Fetal lung-to-liver signal intensity ratio at MR imaging: Development of a normal scale and possible role in predicting pulmonary hypoplasia in utero

Lee J. Brewerton, Radha S. Chari, Yuanyuan Liang, Ravi Bhargava

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Abstract

PURPOSE: To define retrospectively a normal range for lung-to-liver signal intensity ratio (LLSIR) in fetuses of 16-40 weeks gestation by using half-Fourier single-shot turbo spin-echo magnetic resonance (MR) imaging. MATERIALS AND METHODS: Approval from the regional ethics review board for retrospective evaluation was obtained, and informed consent was waived. Retrospective analysis and follow-up of 157 pregnant women who underwent MR imaging over the past 4 years were performed. Seventy-four fetuses were subsequently identified as having clinically normal lung function or normal lung morphologic - features at autopsy. A total of 141 normal lungs were analyzed, and the LLSIR was calculated from images on an MR workstation. A mixed-effects statistical model was applied, and 95% prediction intervals were calculated. Ten fetuses with hypoplastic lungs at autopsy were also evaluated. RESULTS: Plotting LLSIR against gestational age demonstrated that, according to the fitted mean curve, the signal intensity ratio was higher with more advanced gestational age. Statistical modeling suggests a quadratic relationship between gestational age and LLSIR. For fetuses in the normal population, the LLSIR ranged from 1.52 at 21 weeks gestation to 4.31 at 34 weeks gestation. For all hypoplastic lungs in fetuses at or beyond 25 weeks gestation, the LLSIR was outside the lower bound of the 95% prediction interval for the normal population. The distinction between hypoplastic lungs and normal lungs at less than 25 weeks gestation is less definitive. CONCLUSION: This study provides a normal scale with a 95% prediction interval for LLSIR.

Original languageEnglish (US)
Pages (from-to)1005-1010
Number of pages6
JournalRadiology
Volume235
Issue number3
DOIs
StatePublished - Jun 1 2005

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ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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