Dong Ah Lee1, Ho-Joon Lee2, Hyung Chan Kim1, Kang Min Park3. 1. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Republic of Korea. 2. Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea. 3. Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Republic of Korea. smilepkm@hanmail.net.
Abstract
OBJECTIVE: The hypothalamus is one of the key structures involved in the pathophysiology of cluster headaches. This study aimed to analyze the volume of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache. METHODS: We retrospectively enrolled 18 patients with episodic cluster headache and 18 age- and sex-matched healthy controls. We calculated individual structural volumes in ten hypothalamic subunits using three-dimensional T1-weighted imaging and the FreeSurfer program, which conducted an automated segmentation based on deep convolutional neural networks. We also performed an analysis of the structural covariance network in the hypothalamus using graph theory and the BRAPH program. We compared the volumes of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache versus those of healthy controls. RESULTS: There were no significant differences in the structural volumes of the whole hypothalamus and hypothalamic subunits between patients with cluster headache and healthy controls. However, patients with cluster headache had significant alterations of the structural covariance network in the hypothalamus compared to that of healthy controls. The network measure of small-worldness index in patients with cluster headache was lower than that in healthy controls (0.844 vs. 0.955, p = 0.004). CONCLUSION: We demonstrated a significant difference in the structural covariance network in the hypothalamus of patients with cluster headache versus those of healthy controls. These findings could be related to the pathogenesis of cluster headache.
OBJECTIVE: The hypothalamus is one of the key structures involved in the pathophysiology of cluster headaches. This study aimed to analyze the volume of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache. METHODS: We retrospectively enrolled 18 patients with episodic cluster headache and 18 age- and sex-matched healthy controls. We calculated individual structural volumes in ten hypothalamic subunits using three-dimensional T1-weighted imaging and the FreeSurfer program, which conducted an automated segmentation based on deep convolutional neural networks. We also performed an analysis of the structural covariance network in the hypothalamus using graph theory and the BRAPH program. We compared the volumes of hypothalamic subunits and structural covariance networks in the hypothalamus of patients with cluster headache versus those of healthy controls. RESULTS: There were no significant differences in the structural volumes of the whole hypothalamus and hypothalamic subunits between patients with cluster headache and healthy controls. However, patients with cluster headache had significant alterations of the structural covariance network in the hypothalamus compared to that of healthy controls. The network measure of small-worldness index in patients with cluster headache was lower than that in healthy controls (0.844 vs. 0.955, p = 0.004). CONCLUSION: We demonstrated a significant difference in the structural covariance network in the hypothalamus of patients with cluster headache versus those of healthy controls. These findings could be related to the pathogenesis of cluster headache.