Evaluation of the corpus callosum using magnetic resonance imaging histogram analysis in autism spectrum disorder

Abstract

Background: Histogram analysis is a texture analysis method that can be used in medical images. Quantitative values of the intensity of images can be obtained with histogram analysis. It aimed to evaluate corpus callosum in magnetic resonance images (MRIs) using histogram analysis of pediatric patients with autism spectrum disorder (ASD) to compare them with healthy controls. Methods: This study included 29 children with ASD and 29 healthy children with normal brain MRI. High-resolution threedimensional turbo field echo images were obtained with a 1.5 T scanner device for brain magnetic resonance imaging. On the corpus callosum in the sagittal H.-weighted images obtained, mean gray level density (mean), the standard deviation, median, minimum, maximum, entropy, variance, skewness, kurtosis, uniformity, size % L, size % M, size % U, and percentile parameters were measured. Results: In ASD patients, mean, standard deviation, maximum, median, variance, entropy, 25%, 75%, 90/0, 97%, and 99% values were found to be lower than the control group, and size degrees/.3 U value was higher. In addition, the corpus callosum area was significantly lower in the ASD compared to the controls. Conclusion: According to our study, corpus callosum of patients with ASD showed differences compared to healthy controls by histogram analysis, even though they were seen as normal in brain MRI. We think that histogram analysis can be used to evaluate possibly affected areas of brain in ASD patients.