Evidence map›Paper›PMID 40902262›Full record

ArticlePlacenta2025

Association of deep learning-derived histologic features of placental chorionic villi with maternal and infant characteristics in the New Hampshire birth cohort study.

Elizabeth C Anderson, Gokul Srinivasan, Caitlin G Howe, Edward Zhang, Catherine Jeon, Gnan Suchir Gupta Paruchuri, Leah Zhang, Lindsay Hwang, Aditya Sengar, Neha Reddy and 15 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Placenta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors.

Elizabeth C AndersonDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Gokul SrinivasanDepartment of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA; University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA.
Caitlin G HoweDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Edward ZhangDartmouth College, Hanover, NH, USA.
Catherine JeonThomas Jefferson High School for Science and Technology, Alexandria, VA, USA; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA.
Gnan Suchir Gupta ParuchuriEmerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA; Independence High School, Frisco, TX, USA.
Leah ZhangThomas Jefferson High School for Science and Technology, Alexandria, VA, USA; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA.
Lindsay HwangEmerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA; Georgia Institute of Technology, Atlanta, GA, USA.
Aditya SengarThomas Jefferson High School for Science and Technology, Alexandria, VA, USA; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA.
Neha ReddyEmerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA; The University of Texas at Austin, Austin, TX, USA.
Anmol KaranThomas Jefferson High School for Science and Technology, Alexandria, VA, USA; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA.
Andrew ChenThomas Jefferson High School for Science and Technology, Alexandria, VA, USA; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, NH, Lebanon, USA.
Julia ShenDartmouth College, Hanover, NH, USA.
Onyinyechi OwoDartmouth College, Hanover, NH, USA.
ZoëFaith Caraballo-BobeaDartmouth College, Hanover, NH, USA.
Camilo KhatchikianDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Thomas J PalysDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Louis J VaickusDepartment of Pathology, Dartmouth-Hitchcock Medical Center, NH, Lebanon, USA.
Keluo YaoDepartment of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Fabiola MedeirosDepartment of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Helen NguyenDepartment of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Juliette C MadanDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Margaret R KaragasDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA.
Jessica L BentzDepartment of Pathology, Dartmouth-Hitchcock Medical Center, NH, Lebanon, USA.
Joshua J LevyDepartment of Epidemiology, Geisel School of Medicine at Dartmouth, NH, Lebanon, USA; Department of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA; University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA. Electronic address: joshua.levy@cshs.org.

Funding

A prospective study of critical environmental exposures in formative early life that impact lifelong health in rural US children: the New Hampshire Birth Cohort StudyUH3OD023275 · OD · DARTMOUTH COLLEGE · PI MARGARET Rita KARAGAS, Juliette Madan · 2018 to 2026
$44.3M
Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI MICHAEL L WHITFIELD · 2019 to 2026
$27.2M
Relation Between In-utero Vitamin D and Immune Function in Early Childhood P20GM104416 · NIGMS · DARTMOUTH COLLEGE · PI SALAS DIAZ, LUCAS A · 2013 to 2022
$23.7M
A prospective study of critical environmental exposures in formative early life that impact lifelong health in rural US children: the New Hampshire Birth Cohort StudyUG3OD023275 · OD · DARTMOUTH COLLEGE · PI KARAGAS, MARGARET RITA, MADAN, JULIETTE · 2016 to 2024
$17.9M
Project 3: Placental Biomarkers of Exposure and Outcome (Marsit)P01ES022832 · NIEHS · DARTMOUTH COLLEGE · PI KARAGAS, MARGARET RITA · 2013 to 2018
$4.7M
NIEHS NIH HHS P01 ES022832NIGMS NIH HHS P20 GM104416NIGMS NIH HHS P20 GM130454NIH HHS UG3 OD023275NIH HHS UH3 OD023275
6 · The paper itself

Abstract

introductionQuantification of placental histopathological structures is challenging due to a limited number of perinatal pathologists, constrained resources, and subjective assessments prone to variability. Objective standardization of placental structure is crucial for easing the burden on pathologists, gaining deeper insights into placental growth and adaptation, and ultimately improving maternal and fetal health outcomes.

methodsLeveraging advancements in deep-learning segmentation, we developed an automated approach to detect over 9 million placenta chorionic villi from 1531 term placental whole slide images from the New Hampshire Birth Cohort Study. Using unsupervised clustering, we successfully identified biologically relevant villi subtypes that align with previously reported classifications - terminal, mature intermediate, and immature intermediate - demonstrating consistent size distributions and comparable abundance. We additionally defined tertile-based combinations of villi area and circularity to characterize villous geometry. This study applies these cutting-edge AI methods to quantify villi features and examine their association with maternal and infant characteristics, including gestational age at delivery, maternal age, and infant sex.

resultsIncreasing gestational age at delivery was statistically significantly associated (p = 0.003) with an increase in the proportion of mature intermediate villi and a decrease in the proportion of the smallest, most circular villi (p < 0.001). Maternal age and infant sex were not statistically significantly associated with measures of villous geometry. DISCUSSION: This work presents a workflow that objectively standardizes chorionic villi subtypes and geometry to enhance understanding of placental structure and function, while providing insights into the efficiency, growth, and the architecture of term placentas which can be used to inform future clinical care.

Indexed as

Chorionic VilliDeep LearningPlacentaAdultBirth CohortCohort StudiesFemaleGestational AgeHumansInfant, NewbornMaleNew HampshirePregnancyChorionic villiDeep learningGestational age at deliveryPlacental maturationPlacental villi segmentationVilli morphology

Identifiers

PMID40902262
PMCPMC13245368

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.