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

NCT07059286 | Enrolling By Invitation DMC

• 1 other identifier: CET 28-2024
• Study Type: observational
• Target: 160
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Pregnancy; Neurodevelopment; Brain Connectivity; Neurodevelopment Outcome

Keywords

Maternal Risk Factors; Fetal Brain; Neonatal Brain; Resting-State Functional MRI; Functional Connectivity; Brain Development; Cognitive Development; Behavioral Development; Early Childhood Development; Artificial Intelligence; Longitudinal Studies

Outcome Measures

Primary Outcomes (2)

• Correlation Between Fetal and Neonatal Functional Connectivity Markers and Neurodevelopmental Scores

  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.

  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.

  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.

  Model training and validation using imaging and behavioral data collected between prenatal period and 72 months postnatal.

Secondary Outcomes (3)

• Classification and Description of Maternal Clinical and Lifestyle Risk Profiles Using the MaFra Inventory

  through 24-35 weeks gestational weeks

• Effect of Maternal Emotional State on Fetal Brain Connectivity

  At time of fetal rs-fMRI (typically 24-35 gestational weeks).

• Functional Connectivity Integration and Segregation Indices Across Brain Systems

  Acquired at fetal rs-fMRI (typically 24-35 gestational weeks) and neonatal rs-fMRI (within first 14 days of life).

Other Outcomes (1)

• System-Specific Neurodevelopmental Performance Scores

  Developmental assessments at 0, 3, 6, 12, 24, 36, 48, 60, and 72 months of age.

Study Arms (2)

Medium-High Risk

Pregnant women with a medium-to-high risk profile based on the based on the Maternal Frailty Inventory (MaFra) developed by Della Rosa et al. (2021).

Behavioral: Maternal Frailty Inventory (MaFra) Questionnaire; Diagnostic Test: Fetal Resting-State Functional MRI; Diagnostic Test: Neonatal Resting-State Functional MRI; Behavioral: Longitudinal Neurodevelopmental Testing Battery

Low Risk

Pregnant women with a low risk profile based on the based on the Maternal Frailty Inventory (MaFra) developed by Della Rosa et al. (2021).

Behavioral: Maternal Frailty Inventory (MaFra) Questionnaire; Diagnostic Test: Fetal Resting-State Functional MRI; Behavioral: Maternal Emotional Reactivity; Diagnostic Test: Neonatal Resting-State Functional MRI; Behavioral: Longitudinal Neurodevelopmental Testing Battery

Interventions

Maternal Frailty Inventory (MaFra) Questionnaire BEHAVIORAL

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.

Low Risk; Medium-High Risk

Fetal Resting-State Functional MRI DIAGNOSTIC_TEST

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.

Low Risk; Medium-High Risk

Maternal Emotional Reactivity BEHAVIORAL

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.

Low Risk

Neonatal Resting-State Functional MRI DIAGNOSTIC_TEST

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.

Low Risk; Medium-High Risk

Longitudinal Neurodevelopmental Testing Battery BEHAVIORAL

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.

Low Risk; Medium-High Risk

Eligibility Criteria

• Age: 18 Years+
• Gender Eligibility Details: This study includes only individuals who are biologically female and currently pregnant, as the research is focused on the association between maternal health factors during pregnancy, fetal and neonatal brain development, and long-term child neurodevelopmental outcomes. Eligibility is restricted to pregnant women receiving care at the Gynecology and Obstetrics Unit of San Raffaele Hospital, Milan. Male participants and non-pregnant females are not eligible for enrollment.
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population will consist of 160 pregnant women receiving prenatal care at the Gynecology and Obstetrics Unit of San Raffaele Hospital in Milan, Italy. Participants are recruited during the third trimester of pregnancy and stratified into low- or medium/high-risk groups based on the Maternal Frailty Inventory (MaFra), which integrates clinical, psychological, and lifestyle-related risk factors. The fetuses and subsequently the neonates of these women are included in the study for longitudinal neuroimaging and developmental follow-up until 72 months of age.

You may qualify if:

• 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.

You may not qualify if:

• 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).

Sponsors & Collaborators

• IRCCS San Raffaele: lead

Study Sites (1)

Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele

Milan, MI, 20132, Italy

Location

Related Publications (8)

• 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 BACKGROUND

• 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 Neurosci Res. 2023 Sep;101(9):1484-1503. doi: 10.1002/jnr.25207. Epub 2023 Jun 14.

  PMID: 37313950 BACKGROUND

• 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 Journal of Behavioral Development, 0(0). https://doi.org/10.1177/01650254241312136

  BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

Related Links

• RS-FetfMRI for processing Fetal resting-state functional MRI scans
• Swin-Fetal-Brain-Segmentation
• Deep Learning (DL) RF-2016-02364081 dataset for the study titled: 'Optimizing performance of transformer-based models for fetal brain MR image segmentation'.
• Final Dataset for Neural Network Models included in Project RF-2016-02364081 Final Report. Short Title: "A generalized prediction framework of preterm birth"

MeSH Terms

Interventions

Surveys and Questionnaires

Intervention Hierarchy (Ancestors)

Data Collection; Epidemiologic Methods; Investigative Techniques; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Study Officials

• Andrea Falini, Doctor of Medicine

  1. Vita-Salute San Raffaele University, Milan, Italy; 2. Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy

  STUDY DIRECTOR

• Pasquale Anthony Della Rosa, PhD - Psychology

  Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: June 27, 2025
• First Posted: July 10, 2025
• Study Start: July 1, 2025
• Primary Completion (Estimated): November 1, 2031
• Study Completion (Estimated): January 1, 2033
• Last Updated: July 10, 2025

Record last verified: 2025-07

Data Sharing

• IPD Sharing: Will not share

Locations

IT (1)