Am J Perinatol 2016; 33(13): 1306-1312
DOI: 10.1055/s-0036-1586508
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

First Trimester Detection of Placental Disease: Challenges and Opportunities

Carolyn M. Salafia
1   Placental Modulation Laboratory, Institute for Basic Research, Staten Island, New York
2   Division of Predictive Modeling, Placental Analytics, New Rochelle, New York
Diana M. Thomas
3   Center for Quantitative Obesity Research, Montclair State University, Montclair, New Jersey
Drucilla J. Roberts
4   Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
Jennifer K. Straughen
5   Department of Public Health Sciences, Henry Ford Hospital, Detroit, Michigan
Patrick M. Catalano
6   Clinical Research Unit, Case Western Reserve University, Cleveland, Ohio
7   Center for Reproductive Health, Department of Obstetrics and Gynecology, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio
Gabriela Perez-Avilan
2   Division of Predictive Modeling, Placental Analytics, New Rochelle, New York
› Author Affiliations
Further Information

Publication History

29 February 2016

21 June 2016

Publication Date:
04 August 2016 (online)


It is generally agreed that placental pathology accounts for the majority of perinatal morbidity and mortality. If a placental prodrome could be diagnosed in vivo, risk for maternal or fetal complications could be estimated and acted upon before clinical symptoms are apparent. This is especially relevant in early diagnoses of gestational diabetes mellitus, which can be controlled through carefully monitored diet and activity changes. To meet this important need, there have been increased efforts to identify early gestation biomarkers of placental dysfunction using innovative imaging technologies. Here we outline innovative quantitative markers of placental shape and their relationship to placental function, clinical implications of these quantifiers, and the most recent mathematical models that utilize placental images to delineate at risk from normal pregnancies. We propose that novel contexts of readily available placental measures and routine collection of in vivo placental images in all pregnancies may be all that are needed to advance the identification of early risk determination of complicated pregnancies from placental images.

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