Childhood Outcomes of Preterm Brain Abnormalities

Predicting the Early Childhood Outcomes of Preterm Brain Shape Abnormalities

Prematurely born children are at higher risk of cognitive impairments and behavioral disorders than full-term children. There is growing evidence of significant volumetric and shape abnormalities in subcortical structures of premature neonates, which may be associated to negative long-term neurodevelopmental outcomes. The general objective is to look directly at the long-term neurodevelopmental implications of these neonatal subcortical structures abnormalities. Investigators propose to develop biomarkers of prematurity by comparing the morphological and diffusion properties of subcortical structures between preterm, with and without associated brain injuries, and full-term neonates using brain MRI. By combining subcortical morphological and diffusion properties, investigators hypothesize to be able to: (1) delineate specific correlative relationships between structures regionally and differentially affected by normal maturation and different patterns of white matter injury, and (2) improve the specificity of neuroimaging to predict neurodevelopmental outcomes earlier. The specific aims and general methodology are: 1) Build a new toolbox for neonatal subcortical structures analyses that combine a group lasso-based analysis of significant regions of shape changes, a structural correlation network analysis, a neonatal tractography, and tensor-based analysis on tracts; 2) Ascertain biomarkers of prematurity in neonates with different patterns of abnormalities using correlational and connectivity analysis within and between structures features; 3) Assess the predictive potential of subcortical imaging on neurodevelopmental outcomes by correlating neonatal imaging results with long-term neurodevelopmental scores at 9 and 18 months, and 6-8 years, follow-up. In each of these aims, investigators will use advanced neuroimaging analysis developed by their group and collaborator, including multivariate tensor-based morphometry and multivariate tract-based analysis. This application will provide the first complete subcortical network analysis in both term and preterm neonates. In the first study of its kind for prematurity, investigators will use sparse and multi-task learning to determine which of the biomarkers of prematurity at birth are the best predictors of long-term outcome. Once implemented, these methods will be available to compare subcortical structures for other pathologies in newborns and children.

Study Overview

• Status: Recruiting
• Conditions: Premature Birth; Neurodevelopmental Disorders; Brain Lesion; Brain Development Abnormality
• Intervention / Treatment: Diagnostic test: MRI; Diagnostic test: Neurodevelopmental/Neuropsychological Assessment

Detailed Description

The last months of pregnancy are particularly important for the development of the child's brain, and the consequences of premature birth on its development can be substantial. Prematurely born children are at higher risk of various cognitive impairments and exhibits more behavioral disorders than full-term born children. Thus early detection and management of at risk children are essential. There is growing evidence of significant volumetric abnormalities in subcortical structures of premature neonates, which may be associated to negative long-term neurodevelopmental outcomes. Understanding these abnormalities could help elucidate the underlying pathophysiology and enable early determination of at-risk patients, both of which would inform the design of novel treatment strategies. However, to date there is still a lack of sensitive, reliable, and accessible algorithms capable of characterizing the influence of prematurity on the anatomy of neonatal brain subcortical structures. In addition, few studies have looked directly at the long-term neurodevelopmental implications of these neonatal subcortical structures abnormalities. Predicting long-term neurodevelopmental outcomes early on - and preferably at neonatal ages - is likely to have a transformative effect on their outcome. Our preliminary data indicate significant morphological differences in the putamen, ventricles, corpus callosum, and thalamus between preterm and term neonates. Investigators propose to develop biomarkers of prematurity by statistically comparing the morphological and diffusion properties of subcortical structures between preterm and term neonates using brain MRI. These results will further be used in a sparse learning framework to predict long-term neurodevelopmental outcomes of prematurity. Hypotheses: By combining subcortical morphological and diffusion properties, we will be able to: (1) delineate specific correlative relationships between structures regionally and differentially affected by normal maturation and different patterns of white matter injury, and (2) improve the specificity of neuroimaging to predict neurodevelopmental outcomes earlier. Aim 1: Build a new toolbox for neonatal subcortical structures analyses that combine 1) a group lasso-based analysis of significant regions of shape changes, 2) a structural correlation network analysis, 3) a neonatal tractography, and 4) tensor-based analysis on tracts. Aim 2: Ascertain biomarkers of prematurity in neonates with different patterns of abnormalities. Aim 3: Assess the predictive potential of imaging and clinical features on neurodevelopmental outcomes among premature children at 9 and 18 months and 6-8 years of age. Impact: This application will provide the first complete subcortical network analysis in both term and preterm neonates. In the first study of its kind for prematurity, investigators will use sparse and multi-task learning to determine which of the biomarkers of prematurity at birth are the best predictors of long-term outcome. The expected findings could improve the ability to predict these outcomes and enable the design of early treatments - before years of pathological brain development and symptoms occur.

