most common cause of trauma is a motor vehicle accident (MVA) and the most commonly associated pathology is abruptio placentae (AP), detachment of the placenta from uterus.17 AP affects approximately 1% of all pregnancies, and leads to hemorrhaging and reduction of blood flow to the fetus, as well as maternal complications including disseminated intravascular coagulation and renal failure.3,4,17 MVAs during pregnancy are particularly troubling to the clinician, because it is difficult to predict the outcome for the mother and fetus, and therefore are difficult to effectively treat.10,18 MVAs can also cause additional less common pathologies not associated with AP such as amniotic fluid embolism, uterine rupture, and pelvic fractures.2,7,11

The placenta is a transient vascular organ that develops during pregnancy. It attaches by microvilli to the uterine decidua and acts, along with the umbilicus, as a nutritional and respiratory conduit between the mother and fetus. During pregnancy the uterus increases greatly in size and the placenta and membranes form to protect and nourish the fetus.14 The placenta is attached to the inner surface uterus and does not receive direct support from any boney or ligamentous tissues. This makes the pregnant mother and fetus particularly susceptible to trauma through MVA.28 MT is difficult to study since in vitro or in vivo testing of physical specimens carries many logistical and ethical issues. Despite these difficulties, it is important to have methods for understanding MT to allow manufacturers to create safer restraints for pregnant passengers.23

Computational simulations have been widely used in traumatic injury prediction.9,24,32,36 Recent research has shown promise in helping to understand the complex injury mechanisms involved in maternal injuries.12,29,30,34,39 These simulations require advanced constitutive relationships to describe the behavior of the tissues being studied. It has been shown in non-biological materials that the loading state can affect the material properties, but little has been done in the biological world to examine this phenomenon.13,19 Previous MT simulations have used material models based on the phenomenological response of the biomaterial29; furthermore, those pioneering efforts have not considered the stress state dependence of tissue components, which can be a limiting factor in the accuracy of these simulations since loading is usually complicated and multi-axial.

To fully understand and simulate AP from MT, the mechanical properties of the pregnant uterus, the placenta, and the interface between the two need to be known. Previous experimental biomechanics studies have investigated the material properties of human placentas.1,20,21,26,27 These studies have used tensile testing to evaluate and describe complex biomechanical properties of placentas including hyperelasticity, strain rate dependence, and viscoelasticity. To our knowledge, no study has directly investigated the effects of different loading states (tension, compression, and shear) on a human placenta although studies have shown that the mechanical behavior of biological materials might vary under different loading mode.16,38

In this study, we specifically investigated the mechanical behavior of human placentas under various stress states and strain rates. The stress state dependence of human placentas was evaluated by mechanical testing in the tensile, shear, and compressive loading states. Interrupted mechanical tests were also conducted and placenta microstructures were analyzed to reveal the intrinsic mechanisms of tissue behavior under different stress states. The data presented in this study will be used to develop stress-state dependent constitutive models for use in finite element simulations of pregnant females in MVA or other situations of interest (e.g., pregnant woman falling). A computational simulation built on thorough and accurate microstructure characterizations will yield better predictions, provide in-depth understanding of injury mechanisms, and assist in corresponding safety designs.

Materials and Methods

Sample Preparation

Human placentas from eleven donors were used in this study. All samples were obtained from uncomplicated singleton vaginal deliveries at Oktibbeha County Hospital in accordance with the Mississippi State University (MSU) Institutional Review Board (#08-275). Donating patients were screened for the presence of sexually transmitted diseases (including HIV, HBV, and HCV) and unclear perinatal history. Samples were placed in 4 °C Ringers lactate buffered saline (LBS) and transported immediately after delivery to MSU where all tests were performed in a BSL2 certified laboratory. All tests were performed within 24 h of delivery. Note that we used vaginally delivered placentas, because placentas obtained by caesarean delivery are pulled from the uterine wall and are usually already mechanically damaged. Due to the size limit of the placenta tissue, we were not able to perform tests for each strain-rate and stress-state condition within a single donor. However, donor placentas were randomly assigned to loading modalities (tension, compression, and shear). Within a loading modality, there were between three and four donors, each donor placenta contributed at least one test to each strain rate.

