A systematic analysis of neuroimaging studies has been shown to be successful in pediatric neuroradiology, e.g. in the evaluation of white matter diseases. Systematic magnetic resonance imaging (MRI) pattern recognition may simplify and guide the diagnosis of classified diseases and makes it possible to cluster patients with identical MR patterns, allowing further clinical, laboratory, genetic, and molecular investigations. Clinical research on homogenous groups of patients could then allow the identification of new diseases or provide information on detailed long-term outcome. Furthermore, systematic evaluation of longitudinal MR studies should help to quantify the success of therapeutic approaches. The application of the same systematic analysis may be helpful to compare data between different institutions, for example in the context of multicentre studies.
MRI plays a key role in the diagnostic work-up of children with cerebral palsy (CP). In more than 80% of the children with CP, neuroimaging shows abnormal findings. Correlation between the qualitative neuroimaging findings and (1) pathogenesis of CP, (2) clinical type of CP, and (3) functional outcome of the affected children has been demonstrated. Additionally, a normal brain MRI in a child with CP is a red flag and should prompt clinicians to consider diseases ‘masquerading’ as CP. The qualitative nature of the neuroimaging evaluation in these studies incorporates some limitations such as evaluator dependency and limited reproducibility.
Fiori et al. are moving have moved towards reducing these limitations by introducing a novel, highly-reliable, semi-quantitative scoring scale to analyze structural brain MRI in children with CP. This systematic approach quantifies lesion characteristics in different brain regions as a global score as well as subscores that assess the lesions separately based on side, regions, and depth. Further validation studies should confirm the clinical utility of this scoring system in providing a reliable tool to study the relationship between topographical brain abnormalities and clinical function in children with CP. Additionally, the application of this scoring system should facilitate the comparison of patient groups form different centers and increase the multicentre research collaboration.
Despite these innovative aspects, the scoring system proposed by Fiori et al. has some limitations. The use of an adult template limits the application of the scoring system to older children (>3 y), while the diagnosis of CP may be made earlier in life. The application only to older children limits the role of the scoring system as a semi-quantitative biomarker of outcome in children with CP. Additionally, the difficulty in delineating the boundaries of abnormal tissue may limit the application of the scoring system to cortical malformations. Another limitation of the proposed scoring system is that it does not allow the differentiation between primary and secondary injuries, e.g. a primary thalamic lesion in a term neonate with acute hypoxic-ischemic injury versus a secondary thalamic involvement in a preterm newborn with periventricular white matter injury. Differentiation between a primary and secondary lesion is important in terms of outcome. We suggest that the authors take these limitations into account and further develop their scoring system accordingly.
Advanced neuroimaging techniques including diffusion tensor imaging (DTI) or proton MR spectroscopy (1H-MRS) have been shown to play an additive role in the evaluation of children with CP. There is increasing evidence that DTI provides insights into the specific injury and reorganization of white matter pathways in children with CP. Microstructural changes in white matter integrity within the descending corticospinal tracts correlate with the clinical severity of CP. Additionally, changes in DTI scalars in the ascending sensorimotor tracts have been reported to provide information about corticomotor reorganization. Finally, atlas-based, whole-brain analysis of DTI data in children with CP revealed that anatomical abnormalities and their distribution differ significantly between children with dyskinetic and spastic CP and were marked larger in children with dyskinetic CP. The integration of quantitative scalars derived from advanced MRI techniques is an additional, potential, and intriguing development of this scoring system to increase its role in better understanding the relationships between macro- and microstructural brain changes and clinical functions in children with CP.