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R01HD109739

Project Grant

Overview

Grant Description
A Placenta-Based Strategy for Improved Clinical Prediction of Fetal Growth Trajectory Using Automated Image Analysis of Placental Morphology and Vascularity - 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 role in maintaining a healthy pregnancy and supporting fetal growth. However, 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.

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.
Funding Goals
NOT APPLICABLE
Place of Performance
Nashville, Tennessee 37203 United States
Geographic Scope
Single Zip Code
Analysis Notes
Amendment Since initial award the total obligations have increased 412% from $604,173 to $3,092,817.
Vanderbilt University was awarded Automated Placental Analysis for Enhanced Fetal Growth Prediction Project Grant R01HD109739 worth $3,092,817 from the National Institute of Child Health and Human Development in September 2022 with work to be completed primarily in Nashville Tennessee United States. The grant has a duration of 4 years 9 months and was awarded through assistance program 93.865 Child Health and Human Development Extramural Research. The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).

Status
(Ongoing)

Last Modified 6/22/26

Period of Performance
9/5/22
Start Date
6/30/27
End Date
79.0% Complete

Funding Split
$3.1M
Federal Obligation
$0.0
Non-Federal Obligation
$3.1M
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to R01HD109739

Subgrant Awards

Disclosed subgrants for R01HD109739

Transaction History

Modifications to R01HD109739

Additional Detail

Award ID FAIN
R01HD109739
SAI Number
R01HD109739-1885440942
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NT00 NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development
Funding Office
75NT00 NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development
Awardee UEI
GTNBNWXJ12D5
Awardee CAGE
5E694
Performance District
TN-05
Senators
Marsha Blackburn
Bill Hagerty

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
National Institute of Child Health and Human Development, National Institutes of Health, Health and Human Services (075-0844) Health research and training Grants, subsidies, and contributions (41.0) $1,231,326 100%
Modified: 6/22/26