Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS)

Premature Infant Clinical Trial

Official title:

Early Prediction of Cognitive and Motor Deficits Using Advanced MRI in Very Preterm Infants

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT03345069
• Other study ID #: CIN_EARLYPREDICTION_001
• Secondary ID: 5R01NS0942005R01
• Status: Active, not recruiting
• Start date: September 16, 2016
• Est. completion date: November 2027

Study information

• Verified date: February 2024
• Source: Children's Hospital Medical Center, Cincinnati
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The Early Prediction Study is a longitudinal population-based cohort study for very preterm infants ≤32 weeks gestational age. Preterm infants recruited from three greater Cincinnati and two Dayton area neonatal intensive care units (NICUs) will undergo advanced MRIs at 41 weeks postmenstrual age and neurodevelopmental testing at the corrected ages of two and three years correct age. The goal of the Early Prediction Study is to accurately predict motor, cognitive, and behavioral deficits in individual very preterm infants using neuroimaging technologies and established epidemiologic approaches.

Description:

With every neonatal intensive care unit discharge, physicians and early intervention specialists face a critical challenge: How to counsel parents about their very preterm infant's risk of developing cognitive and motor deficits and accurately assign early intervention therapies. More than 100,000 babies are born very preterm at ≤32 weeks gestational age every year in the United States. Up to 35% of these preterm survivors develop cognitive deficits, and up to 20% develop motor impairment. This places them at high risk for poor educational, health, and social outcomes. Yet reliable diagnosis of cognitive and motor deficits cannot be made until early childhood. This long and unnecessary delay wastes early intervention resources, dilutes the effectiveness of infant stimulation programs, and disrupts parental adaptation. Attempts to address these gaps with conventional neuroimaging and other approaches have failed. Thus, a critical need exists before neonatal discharge, to accurately predict cognitive and motor deficits in individual very preterm infants with the use of novel neuroimaging technologies and established epidemiologic approaches. The investigators long-term research goal is to elucidate the etiology, pathogenesis, and early prediction of cognitive and motor deficits in order to facilitate preventive early interventions in very preterm infants, resulting in better outcomes. The investigators objectives in this application therefore are to: 1. Identify the clinical antecedents of objectively diagnosed diffuse white matter abnormality (DWMA). 2. Associate DWMA with pathologic changes on neuroimaging. 3. Predict cognitive and behavioral deficits at 3 years of age using objectively diagnosed DWMA in a geographic cohort of very preterm infants. 4. To predict motor impairment, especially cerebral palsy at 24 months corrected age. The investigators central hypothesis is that objectively quantified DWMA is pathologic, associated with inflammation-associated perinatal illnesses, and an independent predictor of cognitive deficits at 3 years corrected age in very preterm infants. The investigators rationale for this research is that new knowledge investigators expect to have generated will enhance parental counseling, facilitate accurate risk stratification for early intervention therapies, and guide biologically-based strategies for early prevention of DWMA and cognitive and motor deficits in very preterm infants.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 393
• Est. completion date: November 2027
• Est. primary completion date: December 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A to 3 Years

Eligibility

Inclusion Criteria:

• Hospitalized infants born at =32 weeks completed gestational age that are being cared for in all three level III/IV NICUs from the Greater Cincinnati area.

Exclusion Criteria:

• Infants with known chromosomal or congenital anomalies affecting the central nervous system or with cyanotic heart disease.

Related Conditions & MeSH terms

• Premature Birth
• Premature Infant

Locations

Country	Name	City	State
United States	Cincinnati Children's Hospital Medical Center	Cincinnati	Ohio

Sponsors (6)

Lead Sponsor	Collaborator
Children's Hospital Medical Center, Cincinnati	Good Samaritan Hospital, Ohio, Kettering Health Network, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), University of Cincinnati

Country where clinical trial is conducted

United States, 

References & Publications (15)

Chandwani R, Harpster K, Kline JE, Mehta V, Wang H, Merhar SL, Schwartz TL, Parikh NA. Brain microstructural antecedents of visual difficulties in infants born very preterm. Neuroimage Clin. 2022;34:102987. doi: 10.1016/j.nicl.2022.102987. Epub 2022 Mar 9 — View Citation

Chandwani R, Kline JE, Harpster K, Tkach J, Parikh NA; Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS) Group. Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants. Hum Brain Mapp. — View Citation

