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

Официальное название

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

Обзор

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.

Подробное описание

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:

* Medium-to-high risk group (n = 96): Representing mothers with significant maternal frailty indices. * Low-risk group (n = 64): Reflecting minimal clinical and psychosocial risk burden.

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:

* Local connectivity: Connectivity between regions within the same system (e.g., sensorimotor, auditory). * Global connectivity: Connectivity between regions across different systems. * Segregation indices: Reflecting within-system connectivity. * Integration indices: Reflecting cross-system connectivity. Functional connectivity parameters will be estimated for each subject using region-based parcellations aligned with validated fetal and neonatal brain templates. Structural MRI will also be acquired to confirm normative brain development and rule out major anomalies.

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:

* Sensorimotor processing * Language development * Attention and executive function * Socioemotional regulation * Adaptive behavior The association between early brain connectivity and later neurodevelopmental performance will be analyzed using both correlational methods and predictive modeling frameworks.

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:

1. Descriptive statistics for maternal risk profiles and neurodevelopmental scores. 2. Group comparisons across maternal risk strata. 3. Correlation and regression analyses between functional connectivity metrics and neurodevelopmental outcomes. 4. Predictive modeling using machine learning to predict later developmental profiles.

All analyses will consider longitudinal dependencies, potential confounders (e.g., gestational age, birth outcomes), and interactions between maternal risk variables and imaging biomarkers.

Вмешательства

• Поведенческое 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.
• Диагностический тест 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.
• Поведенческое 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.
• Диагностический тест 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 ea
• Поведенческое 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

Первичные конечные точки

• Correlation Between Fetal and Neonatal Functional Connectivity Markers and Neurodevelopmental Scores [Срок оценки: 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.]
• Accuracy of AI-Based Predictive Models for Estimating Neurodevelopmental Outcomes. [Срок оценки: Model training and validation using imaging and behavioral data collected between prenatal period and 72 months postnatal.]

Вторичные конечные точки (3)

• Classification and Description of Maternal Clinical and Lifestyle Risk Profiles Using the MaFra Inventory [Срок оценки: through 24-35 weeks gestational weeks]
• Effect of Maternal Emotional State on Fetal Brain Connectivity [Срок оценки: At time of fetal rs-fMRI (typically 24-35 gestational weeks).]
• Functional Connectivity Integration and Segregation Indices Across Brain Systems [Срок оценки: Acquired at fetal rs-fMRI (typically 24-35 gestational weeks) and neonatal rs-fMRI (within first 14 days of life).]

Критерии участия

Критерии включения

• Pregnant women (biologically female) receiving care at the Gynecology and Obstetrics Unit, San Raffaele Hospital, Milan.
• Age ≥ 18 years at time of enrollment.
• Singleton pregnancy.
• Gestational age within the range suitable for fetal MRI acquisition (typically 24-35 weeks gestation).
• Willing and able to provide written informed consent.
• Willing to undergo fetal and/or neonatal resting-state fMRI as part of the observational study protocol.
• Willing to complete maternal questionnaires assessing clinical, lifestyle, and emotional factors (e.g., MaFra Inventory, anxiety scales).
• Willing to participate in postnatal follow-up assessments of the child, including neurodevelopmental evaluations from birth to 72 months.
• Fetuses with normal brain morphology confirmed by structural MRI.
• Fetuses and neonates without signal alterations on structural MRI.

Критерии исключения

• Twin or multiple gestation pregnancies.
• Fetal diagnosis of any major structural or genetic anomaly known to impact neurodevelopment.
• Evidence of fetal brain parenchymal signal alterations or neurodevelopmental abnormalities as assessed by structural MRI and confirmed by an experienced neuroradiologist.
• Maternal contraindications to undergoing MRI (e.g., presence of non-MRI-compatible implants or severe claustrophobia).

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Италия · 1 центр

• Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele — Milan

Публикации

• Pecco N, Della Rosa PA, Canini M, Nocera G, Scifo P, Cavoretto PI, Candiani M, Falini A, Castellano A, Baldoli C. Optimizing Performance of Transformer-based Models for Fetal Brain MR Image Segmentation. Radiol Artif Intell. 2024 Nov;6(6):e230229. doi: 10.1148/ryai.230229. PMID 38922031
• Canini M, Pecco N, Caglioni M, Katusic A, Isasegi IZ, Oprandi C, Scifo P, Pozzoni M, Lorioli L, Garbetta G, Poloniato A, Sora MGN, Cavoretto PI, Barera G, Candiani M, Kostovic I, Falini A, Baldoli C, Della Rosa PA. Maternal anxiety-driven modulation of fetal limbic connectivity designs a backbone linking neonatal brain functional topology to socio-emotional development in early childhood. J Neuros PMID 37313950
• Canini, M., Cara, C., Oprandi, C., Katušić, A., Žunić Išasegi, I., Messina, A., Zambon, A. A., Pecco, N., Barni, S., Poloniato, A., Natali Sora, M. G., Falautano, M., Scifo, P., Barera, G., Tettamanti, M., Falini, A., Baldoli, C., & Della Rosa, P. A. (2025). Functional connectivity markers of prematurity at birth predict neurodevelopmental outcomes at 6, 12, 24, and 36 months. International Journa
• Miglioli C, Canini M, Vignotto E, Pecco N, Pozzoni M, Victoria-Feser MP, Guerrier S, Candiani M, Falini A, Baldoli C, Cavoretto PI, Della Rosa PA. The maternal-fetal neurodevelopmental groundings of preterm birth risk. Heliyon. 2024 Mar 27;10(7):e28825. doi: 10.1016/j.heliyon.2024.e28825. eCollection 2024 Apr 15. PMID 38596101
• Pecco N, Canini M, Mosser KHH, Caglioni M, Scifo P, Castellano A, Cavoretto P, Candiani M, Baldoli C, Falini A, Rosa PAD. RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data. Neuroinformatics. 2022 Oct;20(4):1137-1154. doi: 10.1007/s12021-022-09592-5. Epub 2022 Jul 14. PMID 35834105
• Della Rosa PA, Miglioli C, Caglioni M, Tiberio F, Mosser KHH, Vignotto E, Canini M, Baldoli C, Falini A, Candiani M, Cavoretto P. A hierarchical procedure to select intrauterine and extrauterine factors for methodological validation of preterm birth risk estimation. BMC Pregnancy Childbirth. 2021 Apr 16;21(1):306. doi: 10.1186/s12884-021-03654-3. PMID 33863296
• Della Rosa PA, Canini M, Marchetta E, Cirillo S, Pontesilli S, Scotti R, Natali Sora MG, Poloniato A, Barera G, Falini A, Scifo P, Baldoli C. The effects of the functional interplay between the Default Mode and Executive Control Resting State Networks on cognitive outcome in preterm born infants at 6 months of age. Brain Cogn. 2021 Feb;147:105669. doi: 10.1016/j.bandc.2020.105669. Epub 2020 Dec 17 PMID 33341657
• Canini M, Cavoretto P, Scifo P, Pozzoni M, Petrini A, Iadanza A, Pontesilli S, Scotti R, Candiani M, Falini A, Baldoli C, Della Rosa PA. Subcortico-Cortical Functional Connectivity in the Fetal Brain: A Cognitive Development Blueprint. Cereb Cortex Commun. 2020 Apr 3;1(1):tgaa008. doi: 10.1093/texcom/tgaa008. eCollection 2020. PMID 34296089

Идентификаторы

NCT: NCT07059286 · CET 28-2024

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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