Mechanical Testing

Specimens were rinsed in LBS and dissected in preparation for mechanical testing. All samples were prepared such that each specimen was dissected from within a single placental lobe as previously described.26,27 This prevents issues with underestimation of placental strength due to the thinner regions between lobes. Specimens were dissected to their appropriate shape by scalpel dissection using a guiding stencil to allow consistent shape. No specimens were frozen prior to testing since we found that the placenta tissue properties changed greatly after freezing and thaw procedures. Specimens were mechanically tested using the Mach 1 Micromechanical Testing System (Biomomentum, Laval, QC, Canada) shown in Fig. 1a. As mentioned above, tension, compression, and shear mechanical tests were performed under three different strain rates to investigate the stress state dependence of placenta tissue. Each donor was tested in a single stress-state and contributed at least one test to each strain-rate. All mechanical tests were conducted in a water bath containing LBS. All tensile and compression tests included a preloading of 1 g, preconditioning of 10 cycles, and a re-preload of 1 g.
Figure 1

Mechanical testing configuration. (a) Mach 1 micromechanical tester configured for compression; (b) dissected tension sample; (c) dissected compression sample; and (d) dissected shear sample

Tensile Testing

Dogbone shaped samples (Fig. 1b) were prepared with a grip-to-grip length of 40 mm, a width of 10 mm at the center of the dogbone, and a thickness of 5 mm. Samples were preloaded to 1 g, subjected to 10 cycles of 10% preconditioning, preloaded to 1 g, and then pulled to failure. The majority of the ends of the dogbone specimens were within the grips to minimize distortion of strain uniformity, and all tensile specimens failed in the middle region of the dogbone indicating that the specimen shape served its intended purpose. The tensile failure tests were conducted at rates of 40, 400, and 4000 μm/s (N = 4+ for each rate). In tensile testing, the displacement rates of 40, 400, and 4000 μm/s correspond to strain rates of 0.001, 0.01, and 0.1/s, respectively.

Unconfined Compression Testing

Cylindrical samples (Fig. 1c) were prepared with a grip-to-grip length of 16 mm and a radius of 19 mm. Specimens were mounted and secured with a small dot of PermaBond cyanoacrylate ester adhesive (PermaBond, Pottstown PA) to prevent slipping from the compression head. The very small amount of glue did not prevent the specimens from deforming as unconfined compression. Specimens were preloaded to 1 g, preconditioned for 10 cycles, re-preloaded to 1 g, and then loaded to 3000 g. Tests were conducted at rates of 40, 400, and 4000 μm/s (N = 5+ for each rate). In compression testing, the displacement rates of 40, 400, and 4000 μm/s correspond to strain rates of 0.0025, 0.025, and 0.25/s, respectively.

Shear Testing

Rectangular samples (Fig. 1d) were prepared to have a width of 20 mm, length of 50 mm, and thickness of 10 mm. All samples were prepared such that the shear loading aligned parallel to the uterine wall. These samples were glued to the shear test setup (two parallel tissue mounting plates) using a minimal amount of PermaBond adhesive. Compressive load between the parallel shear loading surfaces was limited to the minimum necessary to secure the samples with glue. Samples were sheared to 100 g in the positive and negative directions for 10 cycles. The data from the final cycles were used for analysis, as that data represents the tissue behavior after preconditioning. Tests were conducted at rates of 40, 400, and 4000 μm/s (N = 5+ for each rate). In shear testing, the displacement rates of 40, 400, and 4000 μm/s correspond to strain rates of 0.004, 0.04, and 0.4/s, respectively. Data was recorded at sampling rate of 100/s. All data was processed for further comparison using a custom software tool.5,8

Mechanical Data Analyses

Raw data were first analyzed by engineering stress and engineering strain in each stress state at each displacement rate. Briefly, for tension and compression, the engineering stress was calculated as the loading force over the undeformed cross-sectional area, and the engineering strain was calculated as the displacement divided by the initial grip-to-grip distance (gauge length at 1 g preload after preconditioning). The engineering stress and engineering strain were then converted to true stress and true strain using the following formulas:
$$ \sigma_{\text{true}} = \sigma_{\text{eng}} \left( {1 + \varepsilon_{\text{eng}} } \right), $$
(1)
$$ \varepsilon_{\text{true}} = \ln \left( {1 + \varepsilon_{\text{eng}} } \right), $$
(2)
where σeng and \( \varepsilon_{\text{eng}} \) are the engineering stress and strain, and σtrue and \( \varepsilon_{\text{true}} \) are the true stress and strain, respectively. For these formulas, tensile strain is positive, and compressive strain is negative. These formulas also assume material incompressibility.
For shear testing, engineering shear stress was defined as the shear load over the area of contact surface, and engineering shear strain was defined as the change in shear angle (the shear plate displacement over the thickness of sample). In order to accurately compare shear data to compression and tension, an effective stress conversion, based on classical Von Mises stress definitions, was applied to shear stress and strain as follows:
$$ \sigma_{\text{true - shear}} = \sigma_{12} \sqrt 3 . $$
(3)

