# Developing a virtual placenta biobank

> **NIH NIH K08** · NORTHWESTERN UNIVERSITY · 2023 · $18,720

## Abstract

Project Summary / Abstract
The placenta is the first organ to develop and functions as the fetal lung, kidney, gut, skin, immune and endocrine
systems. It is the cause of, and reflects changes from, most diseases in pregnancy, yet remains understudied.
This career development proposal will train me in the tools and practice of digital pathology, while I apply them
to the placenta with the hypothesis that there are reproducible, quantitative changes in the placenta that can be
modeled and used to identify abnormalities via artificial intelligence (AI).
I will create a publicly available atlas of microscopically normal placentas from throughout the 2nd and
3rd trimesters. Whole slide imaging will be performed on microscopic slides of placentas from the beginning of
the 2nd trimester (13 weeks) through post-term (42 weeks). I will lead a team to annotate tissue type, structures,
and cells. Algorithms will be trained to replicate the manual annotations. To study the changes in the placenta
over time, automated measurements will be performed to identify changes in shape, size, and cellularity of
placental structures that correlate with gestational age. This research can be used to develop a model of
placental development and study prematurity. I will demonstrate detection of diseases of pregnancy, using
preeclampsia (PreE) as an example. Placentas with microscopic changes classically seen in PreE will be
scanned and annotated and algorithms trained and tested to identify them. Like many diseases of pregnancy,
placental changes in PreE are variable and sometimes absent. Slides from PreE cases with no microscopic
abnormalities will be scanned and examined using the quantitative parameters developed for normal placentas,
testing the hypothesis that one or more of them will significantly differ between PreE cases and gestational age-
matched controls.
I am an Assistant Professor of Pathology at Northwestern University with an emerging focus in informatics and
machine learning for diseases of pregnancy. The mentor for this project is Lee D.A. Cooper, PhD, an expert in
digital pathology and machine learning. The co-mentor is David M. Aronoff, MD, an expert in maternal-child
health. Mentor and co-mentor both have a history of NIH funding and graduating mentees to independence. The
advisory committee consists of a digital pathology expert (Gutman), a pediatrician (Mestan) and a pathologist
physician scientist (Yang). They have proposed an aggressive schedule of one-on-one meetings, coursework,
seminars, and scientific meetings to supplement learning by doing the science. Completion of these studies will
build my expertise in the application of machine learning to placental pathology while creating a new, publicly-
accessible tool for the rapid assessment and understanding of organ structure and function with great potential
to improve maternal-child health.

## Key facts

- **NIH application ID:** 10692548
- **Project number:** 5K08EB030120-04
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Jeffery A Goldstein
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $18,720
- **Award type:** 5
- **Project period:** 2020-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10692548

## Citation

> US National Institutes of Health, RePORTER application 10692548, Developing a virtual placenta biobank (5K08EB030120-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10692548. Licensed CC0.

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