# Retinal and choroidal vasculature changes in healthy and high-risk pregnancies

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $190,363

## Abstract

Project Summary/Abstract:
This application requests funding for a project to improve maternal fetal healthcare using retinal pictures called
optical coherence tomography angiography. Pregnancy is a complex process that can lead to complications
such as preterm birth and preeclampsia. Preterm birth occurs in about 1 out of 10 pregnancies and is increasing
due to increasing rates of in vitro fertilization, advanced maternal age, and multiple gestations. Preeclampsia,
occurring in about 5-8% of all pregnancies, is an important cause of maternal morbidity and mortality throughout
the world. This study will image pregnant women with optical coherence tomography angiography throughout
pregnancy and then follow them until after the completion of pregnancy. The study hypothesizes that there will
be early findings on retinal imaging that will be able to predict late-term pregnancy complications such as preterm
birth and preeclampsia. We will maximize recruitment and retention by utilizing a large high-volume clinic in an
academic center and placing a camera on site. Through the completion of this research, we hope to develop a
way to better monitor high risk pregnancies and enable the study of early interventions.

## Key facts

- **NIH application ID:** 10089448
- **Project number:** 5R21EY030295-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Irena Tsui
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $190,363
- **Award type:** 5
- **Project period:** 2020-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10089448

## Citation

> US National Institutes of Health, RePORTER application 10089448, Retinal and choroidal vasculature changes in healthy and high-risk pregnancies (5R21EY030295-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10089448. Licensed CC0.

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