Similar to other types of soft tissues,6,37 the stress–strain curve of placenta tissues consists of a nonlinear region and a linear region. For each mechanical test, a linear fit was applied in the linear region of the stress–strain curve to determine the slope and x-intercept of the fitted line. The slope of this fitted line represents the tissue’s tensile, compressive, or shear modulus in the linear region (large-strain elastic modulus) and the x-intercept represents the tissue’s extensibility.6,15

Scanning Electron Microscopy

Scanning electron microscopy (SEM) was performed to visualize the microstructure of placentas. Samples were prepared by common SEM preparation methods. Briefly, specimens were fixed in half-strength Karnovsky’s fixative (2% paraformaldehyde, 2.5% glutaraldehyde, in 0.1 M phosphate buffer). Samples were further fixed in 1% osmium tetroxide and then dehydrated in a critical point dryer (Polaron E 3000 CPD). Dried samples were sputter coated with gold–palladium and observed using a Zeiss EVO 50 SEM (Zeiss, Thornwood, NY) equipped with a LaB6 electron gun and secondary electron detector.

Interrupted Mechanical Testing and Histology

Interrupted mechanical tests were performed to reveal the microstructure evolution of the placenta tissue as the applied load increased. Samples were prepared, as described earlier, for each stress state. After being mounted in the appropriate configuration for their stress state, each sample was deformed to a desired engineering strain value and held at that strain; the water bath was replaced with 10% neutral buffered formalin and the sample was allowed to fix for 24 h. The interrupted mechanical tests were performed at two strain levels for each stress state, the first near the transitional region (heel region) of the nonlinear stress–strain curve (22.3, 35.7, and 39% true strain for tension, compression, and shear, respectively), and the second in the linear region of the stress–strain curve (40.5, 91.6, and 79% true strain for tension, compression, and shear, respectively).

After fixation, samples were prepared for histology analysis. Samples were embedded in paraffin and cut into 5 μm sections. Samples were then stained with Haematoxylin & Eosin (H&E) and examined by light microscopy (Nikon EC600) to assess internal microstructure changes in response to the external loading, especially the alteration of blood vessel alignment and morphology.

Statistical Analysis

All experimental data were presented as mean ± standard deviation. One way analysis of variances (ANOVA) was applied for statistical analysis (SigmaStat 3.0, SPSS Inc., Chicago, IL). Comparison among groups was considered significantly different at p < 0.05.

Results

The experimental data were organized by the stress state to assess the strain rate sensitivity of human placenta tissue (Fig. 2). We found that placenta exhibited a strain rate sensitivity in all three loading states (tension: 0.001, 0.01, and 0.1/s, Fig. 2a; compression: 0.0025, 0.025, and 0.25/s, Fig. 2b; shear: 0.004, 0.04, and 0.4/s, Fig. 2c). The larger applied strain rates incurred stiffer (higher stress) tissue responses.
Figure 2

Strain rate comparison. Strain rate comparisons for each stress state are shown: (a) tensile, (b) compression, and (c) shear. Strain rates are colored from low to high as green, red, and blue. For tension (a), green, red, and blue correspond to 0.001, 0.01, and 0.1/s, respectively; for compression (b), green, red, and blue correspond to 0.0025, 0.025, and 0.25/s; for shear (c), green, red, and blue correspond to 0.004, 0.04, and 0.4/s

To better assess the stress-state dependence of human placenta tissue, the experimental data were further organized by the strain rate domains. Significant stress state dependences were exhibited in the placenta for all the examined strain rate domains, i.e., the strain rate domains of 0.001–0.004/s (Fig. 3a), 0.01–0.04/s (Fig. 3b), and 0.1–0.4/s (Fig. 3c).
Figure 3

Stress state comparison. Stress state comparisons at various strain rate domains are shown. (a) Domain of 0.001–0.004/s, i.e., 0.001/s for tension (green), 0.0025/s for compression (red), 0.004 for shear (blue); all at a displacement rate of 40 μm/s. (b) Domain of 0.01–0.04/s, i.e., 0.01/s for tension (green), 0.025/s for compression (red), 0.04 for shear (blue); all at a displacement rate of 400 μm/s. (c) Domain of 0.1–0.4/s, i.e., 0.1/s for tension (green), 0.25/s for compression (red), 0.4 for shear (blue); all at a displacement rate of 4000 μm/s

The large-strain elastic modulus and extensibility of the placenta tissue were compared among different stress states at various strain rates (Fig. 4). For all three strain rates, the large-strain elastic modulus showed an increasing trend in the order of shear, compression, and tension (Fig. 4a), and the extensibility showed a decreasing trend in the order of shear, compression, and tension (Fig. 4b). It is important to note that, while total deformation of tissues was quite large in compression and shear, failures were not always observed. Because of this, the reported large-strain elastic moduli of compression and shear were likely underestimated.
Figure 4

