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INTRODUCTION: Fetal magnetic resonance imaging (MRI) lung volume nomograms are increasingly used to prognosticate neonatal outcomes in fetuses with suspected pulmonary hypoplasia. However, pregnancies complicated by fetal anomalies associated with pulmonary hypoplasia may also be complicated by fetal growth restriction (FGR). If a small lung volume is suspected in such cases, it is often unclear whether the lungs are "small" because of underlying lung pathology, or small fetal size. Existing MRI lung volume nomograms have mostly been stratified by gestational age (GA), rather than estimated fetal weight (EFW). Therefore, we aimed to develop a novel fetal lung volume nomogram stratified by EFW. METHODS: Consecutive fetal MRIs performed at a quaternary medical center from 2019 to 2021 were analyzed. MRIs performed due to fetal lung anomalies and cases with FGR were excluded. All MRIs were performed without IV contrast on GE 3 or 1.5 Tesla scanners (GE Healthcare). Images were reviewed by three experienced fetal radiologists. Freehand ROI in square centimeter was drawn around the contours of the lungs on consecutive slices from the apex to the base. The volume of the right, left and total lungs were calculated in mL. Lung volumes were plotted by both EFW and GA. RESULTS: Among 301 MRI studies performed during the study period, 170 cases met inclusion criteria and were analyzed. MRIs were performed between 19- and 38-week gestation, and a sonographic EFW was obtained within a mean of 2.9 days (SD ± 5.5 days, range 0-14 days) of each MRI. Nomograms stratified by both EFW and GA were created using 200 g. and weekly intervals respectively. A formula using EFW to predict total lung volume was calculated: LV = 0.07497804 EFW0.88276 (R2 = 0.87). CONCLUSIONS: We developed a novel fetal lung volume nomogram stratified by EFW. If validated, this nomogram may assist clinicians predict outcomes in cases of fetal pulmonary hypoplasia with concomitant FGR.
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BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in children. To avoid limitations of liver biopsy and MRI, quantitative ultrasound has become a research focus. Ultrasound-derived fat fraction (UDFF) is based on a combination of backscatter coefficient and attenuation parameter. OBJECTIVE: The objectives of the study were to determine (1) agreement between UDFF/MRI proton density fat fraction (MR-PDFF) and (2) whether BMI and age are predictive for UDFF. MATERIALS AND METHODS: This cross-sectional prospective study included a convenience sample of 46 children referred for clinically indicated abdominal MRI. MR-PDFF and five acquisitions of UDFF were collected. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to assess agreement between MR-PDFF and UDFF. Receiver operating characteristic curves were calculated for UDFF prediction of liver steatosis (MR-PDFF ≥ 6%). Multivariable regression was performed to assess BMI and age as predictors for UDFF. RESULTS: Twenty-two participants were male, 24 were female, and the mean age was 14 ± 3 (range: 7-18) years. Thirty-six out of 46 participants had normal liver fat fraction <6%, and 10/46 had liver steatosis. UDFF was positively associated with MR-PDFF (ICC 0.92 (95% CI, 0.89-0.96). The mean bias between UDFF and MR-PDFF was 0.64% (95% LOA, -5.3-6.6%). AUROC of UDFF for steatosis was of 0.95 (95% CI, 0.89-0.99). UDFF cutoff of 6% had a sensitivity of 90% (95% CI, 55-99%) and a specificity of 94% (95% CI, 81-0.99%). BMI was an independent predictor of UDFF (correlation: 0.55 (95% CI, 0.35-0.95)). CONCLUSIONS: UDFF shows strong agreement with MR-PDFF in children. A UDFF cutoff of 6% provides good sensitivity and specificity for detection of MR-PDFF of ≥ 6%.
