EVALUATION OF THE OPTIC NERVE IN MIGRAINE PATIENTS BY MAGNETIC RESONANCE IMAGING HISTOGRAM ANALYSIS

Abstract

Background: Migraine is a chronic, paroxysmal neurovascular primary headache disease seen in approximately 15% of the world. In many studies on migraine, changes in the gray and white matter at the microvascular level have been detected. 90% of patients with aura have visual auras. Histogram analysis is an artificial intelligence application that can detect microscopic pathology in tissues before visual pathology. Objective: Histogram analysis was utilized in our investigation to ascertain whether or not the optic nerve, which is ordinarily visible on magnetic resonance images, was impacted. Methods: 120 adult migraine patients and 120 control group were involved. MRI was performed on a Philips 1.5 Tesla Ingenia device. For histogram analysis, optic nerve region of interest (ROI) measurement was performed in the coronal planes from the edges of the intraorbital segment, whose borders can be clearly distinguished, by using the manual drawing tool for both eyes. The data were analyzed through the MatLab program. Results: The average age of individuals diagnosed with migraine was 37.04 ± 9.57 years, whereas the control group had an average age of 37.8 ± 10.8 years. Between the two groups, 27 distinct parameters computed via histogram analysis were compared. In the control and migraine groups, no statistically significant distinction was observed between the right and left eyes. In contrast to the migraine and control groups, the Mean Local Standard Deviation of the Matrix was found to be The histogram's 5th, 10th, 25th, and 75th percentiles, the average squared, the root sum of squared, the size percent M, the most frequently used value, the median, and the average are all quantified using the root sum of squares. The number of pixels is also indicated. It was determined that ROI values were statistically significant (p0.05). Conclusion: In migraine patients, alterations in the optic nerve, which are typically discernible on conventional magnetic resonance images, may be identified via histogram analysis.