Stress-state and rate dependence of large-strain elastic modulus and extensibility. (a) Large-strain elastic modulus and (b) tissue extensibility. Stress-states are colored as follows: shear = blue, compression = red, and tension = green. Strain rate domains are organized as in Fig. 3

SEM micrographs (Fig. 5) of the human placenta showed a highly randomized size and distribution of small blood vessels. These vessels varied greatly in alignment leading to a very tortuous (Figs. 5a and 5b) and entangled (Figs. 5c and 5d) network.
Figure 5

SEM of human placenta. SEM micrographs of placenta at 500× magnification are shown. Scale bars in the lower left of each micrograph are 100 μm. (a) and (b) were prepared by scalpel dissection, (c) and (d) were prepared by cryofracture

The interrupted mechanical tests (Figs. 68) showed that the human placenta tissue exhibited various microstructure behaviors in response to different loading states. The undeformed placenta consists of a relatively disordered network of blood vessels of different sizes with little or no preferred direction and the surrounding blood cells (Figs. 6a and 6b). Under tension, as the deformation increased to 22.3% true strain, the blood vessels, especially the larger vessels, were kinematically recruited into tension and align along the primary loading axis (Figs. 6c and 6d) much like texture in synthetic polymers. This motion from an initially isotropic orientation to a preferred orientation is the so-called texture effect in which the kinematics from the loading direction reorients the material (blood vessels). An increase in the appearance of intervascular spaces has also been shown (Figs. 6c and 6d). As the tensile strain neared failure at 40.5% true strain, only the largest vessels were still aligned to the direction of loading, while the smaller vessels appeared to have failed, allowing them to return to a recoiled configuration (Figs. 6e and 6f). At 40.5% true strain, the intervascular spaces further increased (Figs. 6e and 6f).
Figure 6

Histology of interrupted tension tests. H&E histology of placenta in tension at 100× magnification is shown. Scale bars in the lower left of each micrograph are 200 μm, and arrows indicate direction of tension. (a) and (b) are undeformed tissues, (c) and (d) are tissues at 22.3% true strain, (e) and (f) are tissues at 40.5% true strain

The placenta microstructure also showed blood vessels to have a relatively circular cross-section in the undeformed state (Figs. 7a and 7b). As the compressive strain increased to 35.7% true strain, the vessels began to collapse, with the vessel cross-sections deformed into elliptical (or elongated) shapes, and the long axes of elliptical (elongated) shapes aligned perpendicular to the loading direction (Figs. 7c and 7d), again following kinematic constraints similar to texture evolution in polymers. At 91.6% compressive true strain, the vessels were highly collapsed and elongated, as well as compacted to the point of having almost no space within or between vessels (Figs. 7e and 7f). The intervascular space was tremendously reduced at 91.6% compressive true strain.
Figure 7

Histology of interrupted compression tests. H&E histology of placenta in compression at 100× magnification is shown. Scale bars in the lower left of each micrograph are 200 μm, and arrows indicate direction of compression. (a) and (b) are undeformed placenta tissues, (c) and (d) are tissues at 35.7% true strain, and (e) and (f) are tissues at 91.6% true strain

The microstructure evolution under shear showed a diagonal vessel alignment towards the shearing direction driven by the kinematics, as well as the presence of vessel morphologies similar to that of tensile and compressive microstructure in local regions (Fig. 8). As the shear loading increased to 39% strain, regions of vessel collapse and intervascular space growth were observed (Figs. 8c and 8d). At 79% shear strain, vessels were highly aligned along the diagonal direction of load with significantly larger intervascular spaces (Figs. 8e and 8f).
Figure 8

Histology of interrupted shear testing. H&E histology of placenta in shear at 100× magnification is shown. (a) and (b) are undeformed placenta tissues, (c) and (d) are tissues under 39% true shear strain, and (e) and (f) are tissues under 79% true shear strain. Arrows indicate direction of shear

Discussion

Strain rate comparisons for each stress-state reaffirmed the rate dependence of the placenta under tension but also introduced the notion of varied responses to compression and shear.

