A placenta-based strategy for improved clinical prediction of fetal growth trajectory using automated image analysis of placental morphology and vascularity

点击翻译按钮获取中文摘要

PROJECT SUMMARY/ABSTRACT Fetal growth restriction is associated with a profound increase in perinatal and even long-term health risk. Antenatal care is key to optimizing outcomes and preventing stillbirth, yet up to half of growth-restricted infants are not identified during pregnancy. The placenta serves a central in maintaining a healthy pregnancy and supporting fetal growth; yet, direct assessment of placental development is glaringly absent from clinical care as there are no practical tools that enable providers to monitor placental development. In recent years, 3D ultrasound (3DUS) has allowed investigators to identify important associations between placental morphology and clinical outcomes using a variety of offline medical image analysis techniques. However, these techniques typically require extensive manual input. Moreover, we have recently developed an innovative tool based on a dynamic model of fetal-placental growth that considers placental growth in the evaluation of fetal growth and can help identify pregnancies at increased risk of growth restriction. However, this tool requires placental volume assessment, which, as mentioned above, remains impractical for clinical use. In this proposal, we will expand and enhance our automated segmentation tools to enable bedside volumetric assessment of the placenta throughout pregnancy. In addition, we will develop novel tools and parameters for assessing placental shape, gross morphology, and vascularity in an effort to identify additional features of placental development that can augment our understanding of placental development and create additional markers of placental health. Taken together, the current proposal leverages an ongoing collaboration between computer scientists and physician-scientists to utilize modern fully automated image analysis methodology to create clinically impactful placental assessment tools that can be integrated into the clinical workflow. The proposed research will allow bedside assessment of placental morphology and vascularity, which can be leveraged into precision medicine approaches and allow for more accurate and reliable surveillance of fetal growth and well-being. Specifically, we will build: 1) Refine and validate a fetal-placental growth model using automated early placental volume and placental histopathology, 2) Extend to include later gestational ages and expand the toolkit to include novel measures of placental shape and vascularity, and 3) create an augmented version of the dynamic model that incorporates the added functionality of our segmentation pipeline, as well as serum biomarkers, to result in a clinically useful tool for monitoring fetal growth. We anticipate that this proposal will significantly change clinical care and create a new, placenta-based paradigm for understanding and managing fetal growth disorders.