PregnancyMaMRI-NeUCogINCT07059286
Maternal Risk, Fetal-Neonatal Brain Connectivity, and Early Neurodevelopment: A Longitudinal Observational Study
An observational study of Pregnancy and Neurodevelopment, run by IRCCS San Raffaele at 1 site in Italy.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Pregnancy, Neurodevelopment, Brain Connectivity
- What is being tested?
- Maternal Frailty Inventory (MaFra) Questionnaire, Fetal Resting-State Functional MRI and Maternal Emotional Reactivity
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 160 participants
- Where
- 1 siteItaly
- Study dates
- Jul 2025to Jan 2033
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- 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.
Show all 10Show fewer
- 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.
Who cannot join
- 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).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Italy1 site
Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele
Milan, MI, 20132
About this study
Official title: 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
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.
Read more
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.
Read the detailed description
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:
- Descriptive statistics for maternal risk profiles and neurodevelopmental scores.
- Group comparisons across maternal risk strata.
- Correlation and regression analyses between functional connectivity metrics and neurodevelopmental outcomes.
- 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.
- Being tested
- Maternal Frailty Inventory (MaFra) Questionnaire, Fetal Resting-State Functional MRI, Maternal Emotional Reactivity, Neonatal Resting-State Functional MRI, Longitudinal Neurodevelopmental Testing Battery
- 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
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Maternal Frailty Inventory (MaFra) QuestionnaireBehavioural
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 MRIDiagnostic 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.
Maternal Emotional ReactivityBehavioural
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 MRIDiagnostic 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.
Longitudinal Neurodevelopmental Testing BatteryBehavioural
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 group | Role | What they receive |
|---|---|---|
| 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). Receives: 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). Receives: 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 |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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
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.
Measured: through 24-35 weeks gestational weeks
Effect of Maternal Emotional State on Fetal Brain Connectivity
This outcome examines how maternal emotional valence and arousal ratings-measured immediately before and after listening to musical stimuli-modulate fetal brain connectivity.
Measured: At time of fetal rs-fMRI (typically 24-35 gestational weeks).
Functional Connectivity Integration and Segregation Indices Across Brain Systems
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.
Measured: Acquired at fetal rs-fMRI (typically 24-35 gestational weeks) and neonatal rs-fMRI (within first 14 days of life).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Jul 2025
- Study startJul 2025 (estimated)
- Primary completionNov 2031 (estimated)
- Study completionJan 2033 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (8)Papers the sponsor has linked to this study.
- Other trials for PregnancyStudies of the same condition, open and under way.
- More trials run by IRCCS San RaffaeleThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 160 participants (estimated)
Sponsor and investigators
- Lead sponsor
- IRCCS San Raffaele
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Pasquale Anthony Della Rosa, IRCCS San Raffaele
- Investigators
- Andrea Falini, Doctor of Medicine, Study director, 1. Vita-Salute San Raffaele University, Milan, Italy; 2. Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, ItalyPasquale Anthony Della Rosa, PhD - Psychology, Principal investigator, Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07059286
- Sponsor's protocol ID
- CET 28-2024
- Acronym
- MaMRI-NeUCogI
- Status last verified
- Jul 2025
- First submitted
- 27 Jun 2025
- Last updated
- 10 Jul 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 38922031Canini 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.
PubMed 37313950Canini, 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
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.
PubMed 38596101Pecco 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.
PubMed 35834105Della 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.
PubMed 33863296Della 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.
PubMed 33341657Canini 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.