For compression the human placenta showed greater stresses and lesser extensibility at 0.25/s when compared to 0.025 or 0.0025/s; the trend continued when comparing the responses at 0.025–0.0025/s (Fig. 2b). Since the placenta comprises mainly small blood vessels, we believe compression to be highly affected by the fluid flowing out of these vessels. Note that the toe region of compressive stress–strain behavior is very long and shallow (Fig. 2b), which possibly implies fluid flowing from collapsing vessels with little resistance. The linear region is very steep and abrupt as the mechanical response shifts from vessel collapse to the compaction of collapsed vessels (Fig. 2b). At 0.25/s, the strain rate is high enough to experience greater resistance of flow from the collapsing vessels in both the transition region and linear region. Moreover, 0.025 and 0.0025/s are relatively slow allowing the fluid to flow with less resistance, hence lower displacement rates display a more abrupt increase in mechanical resistance at the transition region corresponding to the fully collapsed vessels.

The shear stress–strain behavior had a trend similar to compression in terms of the strain rate dependence (Fig. 2c). The shear curves for 0.04 and 0.004/s are very similar with long shallow toe region and an abrupt, steep linear region. 0.4/s in shear incurred higher stresses but smaller strains, with a less abrupt transition region.

The tension stress–strain behavior did not show a strong difference among the applied strain rates (Fig. 2a). This observation coincides well with previous tensile studies,26,27 which shows a rate dependence occurring between 7 and 0.7/s but no obvious rate dependence between 0.7 and 0.07/s. A strain-rate normalization of our data reduces our tension strain rates to 0.1, 0.01, and 0.001/s, which is not high enough to elicit a strong rate-dependence under tension.27 The tensile failure reported for true stress appears consistent with those reported in other studies; however, true strain values appears to be somewhat higher despite using a similar preload value.21,26,27 Possible contributions for the variation include that our strain rates were not as high as other studies, our testing configuration in which the specimen is fully submerged in saline throughout the test, or the use of preconditioning which was not clearly reported in the method sections of the previous studies.20,26,27

Stress-state comparisons at each strain rate domain show very clear and important results. Most apparent is the relatively low stress-state in shear when compared to tension and compression stress–strain behavior (Fig. 3). Because the placenta has a less significant shear stiffness as indicated by this data, shear loading could possibly be problematic. The tensile stiffness was very high as compared to shear. The stress-state dependence observed in this study highlights the importance of addressing how different stress states are related to the injury mechanisms of placenta abruption in the real world.

Histology of interrupted tension tests revealed that the tensile loading is dominated by blood vessel recruitment driven by kinematic texture and ultimately blood vessel failure, similar to the kinematically-driven mechanism of collagen fiber recruitment observed in other biological materials such as tendon and heart valve.22,25,35 Histology of the interrupted compression tests showed vessel collapse and compaction that dominated the compressive response of the placenta. In shear, blood vessel recruitment occurred diagonally from the kinematic rotational spin as the strain increased; later, blood vessel failure occurred as revealed by the histology results. The interrupted tests showed the deformation of blood vessels induced recruitment such that the morphological changes occurred. This gave rise to structural changes similar to textural softening as is often described in texture analysis (see Horstemeyer and co-workers8,19 for example). This is also important related to placental detachment, which is likely caused by a complex multiaxial loading event, involving the incremental failure of discrete microstructure elements that connect the placenta and uterus. As the placenta-uterus connections fail, the placental detachment increases, potentially leading to full abruption and termination of the pregnancy. Studying this interface from a mechanical standpoint remains a difficult research problem due to the ethical and logistical issues of procuring human samples, or appropriately similar animal specimens.

Future studies will include assessment of Poisson’s ratio of the human placenta to allow more accurate true stress–strain calculations than our current assumptions. Research is also being conducted to prepare structure-based constitutive relationships from our mechanical and structural characterizations. These relationships will provide more accurate description of the mechanical behavior in computational simulations of biological tissues. Further research should be conducted to evaluate failure in shear and compression, as well as the failure properties of the utero-placental junction.

Limitations

The fact that displacement rate, as opposed to normalized strain rate, was held constant across stress states is a limitation of this study. Using the same normalized strain rates would more directly compare the different stress states. However, this limitation did not affect our conclusions on stress state dependence and strain rate dependence. Furthermore, our strain rates were not as high as those in other studies, which limits the degree to which the strain-rate sensitivity was elucidated. Strain and stress calculations are based on the grip-to-grip gauge length and the average tissue cross-section, respectively. For both sample dimension and strain measurement, our current method is less preferred than optical measurement techniques which better account for variation within sample. Optical tracking of local deformation provides a better indication of the strain field across the tissue, as compared with grip-to-grip measurement. Another limitation concerning dogbone shaped specimens for tensile testing involves consistency uniform middle region. Our specimens were prepared by hand dissection, assisted with cutting patterns. This has the advantage of allowing us to cut with minimal tissue deformation, but the disadvantage of being manually performed and therefore less reproducible. The natural tendency of human placenta to relax under stress may interfere with our interrupted mechanical testing. Since stress-relaxation begins immediately after loading, while formaldehyde fixation processes require hours to complete, the final fixed tissue sample may not exactly mirror the loading state being evaluated. Nevertheless, the significant microstructure alterations at different strain level (Figs. 68) demonstrate the effectiveness of tissue fixation in the interrupted mechanical testing to reveal internal structural evolution.

