Calculation of gestational age in late second and third trimesters by ex vivo magnetic resonance spectroscopy of amniotic fluid

Brad R. Cohn, Emily Y. Fukuchi, Bonnie N. Joe, Mark G. Swanson, John Kurhanewicz, Jingwei Yu, Aaron B. Caughey

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Objective: The purpose of this study was to develop a reliable model for the calculation of gestational age (GA) in second and third trimesters with the use of amniotic fluid (AF) metabolite profiles that were determined by magnetic resonance spectroscopy. Study Design: High-resolution (11.7 T) ex vivo magnetic resonance spectroscopy was performed on 95 AF samples (mean, 31.7 weeks; range, 15.6-39.9 weeks). GA was determined by last menstrual period or first-trimester ultrasound scanning. Concentrations of 21 AF metabolites were measured with automated techniques. Metabolite concentrations, inverses, natural logs, and squares were entered as predictive variables in a stepwise linear regression model. Results: The following formula was derived: GA = 64.922 - (14.456 × alanine) + (4.965 × natural log [creatinine]) - (0.931 × glucose) - (5.202 × valine). This model fit the data with an R2 value of 0.926. Average error among all samples was ±1.75 weeks (SD, ±1.43 weeks), for the second trimester was ±2.21 weeks (SD, ±1.78 weeks), and for the third trimester was ±1.59 weeks (SD, ±1.26 weeks). Conclusion: Statistical modeling accurately predicted GA with amniotic fluid metabolite profiles that were obtained by magnetic resonance spectroscopy, which may represent a significant improvement over conventional ultrasound dating in the third trimester. Future studies should compare these techniques directly.

Original languageEnglish (US)
Pages (from-to)76.e1-76.e10
JournalAmerican journal of obstetrics and gynecology
Volume203
Issue number1
DOIs
StatePublished - Jul 2010
Externally publishedYes

Keywords

  • amniotic fluid
  • gestational age
  • magnetic resonance spectroscopy
  • multiple linear regression models

ASJC Scopus subject areas

  • Obstetrics and Gynecology

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