A Computational Framework for the Clinical Evaluation of the Soft Tissue Mechanics in Pregnancy

项目总结/文摘

PROJECT SUMMARY/ABSTRACT Despite advances in prenatal care, the rate of preterm birth in the US and around the world remains on the rise. This fact underscores how little we know about the causes of preterm birth, which is a leading cause of neonatal deaths. Our ultimate research goal is to reduce the preterm birth rate and the associated emotional and societal costs by providing a validated computational framework to identify the potential for mechanical dysfunction in pregnancy. Researchers and clinicians know that the healthy mechanical function of soft tissues surrounding the fetus is crucial for a successful pregnancy. Particularly, the uterus, fetal membrane, and cervix must withstand mechanical forces to protect, support, and maintain an optimal growth environment for the developing baby. The magnitude of stress and stretch of these tissues are thought to control physiologic processes that regulate tissue growth, remodeling, contractility, and rupture, and it is generally hypothesized that these mechanical signals are clinical cues for normal labor and preterm birth. Yet, the mechanical stress and stretch of these tissues during pregnancy have not been determined, limiting the understanding of vital mechnobiology processes in pregnancy. To understand what causes the mechanical dysfunction in pregnancy, we will build a finite element (FE) simulation framework to identify the anatomical and/or material factors that drive uterine, cervical, and fetal membrane tissue remodeling and deformation. To build and validate these computational models we will longitudinally measure the anatomical features and cervical tissue properties of pregnant patients who are at low- risk for preterm birth throughout pregnancy. We will also conduct multi-scale structure-function studies on ex vivo cervical, uterine, and fetal membrane tissue to equip our model with features of the underlying tissue ultrastructure. We will then construct a flexible, parameterized FE framework that can directly incorporate our experimental measurements. Lastly, we will validate the FE framework by assessing the predictive capabilities of the model based on experimental evidence, and we will conduct a sensitivity study of material and geometric parameters to uncover the driving factors of tissue stress and stretch. Upon completion of our proposed research study, we will have a computational model of pregnancy that can identify the mechanistic cause of cervical, uterine, and fetal membrane deformation and guide the development of appropriate clinical studies that target women who are at high-risk for preterm birth.