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MRI patterns and clinical outcomes in cerebral palsy: insights from a large MRICS-based cohort
Junying Yuan1,2, Kejie Cao3, Dong Li3
1Henan Pediatric Clinical Research Center and Henan Key Laboratory of Child Brain Injury, Institute of Neuroscience and Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. 15890056850@163.com.
Insights
Cerebral palsy (CP) MRI patterns classified by MRICS reveal diverse neurodevelopmental outcomes. Normal MRI scans do not rule out significant impairment, highlighting the need for integrated assessments.
Area of Science:
- Pediatric Neurology
- Neuroimaging
- Developmental Pediatrics
Background:
- Cerebral palsy (CP) is a complex neurological disorder with diverse etiologies and clinical presentations.
- Neuroimaging, particularly MRI, plays a crucial role in understanding the underlying brain abnormalities in CP.
- The MRI Classification System (MRICS) provides a standardized framework for categorizing CP-related brain lesions.
Purpose of the Study:
- To classify MRI patterns in children with CP using the MRI Classification System (MRICS).
- To investigate the associations between specific MRI patterns and perinatal risk factors.
- To examine the relationship between MRI findings and various clinical outcomes in children with CP.
Main Methods:
- Retrospective cohort study of 1,403 children with CP undergoing post-neonatal cranial MRI (2011-2020).
- MRI patterns categorized using MRICS; associations with perinatal factors (gestational age, birth weight, adversity) analyzed via logistic regression.
- Clinical outcomes (CP subtype, motor function, intellectual disability, epilepsy) assessed using statistical tests and correspondence analysis.
Main Results:
- MRI abnormalities detected in 86.5% of children; predominant white matter injury (PWMI) most frequent (46.5%).
- Preterm birth and perinatal adversity significantly correlated with PWMI and periventricular/intraventricular gray matter injury (PGMI).
- PWMI linked to spastic CP and better motor outcomes; PGMI/maldevelopments associated with epilepsy and severe impairment. Normal MRIs did not exclude functional deficits.
Conclusions:
- MRICS classification of MRI patterns offers crucial insights into the neurodevelopmental heterogeneity of CP.
- Normal MRI findings do not preclude significant clinical impairment, emphasizing limitations of structural imaging alone.
- Integrated neuroimaging, clinical, and genetic assessments are essential for comprehensive CP management.
Background:
To classify MRI patterns in children with cerebral palsy (CP) using the MRI Classification System (MRICS) and examine their associations with perinatal risk factors and clinical outcomes.
Methods:
This retrospective cohort study included 1,403 children with CP who underwent post-neonatal cranial MRI between 2011 and 2020. MRI patterns were categorized using MRICS. We analyzed the associations between MRI findings and perinatal risk factors (e.g., gestational age, birth weight, sex, perinatal adversity, plurality) using univariate and multivariable multinomial logistic regression. Clinical outcomes-including CP subtype, gross motor function, intellectual disability, epilepsy, and composite impairment index-were assessed using chi-square, Kruskal-Wallis tests, and correspondence analysis.
Results:
MRI abnormalities were observed in 86.5% of children, with predominant white matter injury (PWMI) being most common (46.5%). Preterm birth and perinatal adversity significantly increased the risk of PWMI and PGMI. PWMI was linked with spastic CP, better motor outcomes, and lower rates of intellectual disability. In contrast, PGMI and maldevelopments were associated with epilepsy, hearing loss, and severe impairment. Importantly, a subset of children with normal MRI findings still exhibited substantial functional impairments, emphasizing the limitations of structural imaging alone.
Conclusions:
MRI patterns, as classified by MRICS, provide critical insight into the neurodevelopmental heterogeneity of CP. Normal MRI findings do not preclude significant clinical impairment, underscoring the need for integrated neuroimaging and clinical-genetic assessment in CP management.
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