Conclusions

Our study reaffirmed previous observations of the strain rate dependence of the human placenta in tension and extended those observations to compressive and shear loading. We further demonstrated that the human placenta behaved quite differently under the different loading states with the placenta exhibiting greater stresses in tension, lesser stresses in compression, and the least in shear at the same strain levels. At 50% strain, the tensile stresses were approximately one order of magnitude greater indicating the greater resistance to the loading. Tissue extensibility exhibited an opposite trend: the highest extensibility in shear, less in compression, and least in tension. These results are important, because multi-axial loading conditions associated with trauma cannot be accurately simulated without constitutive relationships that account for this stress state difference. We further demonstrated that the human placenta undergoes a distinct microstructure evolution for each of the stress states observed. The reported data are important for creating structure-based constitutive models that capture complex tissue behaviors and consequently enable accurate computational simulations of MT in various boundary conditions.

Notes

Acknowledgments

This study is supported by the MAFES SRI (awarded to JL) and Health Resources and Services Administration (HRSA) (DHHS R1CRH10429-01-00). We thank Karen Tiffen, RNC, Chrissy Poole, RNC, Dana Brooks, RNC, Cindy Patton, RN, Heather McMillian, ST, Bella Oswalt, ST, Sonya Anderson, RN, Rene Guines, ST, and other staff members of the Labor & Delivery Unit at OCH Regional Medical Center for their assistance with patient eligibility and tissue procurement; we also appreciate help from Amanda Lawrence (MSU EM Center) for her assistance in SEM imaging. We would also like to thank the Center for Advanced Vehicular Systems (CAVS) at the Mississippi State University for helping to support this research effort.

