The objective of this study was to determine if magnetic resonance signal intensity measurements can be used to predict gestational age and hence fetal lung maturity.
This institutional review board–approved study was a retrospective review of 394 fetal magnetic resonance imaging cases from a single institution for the years 2001 to 2011. For each case, T1- and T2-weighted sequences were selected for data collection. A single reviewer obtained 10 regions of interest (when possible) from each scan (fetal lung, fetal liver, fetal muscle, fetal spleen, and maternal urine, for both T1- and T2-weighted sequences). The medical record was searched for relevant information including best estimate of gestational age, Apgar scores, karyotype, and fetal diagnosis. A variety of organ-to-organ ratios and direct organ signal intensity measurements were assessed for correlation with gestational age.
Three hundred thirty-five cases met inclusion criteria with gestational ages ranging from 17 to 39 weeks (mean, 28.6 weeks). A significant relationship between magnetic resonance signal intensity ratios and gestational age was demonstrated on the T2 lung-to-liver, T2 lung-to-spleen, T2 lung-to-muscle, T1 lung-to-liver, and T1 lung-to-spleen ratios (P < 0.05). T2 lung-to-liver and T2 lung-to-muscle demonstrated the strongest relationship with gestational age (best correlation r = 0.483, P < 0.001). T1 lung-to-liver and T1 lung-to-spleen demonstrated inverse relationships with gestational age (r = −0.174 [P = 0.03] and r = −0.236 [P = 0.02], respectively).
A significant correlation between multiple signal intensity ratios and gestational age is demonstrated. However, the large variances preclude a clinically useful relationship.
Abdominal Imaging Section, Department of Diagnostic Radiology, University of Utah Medical Center, Salt Lake City, Utah.
Received for publication July 17, 2013; accepted October 18, 2013.
Conflicts of interest and source of funding: none.
Reprints: Thomas C. Winter, MD, Department of Radiology, University of Utah, 30 N 1900 E RM 1A071 University Hospital, Salt Lake City, UT 84132 (e-mail: email@example.com).