“…We appreciate DeSouza et al.’s interest in and comments (1) on our study (2) and find the results from their recent study of great interest (3). In their study, in addition to conventional volume and thickness-based measures, a graph-theoretical approach was used to delineate differences in structural covariance networks between patients with chronic migraine (CM) and healthy controls (HC).…”
mentioning
confidence: 72%
“…The authors received no financial support for the research, authorship, and/or publication of this article. Kuan-Lin Lai 1,2,3,4 , David M Niddam 4,5 Jong-Ling Fuh 1,2,4 , Wei-Ta Chen 1,2,4,5 Jaw-Ching Wu 3,6 and Shuu-Jiun Wang 1,2,4…”
“…We appreciate DeSouza et al.’s interest in and comments (1) on our study (2) and find the results from their recent study of great interest (3). In their study, in addition to conventional volume and thickness-based measures, a graph-theoretical approach was used to delineate differences in structural covariance networks between patients with chronic migraine (CM) and healthy controls (HC).…”
mentioning
confidence: 72%
“…The authors received no financial support for the research, authorship, and/or publication of this article. Kuan-Lin Lai 1,2,3,4 , David M Niddam 4,5 Jong-Ling Fuh 1,2,4 , Wei-Ta Chen 1,2,4,5 Jaw-Ching Wu 3,6 and Shuu-Jiun Wang 1,2,4…”
“…Chronicity of migraine accounts for approximately 2.5% of episodic migraines annually, and its neuromechanism remains unknown. 6 Cerebral gray matter plays an important role in the pathophysiology of CM, 7 and the previous study demonstrated that gray matter was associated with pain sensitivity, 8 which was common in chronic pain. Advanced functional imaging studies have shown that functional connectivity changed in cortex 9,10 and deep nuclei [9][10][11][12][13][14] was altered in both the interictal and ictal phases of migraine, and further structural imaging studies also indicated significantly abnormal gray matter volumes in migraine.…”
Background: Prior studies identified iron deposition in deep brain nuclei and the periaqueductal gray matter region in chronic migraine (CM), and less is known about the cerebral iron deposition over the whole cerebral gray matter in CM. The aim of this case-control study is to investigate the cerebral iron deposition of gray matter in CM using an advanced quantitative susceptibility mapping. Methods: A multi-echo gradient echo MR sequence was used to obtain raw quantitative susceptibility mapping data from 12 CM patients and 18 normal controls (NC), and the quantitative susceptibility mapping were reconstructed. Three dimensional T1 images were segmented and the gray matter mask was generated to extract the susceptibility value of gray matter over the whole brain. The independent t test and receiver operating characteristic curve (ROC) was used to investigate the iron deposition changes in CM patients. Results: CM presented a higher susceptibility value (1.44×10-3 ppm) compared with NC group (0.47×10-3 ppm) (P < 0.0001) over the whole cerebral gray matter. There was no correlation between susceptibility value and the clinical variables including disease duration, Visual Analog Scale (VAS), Migraine Disability Assessment Scale (MIDAS), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD) and Montreal Cognitive Assessment (MoCA) scores (P > 0.05). ROC analysis demonstrated the susceptibility had a high diagnostic efficacy (AUC 0.949, sensitivity 77.78% and specificity 100%) in distinguishing CM from NC. Conclusion: CM patients had increased iron deposition in total cerebral gray matter which could be considered as a potential diagnostic and evaluated imaging biomarker in CM.
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