References

  1. 1.
    Abbassi-Ghanavati, M., B. M. Casey, C. Y. Spong, D. D. McIntire, L. M. Halvorson, and F. G. Cunningham. Pregnancy outcomes in women with thyroid peroxidase antibodies. Obstet. Gynecol. 116:381–386, 2010.PubMedCrossRefGoogle Scholar
  2. 2.
    Aboutanos, M. B. M. D. M. P. H., S. Z. M. D. Aboutanos, D. B. S. Dompkowski, T. M. M. D. Duane, A. K. M. D. Malhotra, and R. R. M. D. Ivatury. Significance of motor vehicle crashes and pelvic injury on fetal mortality: a five-year institutional review. J. Trauma-Inj. Infect. Crit. Care 65:616–620, 2008.CrossRefGoogle Scholar
  3. 3.
    Ananth, C. V., Y. Oyelese, L. Yeo, A. Pradhan, and A. M. Vintzileos. Placental abruption in the united states, 1979 through 2001: temporal trends and potential determinants. Am. J. Obstet. Gynecol. 192:191–198, 2005.PubMedCrossRefGoogle Scholar
  4. 4.
    Ananth, C. V., D. A. Savitz, and M. A. Williams. Placental abruption and its association with hypertension and prolonged rupture of membranes: a methodologic review and meta-analysis. Obstet. Gynecol. 88:309–318, 1996.PubMedCrossRefGoogle Scholar
  5. 5.
    Begonia, M., R. Prabhu, J. Liao, M. Horstemeyer, and L. Williams. The influence of strain rate dependency on the structure–property relations of porcine brain. Ann. Biomed. Eng. 38:3043–3057, 2010.PubMedCrossRefGoogle Scholar
  6. 6.
    Carew, E. O., J. Patel, A. Garg, P. Houghtaling, E. Blackstone, and I. Vesely. Effect of specimen size and aspect ratio on the tensile properties of porcine aortic valve tissues. Ann. Biomed. Eng. 31:526–535, 2003.PubMedCrossRefGoogle Scholar
  7. 7.
    Chames, M. C. M., and M. D. M. Pearlman. Trauma during pregnancy: outcomes and clinical management. Clin. Obstet. Gynecol. 51:398–408, 2008.PubMedCrossRefGoogle Scholar
  8. 8.
    Clemmer, J., J. Liao, D. Davis, M. F. Horstemeyer, and L. N. Williams. A mechanistic study for strain rate sensitivity of rabbit patellar tendon. J. Biomech. 43:2785–2791, 2010.PubMedCrossRefGoogle Scholar
  9. 9.
    Colgan, N. C., M. D. Gilchrist, and K. M. Curran. Applying DTI white matter orientations to finite element head models to examine diffuse TBI under high rotational accelerations. Prog. Biophys. Mol. Biol. 103:304–309, 2010.PubMedCrossRefGoogle Scholar
  10. 10.
    Connolly, A. M., V. L. Katz, K. L. Bash, M. J. McMahon, and W. F. Hansen. Trauma and pregnancy. Am. J. Perinatol. 14:331–336, 1997.PubMedCrossRefGoogle Scholar
  11. 11.
    Daria, C. R. Trauma care and managing the injured pregnant patient. J. Obstet. Gynecol. Neonatal. Nurs. 38:704–714, 2009.CrossRefGoogle Scholar
  12. 12.
    Delotte, J., M. Behr, L. Thollon, P.-J. Arnoux, P. Baque, A. Bongain, and C. Brunet. Pregnant woman and road safety: experimental crash test with post mortem human subject. Surg. Radiol. Anat. 30:185–189, 2008.PubMedCrossRefGoogle Scholar
  13. 13.
    Dighe, M., A. Gokhale, and M. Horstemeyer. Effect of loading condition and stress state on damage evolution of silicon particles in an Al–Si–Mg-base cast alloy. Metall. Mater. Trans. A 33:555–565, 2002.CrossRefGoogle Scholar
  14. 14.
    Duma, S. M. Pregnant Occupants Biomechanics: Advances in Automobile Safety Research. Warrendale, PA: Society of Automotive Engineers, 2010.Google Scholar
  15. 15.
    Fung, Y. C. Biomechanics: Mechanical Properties of Living Tissues. New York: Springer, 1981.Google Scholar
  16. 16.
    Gao, Z., and J. P. Desai. Estimating zero-strain states of very soft tissue under gravity loading using digital image correlation. Med. Image Anal. 14:126–137, 2010.PubMedCrossRefGoogle Scholar
  17. 17.
    Hall, D. R. Abruptio placentae and disseminated intravascular coagulopathy. Semin. Perinatol. 33:189–195, 2009.PubMedCrossRefGoogle Scholar
  18. 18.
    Hitosugi, M., Y. Motozawa, M. Kido, T. Yokoyama, H. Kawato, K. Kuroda, and S. Tokudome. Traffic injuries of the pregnant women and fetal or neonatal outcomes. Forensic Sci. Int. 159:51–54, 2006.PubMedCrossRefGoogle Scholar
  19. 19.
    Horstemeyer, M. F., J. Lathrop, A. M. Gokhale, and M. Dighe. Modeling stress state dependent damage evolution in a cast Al–Si–Mg aluminum alloy. Theor. Appl. Fract. Mech. 33:31–47, 2000.CrossRefGoogle Scholar
  20. 20.
    Hu, J., K. D. Klinich, C. S. Miller, G. Nazmi, M. D. Pearlman, L. W. Schneider, and J. D. Rupp. Quantifying dynamic mechanical properties of human placenta tissue using optimization techniques with specimen-specific finite-element models. J. Biomech. 42:2528–2534, 2009.PubMedCrossRefGoogle Scholar
  21. 21.
    Hu, J., K. Klinich, C. Miller, J. Rupp, G. Nazmi, M. Pearlman, and L. Schneider. A stochastic visco-hyperelastic model of human placenta tissue for finite element crash simulations. Ann. Biomed. Eng. 39:1074–1083, 2011.PubMedCrossRefGoogle Scholar
