Background Previous functional and structural imaging studies have revealed that subcortical structures play a key a role in pain processing. The recurring painful episodes might trigger maladaptive plasticity or alternatively degenerative processes that might be detected by MRI as changes in size or microstructure. In the current investigation, we aimed to identify the macro- and microstructural alterations of the subcortical structures in episodic cluster headache. Methods High-resolution T1-weighted and diffusion-weighted MRI images with 60 gradient directions were acquired from 22 patients with cluster headache and 94 healthy controls. Surface-based segmentation analysis was used to measure the volume of the subcortical nuclei, and mean diffusion parameters (fractional anisotropy, mean, radial and axial diffusivity) were determined for these structures. In order to understand whether the size and diffusion parameters could be investigated in a headache lateralised manner, first the asymmetry of the size and diffusion parameters of the subcortical structures was analysed. Volumes and diffusion parameters were compared between groups and correlated with the cumulative number of headache days. To account for the different size of the patient and control group, a bootstrap approach was used to investigate the stability of the findings. Results A significant lateralisation of the size (caudate, putamen and thalamus) and the diffusion parameters of the subcortical structures were found in normal controls. In cluster headache patients, the mean fractional anisotropy of the right amygdalae, the mean axial and mean diffusivity of the right caudate nucleus and the radial diffusivity of the right pallidum were higher. The mean anisotropy of the right pallidum was lower in patients. Conclusion The analysis of the pathology in the subcortical structures in episodic cluster headache reveals important features of the disease, which might allow a deeper insight into the pathomechanism of the pain processing in this headache condition.

Bacs Kiskun County Hospital Kecskemét Hungary

Department of Image Processing and Computer Graphics Faculty of Science and Informatics Szeged Hungary

Department of Neurology Albert Szent Györgyi Clinical Center University of Szeged Szeged Hungary

Department of Neurology Semmelweis University Budapest Hungary

International Clinical Research Center St Anne's University Hospital Brno Brno Czech Republic

MTA SZTE Neuroscience Research Group Szeged Hungary

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