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Published on: November 20, 2015
The maternal-fetal neurodevelopmental groundings of preterm birth risk
Cesare Miglioli1, Matteo Canini2, Edoardo Vignotto1
1Research Center for Statistics, University of Geneva, Boulevard Du Pont-d'Arve 40, 1205 Geneva, Switzerland.
Insights
Fetal brain connectivity differences predict preterm birth risk. Integrating brain data with maternal factors improves prediction, offering insights into neurodevelopmental risks before birth.
Area of Science:
- Neuroimaging
- Developmental Neuroscience
- Maternal-Fetal Medicine
Background:
- Altered neurodevelopment is a significant complication of preterm birth (PTB), with in-utero factors largely unexplored.
- Investigating fetal brain functional connectivity offers a novel window into understanding PTB's impact on neurodevelopment.
Purpose of the Study:
- To examine the relationship between fetal brain functional connectivity and the risk of preterm birth.
- To assess if incorporating fetal brain data improves prediction models for PTB risk.
Main Methods:
- Used resting-state functional magnetic resonance imaging (rs-fMRI) in 31 pregnancies stratified by PTB risk (low vs. high).
- Applied Greedy Equivalence Search (GES) for connectivity analysis and Monte Carlo permutation tests for group comparisons.
- Developed and compared random forest models with and without fetal brain connectivity data for PTB risk prediction.
Main Results:
- High-risk PTB pregnancies exhibited reduced fetal brain functional connections compared to low-risk pregnancies.
- The model incorporating fetal brain connectivity (MaFra-Neuro) demonstrated improved PTB risk prediction accuracy.
- MaFra-Neuro class probabilities correlated significantly with gestational age at birth, PTB risk gradients, and perinatal clinical conditions.
Conclusions:
- Fetal brain functional connectivity is a promising, unexplored predictor of PTB.
- This connectivity is associated with maternal risk profiles and predicts neurodevelopmental risks evident at birth.
- Findings suggest fetal brain connectivity can bridge different PTB phenotypes and their long-term consequences.
Background:
Altered neurodevelopment is a major clinical sequela of Preterm Birth (PTB) being currently unexplored in-utero.
Aims:
To study the link between fetal brain functional (FbF) connectivity and preterm birth, using resting-state functional magnetic resonance imaging (rs-fMRI).
Study Design:
Prospective single-centre cohort study.
Subjects:
A sample of 31 singleton pregnancies at 28-34 weeks assigned to a low PTB risk (LR) (n = 19) or high PTB risk (HR) (n = 12) group based on a) the Maternal Frailty Inventory (MaFra) for PTB risk; b) a case-specific PTB risk gradient.
Methods:
Fetal brain rs-fMRI was performed on 1.5T MRI scanner. First, directed causal relations representing fetal brain functional connectivity measurements were estimated using the Greedy Equivalence Search (GES) algorithm. HR vs. LR group differences were then tested with a novel ad-hoc developed Monte Carlo permutation test. Second, a MaFra-only random forest (RF) was compared against a MaFra-Neuro RF, trained by including also the most important fetal brain functional connections. Third, correlation and regression analyses were performed between MaFra-Neuro class probabilities and i) the GA at birth; ii) PTB risk gradient, iii) perinatal clinical conditions and iv) PTB below 37 weeks.
Results:
First, fewer fetal brain functional connections were evident in the HR group. Second, the MaFra-Neuro RF improved PTB risk prediction. Third, MaFra-Neuro class probabilities showed a significant association with: i) GA at birth; ii) PTB risk gradient, iii) perinatal clinical conditions and iv) PTB below 37 weeks.
Conclusion:
Fetal brain functional connectivity is a novel promising predictor of PTB, linked to maternal risk profiles, ahead of birth, and clinical markers of neurodevelopmental risk, at birth, thus potentially "connecting" different PTB phenotypes.
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