PubMed 34296089
Study at a glance
From the registry record, last updated by the sponsor on 10 Jul 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- 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
- ClinicalTrials.gov ID
- NCT07059286
- Acronym / sponsor ID
- MaMRI-NeUCogI / CET 28-2024
- Keywords
- Maternal Risk Factors, Fetal Brain, Neonatal Brain, Resting-State Functional MRI, Functional Connectivity, Brain Development, Cognitive Development, Behavioral Development
- Study type
- Observational
- Recruitment status
- Enrolling by invitation
- Enrolment
- 160 participants (estimated)
- Lead sponsor
- IRCCS San RaffaeleUniversity, hospital or other
- Study start
- Jul 2025 (estimated)
- Primary completion
- Nov 2031 (estimated)
- Study completion
- Jan 2033 (estimated)
- First posted
- 10 Jul 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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:
- Descriptive statistics for maternal risk profiles and neurodevelopmental scores.
- Group comparisons across maternal risk strata.
- Correlation and regression analyses between functional connectivity metrics and neurodevelopmental outcomes.
- 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Medium-High Risk | – | Behavioral: Maternal Frailty Inventory (MaFra) Questionnaire, Diagnostic Test: Fetal Resting-State Functional MRI, Diagnostic Test: Neonatal Resting-State Functional MRI, Behavioral: Longitudinal Neurodevelopmental Testing BatteryPregnant 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). |
| Low Risk | – | 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 BatteryPregnant women with a low risk profile based on the based on the Maternal Frailty Inventory (MaFra) developed by Della Rosa et al. (2021). |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (10 listed)
- 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.
Key exclusion criteria (4 listed)
- 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).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Maternal Frailty Inventory (MaFra) QuestionnaireA 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. | Behavioural | Low Risk, Medium-High Risk |
| Fetal Resting-State Functional MRINon-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. | Diagnostic test | Low Risk, Medium-High Risk |
| Maternal Emotional ReactivityDuring 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. | Behavioural | Low Risk |
| Neonatal Resting-State Functional MRINon-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. | Diagnostic test | Low Risk, Medium-High Risk |
| Longitudinal Neurodevelopmental Testing BatteryStandardized 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. | Behavioural | Low Risk, Medium-High Risk |
Primary outcome
Correlation Between Fetal and Neonatal Functional Connectivity Markers and Neurodevelopmental Scores
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.
Accuracy of AI-Based Predictive Models for Estimating Neurodevelopmental Outcomes.
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.
3 secondary outcomes
Classification and Description of Maternal Clinical and Lifestyle Risk Profiles Using the MaFra Inventory
Time frame: through 24-35 weeks gestational weeks
Effect of Maternal Emotional State on Fetal Brain Connectivity
Time frame: At time of fetal rs-fMRI (typically 24-35 gestational weeks).
Functional Connectivity Integration and Segregation Indices Across Brain Systems
Time frame: Acquired at fetal rs-fMRI (typically 24-35 gestational weeks) and neonatal rs-fMRI (within first 14 days of life).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jul 2025.
- Background: PubMed 38922031Pecco 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.
- Background: PubMed 37313950Canini 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.
- BackgroundCanini, 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: PubMed 38596101Miglioli 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.
- Background: PubMed 35834105Pecco 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.
- Background: PubMed 33863296Della 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.
- Background: PubMed 33341657Della 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.
- Background: PubMed 34296089Canini 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.
- RS-FetfMRI for processing Fetal resting-state functional MRI scansLink provided by the sponsor.
- Swin-Fetal-Brain-SegmentationLink provided by the sponsor.
- Deep Learning (DL) RF-2016-02364081 dataset for the study titled: 'Optimizing performance of transformer-based models for fetal brain MR image segmentation'.Link provided by the sponsor.
- Final Dataset for Neural Network Models included in Project RF-2016-02364081 Final Report. Short Title: "A generalized prediction framework of preterm birth"Link provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Andrea Falini, Doctor of Medicine study director
1. Vita-Salute San Raffaele University, Milan, Italy; 2. Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
Pasquale Anthony Della Rosa, PhD - Psychology principal investigator
Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pregnancy and Neurodevelopment, run by IRCCS San Raffaele at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 10 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 10 Jul 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correlation Between Fetal and Neonatal Functional Connectivity Markers and Neurodevelopmental Scores (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.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07059286, which also lists 8 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Jul 2025.