ABSTRACT
BACKGROUND AND PURPOSE: Texture analysis is an image processing technique that can be used to extract parameters able to describe meaningful features of an image or ROI. Texture analysis based on the gray level co-occurrence matrix gives a second-order statistical description of the image or ROI. In this work, the co-occurrence matrix texture approach was used to extract information from brain MR images of patients with Friedreich ataxia and a control group, to see whether texture parameters were different between these groups. A longitudinal analysis was also performed. MATERIALS AND METHODS: Twenty patients and 21 healthy controls participated in the study. Both groups had 2 sets of T1-weighted MR images obtained 1 year apart for every subject. ROIs chosen for analysis were the medulla oblongata and pons. Texture parameters were obtained for these ROIs for every subject, for the 2 sets of images. These parameters were compared longitudinally within groups and transversally between groups. RESULTS: The comparison between patients and the control group showed a significant differences for the medulla oblongata (t test, P < .05, Bonferroni-corrected) but did not show a statistically significant difference for the pons. Longitudinal comparison of images obtained 1 year apart did not show differences for either patients or for controls, in any of the analyzed structures. CONCLUSIONS: Gray level co-occurrence matrix-based texture analysis showed statistically significant differences for the medulla oblongata of patients with Friedreich ataxia compared with controls. These results highlight the medulla as an important site of damage in Friedreich ataxia.