  22. 22.
    Kastelic, J., and E. Baer. Deformation of tendon collagen. In: The Mechanical Properties of Biological Materials, edited by J. F. Vincient, and J. D. Currey. Cambridge: Society for Experimental Biology, 1980, pp. 397–433.Google Scholar
  23. 23.
    Klinich, K. D., C. A. C. Flannagan, J. D. Rupp, M. Sochor, L. W. Schneider, and M. D. Pearlman. Fetal outcome in motor-vehicle crashes: effects of crash characteristics and maternal restraint. Am. J. Obstet. Gynecol. 198:450.e451–450.e459, 2008.CrossRefGoogle Scholar
  24. 24.
    Lee, J. B., and K. H. Yang. Development of a finite element model of the human abdomen. Stapp Car Crash J. 45:79–100, 2001.PubMedGoogle Scholar
  25. 25.
    Liao, J., L. Yang, J. Grashow, and M. S. Sacks. The relation between collagen fibril kinematics and mechanical properties in the mitral valve anterior leaflet. J. Biomech. Eng. 129:78–87, 2007.PubMedCrossRefGoogle Scholar
  26. 26.
    Manoogian, S. J., J. A. Bisplinghoff, C. McNally, A. R. Kemper, A. C. Santago, and S. M. Duma. Dynamic tensile properties of human placenta. J. Biomech. 41:3436–3440, 2008.PubMedCrossRefGoogle Scholar
  27. 27.
    Manoogian, S. J., J. A. Bisplinghoff, C. McNally, A. R. Kemper, A. C. Santago, and S. M. Duma. Effect of strain rate on the tensile material properties of human placenta. J. Biomech. Eng. 131:091008, 2009.PubMedCrossRefGoogle Scholar
  28. 28.
    Mattox, K. L. M. D., and L. M. D. Goetzl. Trauma in pregnancy. Crit. Care Med. Crit. Illn. Pregnancy 33:S385–S389, 2005.Google Scholar
  29. 29.
    Moorcroft, D. M., J. D. Stitzel, G. G. Duma, and S. M. Duma. Computational model of the pregnant occupant: predicting the risk of injury in automobile crashes. Am. J. Obstet. Gynecol. 189:540–544, 2003.PubMedCrossRefGoogle Scholar
  30. 30.
    Moorcroft, D., J. Stitzel, S. Duma, and G. Duma. The effects of uterine ligaments on fetal injury risk in frontal automobile crashes. Proc. Inst. Mech. Eng. D: J. Automob. Eng. 217:1049–1055, 2003.CrossRefGoogle Scholar
  31. 31.
    Motozawa, Y., M. Hitosugi, T. Abe, and S. Tokudome. Effects of seat belts worn by pregnant drivers during low-impact collisions. Am. J. Obstet. Gynecol. 203(1):62.e1–62.e8, 2010.CrossRefGoogle Scholar
  32. 32.
    Nyein, M. K., A. M. Jason, L. Yu, C. M. Pita, J. D. Joannopoulos, D. F. Moore, and R. A. Radovitzky. In silico investigation of intracranial blast mitigation with relevance to military traumatic brain injury. Proc. Natl. Acad. Sci. 107:20703–20708, 2010.PubMedCrossRefGoogle Scholar
  33. 33.
    Oxford, C. M. M., and J. B. Ludmir. Trauma in pregnancy. Clin. Obstet. Gynecol. 52:611–629, 2009.PubMedCrossRefGoogle Scholar
  34. 34.
    Rupp, J. D. K. K., S. Moss, J. Zhou, M. D. Pearlman, and L. W. Schneider. Development and testing of a prototype pregnant abdomen for the small-female hybrid III ATD. Stapp Car Crash J. 45:18, 2001.Google Scholar
  35. 35.
    Viidik, A. Simultaneous mechanical and light microscopic studies of collagen fibers. Zeitschrift fur Anatomie und Entwicklungsgeschichte 136:204–212, 1972.PubMedCrossRefGoogle Scholar
  36. 36.
    Weaver, A. A., K. L. Loftis, S. M. Duma, and J. D. Stitzel. Biomechanical modeling of eye trauma for different orbit anthropometries. J. Biomech. 44:1296–1303, 2011.PubMedCrossRefGoogle Scholar
  37. 37.
    Wren, T. A., and D. R. Carter. A microstructural model for the tensile constitutive and failure behavior of soft skeletal connective tissues. J. Biomech. Eng. 120:55–61, 1998.PubMedCrossRefGoogle Scholar
  38. 38.
    Yamada, H. Strength of Biological Materials. Baltimore: Williams and Wilkinson, 1970.Google Scholar
  39. 39.
    Yu, M., S. Manoogian, S. M. Duma, and J. D. Stitzel. Finite element modeling of human placental tissue. Ann. Adv. Automot. Med. 53:257–270, 2009.PubMedGoogle Scholar

Copyright information

© Biomedical Engineering Society 2012

Authors and Affiliations

  • Benjamin C. Weed
    • 1
    • 2
  • Ali Borazjani
    • 1
  • Sourav S. Patnaik
    • 1
    • 2
  • R. Prabhu
    • 1
    • 2
  • M. F. Horstemeyer
    • 2
  • Peter L. Ryan
    • 3
  • Thomas Franz
    • 4
  • Lakiesha N. Williams
    • 1
    • 2
  • Jun Liao
    • 1
    • 2
  1. 1.Tissue Bioengineering Laboratory, Department of Agricultural and Biological EngineeringMississippi State UniversityMississippi StateUSA
  2. 2.Center for Advance Vehicular SystemsMississippi State UniversityMississippi StateUSA
  3. 3.Department of Animal and Dairy SciencesMississippi State UniversityMississippi StateUSA
  4. 4.Cardiovascular Research Unit and Centre for Research in Computational and Applied MechanicsUniversity of Cape TownCape TownSouth Africa

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