Radiomic Models for Diagnosing Juvenile Myoclonic Epilepsy Should Note Its Genetic Heterogeneity
Abstract
I read with interest the article by Kim et al. [1] about the generation of magnetic resonance imaging (MRI)derived radiomic models to diagnose juvenile myoclonic epilepsy (JME). Seven radiomic models (light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree) were examined [1]. The light gradient boosting machine achieved the highest area under the receiver operating curve, without significant differences with other models [1]. The putamen and ventral diencephalon were the most important for suggesting JME [1]. MRI-derived radiomic models differentiated JME from healthy controls [1]. The study is appealing but needs further discussion. The main study limitation is that JME is considered as a single entity, although there is evidence that this is not the case [1]. JME can be idiopathic or hereditary [2]. Hereditarily, mutations in several genes, such as CACNB4, EFHC1, NKCC1 (SCL12A2), KCC2 (SCL12A5), CSTB, and GABRA1 [2,3], were reportedly associated with JME [2]. The genetic heterogeneity of the disease suggests that cerebral functions may be differentially impaired in these JME subtypes. Additionally, there is evidence that the methylation status of certain DNA segments is associated with JME expression [4]. Current antiseizure drug (ASD) treatment was not considered in the evaluation. ASDs can strongly influence the clinical and subclinical seizure activity extent…
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