• Study Type: Observational
• Enrollment (Estimated): 80

Contacts and Locations

• Study Contact: Name: Natasha Lepore, Phd; Phone Number: (323) 361-5088; Email: nlepore@chla.usc.edu
• Study Contact Backup: Name: Natacha Paquette, Phd; Phone Number: (323) 361-8726; Email: npaquette@chla.usc.edu

Study Locations

• United States
  • California
    • Los Angeles, California, United States, 90027
      • Recruiting
      • Children's Hospital Los Angeles
      • Contact: Kayla Guzman, BS; Phone Number: 323-361-6876; Email: kayguzman@chla.usc.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: No older than 8 years (Child)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Our MRI data will consist of two separate neonatal cohorts. Cohort 1 is an existing dataset of neonates scanned in Pittsburgh as part of a separate completed grant. This cohort was scanned at neonatal equivalent age and will be brought back for childhood neurodevelopmental outcomes at 6-8 years of age. Cohort 2 will be a new prospectively recruited cohort that will be scanned in Los Angeles as part of this proposal and will be brought back for infant neurodevelopmental outcome at 9 and 18 months.

Description

Inclusion Criteria:

• Preterm birth (Gestational Age 21-36 weeks)
• English or Spanish speaking families
• PVL and Grade I and II IVH will be considered

Exclusion Criteria:

• Shunt
• Intubation, Cpap, Nasal Ventilation
• Chromosomal/Genetic abnormalities
• Mitochondrial/Metabolic Diseases
• Treatment for extracorporeal membrane oxygenation (ECMO)
• Grade III and IV IVH (optional)

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Infant Control Group; The control arm (term born Infants) will receive an MRI at neonatal age and neurodevelopmental follow-up assessments, investigators will then compare significant morphological and diffusion properties within the brain to those of a Preterm brain.	Diagnostic test: MRI; MRI analysis; Diagnostic test: Neurodevelopmental/Neuropsychological Assessment; Standardized Cognitive and Developmental Tests
Infant Preterm Group; The experimental group will consist of preterm infants, who will receive an MRI at neonatal age and neurodevelopmental assessments. This groups scans will then be compared to those of the control arm. Significant biomarkers will then be identified.	Diagnostic test: MRI; MRI analysis; Diagnostic test: Neurodevelopmental/Neuropsychological Assessment; Standardized Cognitive and Developmental Tests
Childhood Control Group; The experimental group will consist of preterm born children aged 6-8 years, who received an MRI at neonatal age and will be called back for a neuropsychological assessment. This groups scans will then be compared to those of the children control arm. Significant biomarkers will then be identified.	Diagnostic test: Neurodevelopmental/Neuropsychological Assessment; Standardized Cognitive and Developmental Tests
Childhood Preterm Group; The experimental group will consist of term born children aged 6-8 years, who received an MRI at neonatal age and will be called back for a neuropsychological assessment. This groups scans will then be compared to those of the children preterm group. Significant biomarkers will then be identified.	Diagnostic test: Neurodevelopmental/Neuropsychological Assessment; Standardized Cognitive and Developmental Tests

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Changes in Surface Area and Thickness of Subcortical Structures	Measured in Voxel Size (mm)	2018 - 2022
Changes in Diffusion values of white matter Tracts	Measured in mm squared per second	2018 - 2022
Differences in developmental Quotient / Neuropsychological scores	Measured using standardized tests (Bayley-III and NIH toolbox)	2018 - 2022

Collaborators and Investigators

• Sponsor: Children's Hospital Los Angeles
• Collaborators: University of Pittsburgh; Arizona State University

Publications and helpful links

General Publications

• Paquette N, Shi J, Wang Y, Lao Y, Ceschin R, Nelson MD, Panigrahy A, Lepore N. Ventricular shape and relative position abnormalities in preterm neonates. Neuroimage Clin. 2017 May 28;15:483-493. doi: 10.1016/j.nicl.2017.05.025. eCollection 2017.
• Lao Y, Wang Y, Shi J, Ceschin R, Nelson MD, Panigrahy A, Lepore N. Thalamic alterations in preterm neonates and their relation to ventral striatum disturbances revealed by a combined shape and pose analysis. Brain Struct Funct. 2016 Jan;221(1):487-506. doi: 10.1007/s00429-014-0921-7. Epub 2014 Nov 1.

Helpful Links

• Computational Imaging of Brain Organization Research Group (CIBORG) laboratory specializes in mathematical and numerical methods to study brain anatomy and function though magnetic resonance imaging.

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2018
• Primary Completion (Estimated): August 1, 2025
• Study Completion (Estimated): August 1, 2025

Study Registration Dates

• First Submitted: January 19, 2018
• First Submitted That Met QC Criteria: January 24, 2018
• First Posted (Actual): January 25, 2018

Study Record Updates

• Last Update Posted (Actual): April 10, 2024
• Last Update Submitted That Met QC Criteria: April 9, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Keywords: Neuroimaging; Prematurity
• Additional Relevant MeSH Terms: Mental Disorders; Pregnancy Complications; Obstetric Labor Complications; Obstetric Labor, Premature; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Congenital Abnormalities; Premature Birth; Neurodevelopmental Disorders
• Other Study ID Numbers: CHLA-17-00323

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No