Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele
Milan, MI, 20132, Italy
NCT Number: NCT07059286
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.
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Request Info18 year and older
Female
Observational
Milan, MI, 20132, Italy
This single-center, prospective longitudinal observational cohort study-entitled Maternal Risk, Fetal-Neonatal Brain Connectivity, and Early Neurodevelopment (MaMRI-NeUCogI)-is designed to explore the relationship between maternal risk profiles, early-life brain connectivity, and developmental outcomes from birth to early childhood (up to 72 months). The protocol aims to trace the temporal continuity between functional neurodevelopmental markers present in utero or shortly after birth and subsequent cognitive, behavioral, and emotional trajectories during early childhood.
Scientific Rationale A key challenge in developmental neuroscience is identifying early biomarkers that can predict individual differences in neurodevelopmental trajectories. The fetal and neonatal periods represent critical windows during which the brain undergoes major organizational changes. Disruptions or variations in these processes-particularly in the presence of maternal medical, psychological, or environmental risks-may lead to atypical connectivity patterns that forecast later neurodevelopmental difficulties.
This study leverages resting-state functional MRI (rs-fMRI) in fetuses and neonates to map the functional architecture of core neural systems (sensorimotor, auditory, visual, language, and attention). The project builds upon prior work from the Italian Ministry of Health's "Ricerca Finalizzata 2016" (grant number RF-2016-02364081; Principal Investigator: Dr. Pasquale Anthony Della Rosa), expanding its focus to include a multivariate risk framework and an artificial intelligence-based predictive modeling approach.
Study Population and Grouping
A total of 160 pregnant women will be enrolled from the Gynecology and Obstetrics Unit at San Raffaele Hospital, Milan. They will be stratified into two groups based on the Maternal Frailty Inventory (MaFra) developed by Della Rosa et al. (2021), which integrates clinical (e.g., obstetric, gynecological) and non-clinical (e.g., psychological, lifestyle) risk factors:
This stratification is established a posteriori based on a risk profile classification aligned with research goals, and is not connected to clinical diagnoses or intervention decisions.
Imaging Protocol and Data Collection
All participants will undergo fetal and/or neonatal rs-fMRI, depending on clinical indications and risk group membership. Imaging data will be used to derive metrics of functional connectivity, specifically:
Longitudinal Neurodevelopmental Follow-up
Children born to participating mothers will undergo standardized neuropsychological assessment at several developmental milestones from birth to 72 months. These assessments will yield dimensional scores across various cognitive, behavioral, and emotional domains, including:
Artificial Intelligence and Prediction Modeling A core innovation of the MaMRI-NeUCogI study lies in the use of ML models trained on imaging-derived connectivity features and maternal risk indices. The goal is to predict multidimensional developmental trajectories. The resulting predictive framework is intended to quantify deviation from typical developmental trajectories and may serve in the future to inform early intervention strategies.
Secondary Aims: Maternal Emotional State influence on fetal brain connectivity A secondary component of the study investigates the impact of emotional responses to music on fetal brain connectivity. During fetal rs-fMRI, participating mothers will listen to emotionally evocative music. The study will examine how maternal emotional valence and arousal ratings relate to fetal connectivity patterns.
Data Integration and Analytic Plan
The study adopts a multi-tiered analytic approach:
All analyses will consider longitudinal dependencies, potential confounders (e.g., gestational age, birth outcomes), and interactions between maternal risk variables and imaging biomarkers.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
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.
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.
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.
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.
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.
Time frame: 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.
Time frame: 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.
Time frame: through 24-35 weeks gestational weeks
Maternal risk profiles are derived using the MaFra Inventory, a psychometric tool that aggregates clinical, psychological, and lifestyle factors. The outcome quantifies maternal frailty as a continuous score between 0 (no risk) and 1 (maximum risk), allowing classification into low vs. medium-high risk groups. These profiles are used in further analyses to assess predictive associations with fetal brain connectivity and child development trajectories.
Time frame: At time of fetal rs-fMRI (typically 24-35 gestational weeks).
This outcome examines how maternal emotional valence and arousal ratings-measured immediately before and after listening to musical stimuli-modulate fetal brain connectivity.
Time frame: Acquired at fetal rs-fMRI (typically 24-35 gestational weeks) and neonatal rs-fMRI (within first 14 days of life).
Quantitative rs-fMRI measures of within-network segregation and between-network integration across fetal and neonatal scans. Used as continuous predictors in association and prediction models of developmental outcomes.
Time frame: Developmental assessments at 0, 3, 6, 12, 24, 36, 48, 60, and 72 months of age.
Standardized composite and domain-specific scores (sensorimotor, auditory, language, visual, attention) derived from longitudinal neuropsychological assessments administered at multiple developmental timepoints. Used to characterize the temporal progression and integration of neurocognitive functions.
IRCCS San Raffaele
Other
The Combination of Maternal Risk Factors and Functional/Structural Connectivity in Fetuses and Neonates to Predict Neurodevelopment From Birth Through Early Childhood: A Single-Center Observational Cohort Study
Acronym: MaMRI-NeUCogI
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