Maternal Risk, Fetal-Neonatal Brain Connectivity, and Early Neurodevelopment: A Longitudinal Observational Study

Condition(s) studied

Investigational drug(s) / intervention(s)

Maternal Frailty Inventory (MaFra) Questionnaire: A validated psychometric inventory designed to assess maternal clinical, psychological, and lifestyle risk factors during pregnancy. The composite risk score is used to stratify participants into low- or medium/high-risk categories. Administered during pregnancy, the inventory informs classification and predictive modeling of fetal and child neurodevelopmental outcomes.

Fetal Resting-State Functional MRI: Non-invasive resting-state functional MRI scans performed during gestation (fetal) life to assess functional connectivity across sensorimotor, auditory, visual, language, and attention networks. Imaging data are analyzed to derive local and global connectivity measures and indices of segregation and integration among functional brain systems. Structural MRI is used to confirm normal brain morphology.

Maternal Emotional Reactivity: During fetal rs-fMRI acquisition, mothers listen to emotionally evocative musical excerpts while rating their emotional responses. These self-reported ratings (valence and arousal) are later correlated with fetal brain connectivity responses.

Neonatal Resting-State Functional MRI: Non-invasive MRI scanning protocol conducted during the neonatal period to acquire resting-state functional MRI (rs-fMRI) data. The scan is performed while the newborn is in a natural sleep state, using motion-optimized sequences to assess functional connectivity between brain regions. The focus is on sensorimotor, auditory, visual, language, and attention networks. Structural MRI is also acquired to verify normative brain morphology. Imaging outcomes are used in longitudinal analyses to link early brain connectivity with cognitive and behavioral development.

Longitudinal Neurodevelopmental Testing Battery: Standardized neuropsychological and behavioral assessments are administered at multiple timepoints between birth and 72 months of age. Domains evaluated include sensorimotor skills, cognitive abilities, language development, executive function, social-emotional regulation, and adaptive behaviors. Data are used to compute specific and composite scores that reflect neurocognitive and behavioral profiles. These are later integrated with prenatal and neonatal brain imaging and maternal risk data to model individual neurodevelopmental trajectories.

Study summary

This study aims to understand how a pregnant woman's health, lifestyle, and psychological state-especially when associated with known risk factors-might influence the developing brain of her baby, both before and after birth. Specifically, the research investigates whether differences in brain connectivity observed through fetal and neonatal magnetic resonance imaging (MRI) can predict how a child will develop cognitively, emotionally, and behaviorally from birth through early childhood.

This is a prospective, observational study that will follow 160 pregnant women and their children over time. Participants will be enrolled at the Gynecology and Obstetrics Unit of San Raffaele Hospital in Milan. Using advanced brain imaging techniques (resting-state functional MRI), the study will examine how key brain systems-such as those involved in movement, hearing, vision, language, and attention-are connected during fetal life and shortly after birth. The study also evaluates how these patterns of brain connectivity relate to later developmental outcomes, assessed through standard neuropsychological tests from birth up to 6 years of age.

One of the study's core hypotheses is that early patterns of brain connectivity-especially when combined with detailed profiles of maternal health and risk-can serve as early markers of a child's neurodevelopmental path. To explore this, the study uses an integrated approach that combines imaging data with clinical and psychological information from the mother (e.g., her stress levels, medical history, and lifestyle habits).

Participants are grouped based on the "Maternal Frailty Inventory," a tool that captures the cumulative risk profile of each mother. The sample will include mothers with both low and medium-high risk scores. This grouping allows researchers to investigate how varying degrees of maternal risk are reflected in the baby's early brain organization and how this, in turn, influences developmental milestones.

A secondary aim of the study is to investigate how emotional responses to music may affect fetal brain activity. During the fetal MRI, mothers will listen to selected musical pieces. Researchers will examine if the baby's brain is influenced by the mother's emotional state.

Ultimately, the study hopes to build predictive models-using artificial intelligence and advanced statistical techniques-that can estimate a child's developmental trajectory based on early brain imaging and maternal data. This could provide an important step toward early identification of children who might benefit from developmental support or intervention, even before symptoms appear.

Eligibility

Primary outcome measure(s)

• Correlation Between Fetal and Neonatal Functional Connectivity Markers and Neurodevelopmental Scores — At fetal and neonatal rs-fMRI acquisition (prenatal and perinatal period); developmental assessments at 0. 3, 6, 12, 24, 36, 48, 60, and 72 months of age.
  This primary outcome assesses the association between functional connectivity indices obtained from resting-state functional MRI (rs-fMRI) scans in fetuses and neonates and neurodevelopmental outcomes. Functional connectivity is quantified using network-level measures of segregation (within-system connectivity) and integration (cross-system connectivity) across sensorimotor, visual, auditory, language, and attention systems. Neurodevelopmental outcomes are measured using standardized neurocognitive and neurobehavioral batteries that evaluate multiple domains including cognitive, language, sensorimotor, emotional, and adaptive functioning. The correlations are computed to quantify the strength of associations between early brain connectivity and later behavioral and cognitive performance.
• Accuracy of AI-Based Predictive Models for Estimating Neurodevelopmental Outcomes. — Model training and validation using imaging and behavioral data collected between prenatal period and 72 months postnatal.
  Predictive performance of machine learning models trained on fetal/neonatal rs-fMRI-derived connectivity features and maternal risk profiles to estimate long-term neurodevelopmental outcomes.

Trial sites (1)

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