Chen M, Li H, Fan H, Dillman JR, Wang H, Altaye M, Zhang B, Parikh NA, He L. ConCeptCNN: A novel multi-filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome. Med Phys. 2022 May;49(5):3171-3184. doi: — View Citation

Harpster K, Merhar S, Priyanka Illapani VS, Peyton C, Kline-Fath B, Parikh NA. Associations Between Early Structural Magnetic Resonance Imaging, Hammersmith Infant Neurological Examination, and General Movements Assessment in Infants Born Very Preterm. J — View Citation

He L, Li H, Chen M, Wang J, Altaye M, Dillman JR, Parikh NA. Deep Multimodal Learning From MRI and Clinical Data for Early Prediction of Neurodevelopmental Deficits in Very Preterm Infants. Front Neurosci. 2021 Oct 5;15:753033. doi: 10.3389/fnins.2021.753 — View Citation

He L, Li H, Wang J, Chen M, Gozdas E, Dillman JR, Parikh NA. A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants. Sci Rep. 2020 Sep 15;10(1):15072. doi: 10.1038/s41598-020-71914-x. — View Citation

Jain VG, Kline JE, He L, Kline-Fath BM, Altaye M, Muglia LJ, DeFranco EA, Ambalavanan N, Parikh NA; Cincinnati Infant Neurodevelopment Early Prediction Study Investigators. Acute histologic chorioamnionitis independently and directly increases the risk fo — View Citation

Kline JE, Illapani VSP, Li H, He L, Yuan W, Parikh NA. Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency. Neuroimage Clin. 2021;31:102739. doi: 10.1016/j.nicl.2021.102739. Epub 2021 Jun 25. — View Citation

Kline JE, Yuan W, Harpster K, Altaye M, Parikh NA. Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants. Neuroimage. 2021 Dec 15;245:118688. doi: 10.1016/j.neuroimag — View Citation

Lal SK, Nath LS. An atypical case of Vogt-Koyanagi syndrome. J Indian Med Assoc. 1986 Dec;84(12):382-3. No abstract available. — View Citation

Li H, Chen M, Wang J, Illapani VSP, Parikh NA, He L. Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants. Radiol Artif Intell. 2021 Feb 3;3(3):e200166. doi: 10.1148/ryai.202 — View Citation

Parikh NA, Sharma P, He L, Li H, Altaye M, Priyanka Illapani VS; Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS) Investigators. Perinatal Risk and Protective Factors in the Development of Diffuse White Matter Abnormality on Term-Equival — View Citation

Parikh NA. Advanced neuroimaging and its role in predicting neurodevelopmental outcomes in very preterm infants. Semin Perinatol. 2016 Dec;40(8):530-541. doi: 10.1053/j.semperi.2016.09.005. Epub 2016 Nov 15. — View Citation

Tamm L, Patel M, Peugh J, Kline-Fath BM, Parikh NA; Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS) Group. Early brain abnormalities in infants born very preterm predict under-reactive temperament. Early Hum Dev. 2020 May;144:104985. do — View Citation

Yuan W, Tamm L, Harpster K, Altaye M, Illapani VSP, Parikh NA. Effects of intraventricular hemorrhage on white matter microstructural changes at term and early developmental outcomes in infants born very preterm. Neuroradiology. 2021 Sep;63(9):1549-1561. — View Citation

* Note: There are 15 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Motor development	Standardized assessment and diagnosis of cerebral palsy at 2 years corrected age	2 years of age, corrected for prematurity
Primary	Cognitive development	General Conceptual Ability (GCA) score from the Differential Abilities Scale, 2nd Edition	3 years of age, corrected for prematurity
Primary	Behavioral development	Scores on the Child Behavior Checklist & Early Childhood Behavior Questionnaire - Short Form	3 years of age, corrected for prematurity
Secondary	Cognitive and language deficits at 2years of age	Cognitive and language scores on Bayley Scales of Infant and Toddler Development, 3rd Ed	2 years of age, corrected for prematurity
Secondary	Executive function	Computerized measures of executive function for preschoolers	3 years of age, corrected for prematurity
Secondary	Behavioral development	General Adaptive Composite score on the Adaptive Behavior Assessment System, 2nd Ed.	3 years of age, corrected for prematurity
Secondary	Pre-academic skills	Bracken School Readiness Assessment, 3rd Ed.	3 years of age, corrected for prematurity

External Links

•   Early Prediction Study website