Dataset Information

Assessment of MRI-Based Automated Fetal Cerebral Cortical Folding Measures in Prediction of Gestational Age in the Third Trimester.

ABSTRACT: Traditional methods of dating a pregnancy based on history or sonographic assessment have a large variation in the third trimester. We aimed to assess the ability of various quantitative measures of brain cortical folding on MR imaging in determining fetal gestational age in the third trimester.We evaluated 8 different quantitative cortical folding measures to predict gestational age in 33 healthy fetuses by using T2-weighted fetal MR imaging. We compared the accuracy of the prediction of gestational age by these cortical folding measures with the accuracy of prediction by brain volume measurement and by a previously reported semiquantitative visual scale of brain maturity. Regression models were constructed, and measurement biases and variances were determined via a cross-validation procedure.The cortical folding measures are accurate in the estimation and prediction of gestational age (mean of the absolute error, 0.43 ± 0.45 weeks) and perform better than (P = .024) brain volume (mean of the absolute error, 0.72 ± 0.61 weeks) or sonography measures (SDs approximately 1.5 weeks, as reported in literature). Prediction accuracy is comparable with that of the semiquantitative visual assessment score (mean, 0.57 ± 0.41 weeks).Quantitative cortical folding measures such as global average curvedness can be an accurate and reliable estimator of gestational age and brain maturity for healthy fetuses in the third trimester and have the potential to be an indicator of brain-growth delays for at-risk fetuses and preterm neonates.

SUBMITTER: Wu J

PROVIDER: S-EPMC4940851 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Pregnancy-induced changes in plasma pharmacokinetics of many antiretrovirals (ARV) are well-established. Current knowledge about the extent of ARV exposure in lymphoid tissues of pregnant women and within the fetal compartment is limited due to their inaccessibility. Subtherapeutic ARV concentrations in HIV reservoirs like lymphoid tissues during pregnancy may constitute a barrier to adequate virological suppression and increase the risk of mother-to-child transmission (MTCT). The present study describes the pharmacokinetics of three ARVs (efavirenz, dolutegravir, and rilpivirine) in lymphoid tissues and fetal plasma during pregnancy using materno-fetal physiologically-based pharmacokinetic models (m-f-PBPK). Lymphatic and fetal compartments were integrated into our previously validated adult PBPK model. Physiological and drug disposition processes were described using ordinary differential equations. For each drug, virtual pregnant women (n = 50 per simulation) received the standard dose during the third trimester. Essential pharmacokinetic parameters, including Cmax, Cmin, and AUC (0-24), were computed from the concentration-time data at steady state for lymph and fetal plasma. Models were qualified by comparison of predictions with published clinical data, the acceptance threshold being an absolute average fold-error (AAFE) within 2.0. AAFE for all model predictions was within 1.08-1.99 for all three drugs. Maternal lymph concentration 24 h after dose exceeded the reported minimum effective concentration (MEC) for efavirenz (11,514 vs. 800 ng/ml) and rilpivirine (118.8 vs. 50 ng/ml), but was substantially lower for dolutegravir (16.96 vs. 300 ng/ml). In addition, predicted maternal lymph-to-plasma AUC ratios vary considerably (6.431-efavirenz, 0.016-dolutegravir, 1.717-rilpivirine). Furthermore, fetal plasma-to-maternal plasma AUC ratios were 0.59 for efavirenz, 0.78 for dolutegravir, and 0.57 for rilpivirine. Compared with rilpivirine (0 h), longer dose forgiveness was observed for dolutegravir in fetal plasma (42 h), and for efavirenz in maternal lymph (12 h). The predicted low lymphoid tissue penetration of dolutegravir appears to be significantly offset by its extended dose forgiveness and adequate fetal compartment exposure. Hence, it is unlikely to be a predictor of maternal virological failure or MTCT risks. Predictions from our m-f-PBPK models align with recommendations of no dose adjustment despite moderate changes in exposure during pregnancy for these drugs. This is an important new application of PBPK modeling to evaluate the adequacy of drug exposure in otherwise inaccessible compartments.

Dataset Information

Assessment of MRI-Based Automated Fetal Cerebral Cortical Folding Measures in Prediction of Gestational Age in the Third Trimester.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets