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| Name | Class |
|---|---|
| National Research Foundation of Korea | OTHER |
| Sungkyunkwan University | OTHER |
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The purpose of this study is to identify a core fMRI feature that determines migrainous brain and plastic fMRI features that changes with longitudinal courses of migraine.
Migraine is associated with functional alterations in specific brain networks. The investigators aimed to identify network abnormalities which remain unchanged throughout the longitudinal course of migraine. The investigators also aimed to identify networks which change in association with changes in migraine frequency and associated psychiatric conditions. The investigators expect these can serve as neuroimaging biomarkers for diagnosis of migraine brain and monitoring of disease severity.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Migraineurs | Patients diagnosed with migraine based on the ICHD-3 beta will undergo 3-tesla resting-state functional MRI. |
| |
| Control | Normal controls without headaches will undergo 3-tesla resting-state functional MRI. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| resting-state functional MRI | Diagnostic Test |
|
| Measure | Description | Time Frame |
|---|---|---|
| Core fMRI features for migraine brain | Among significant networks identified by ICA, we will identify altered networks which remain unchanged in follow-up resting-state fMRI in 1 year. | 1-year follow-up (2nd year) |
| Measure | Description | Time Frame |
|---|---|---|
| Candidate fMRI features for migraine | Using baseline resting-state fMRI, altered brain networks associated with migraine will be identified by independent component analysis (ICA) between patients and controls. | Baseline (1st year) |
| Dynamic fMRI features for disease severity |
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Inclusion Criteria:
Migrainuers :
Controls:
Exclusion criteria:
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Controls and migraineurs who visited to a single university hospital
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| Name | Affiliation | Role |
|---|---|---|
| Mi Ji Lee, MD | Samsung Medical Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Samsung Medical Center | Seoul | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38554782 | Derived | Park Y, Lee MJ, Yoo S, Kim CY, Namgung JY, Park Y, Park H, Lee EC, Yoon YD, Paquola C, Bernhardt BC, Park BY. GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox. Neuroimage. 2024 May 1;291:120595. doi: 10.1016/j.neuroimage.2024.120595. Epub 2024 Mar 29. |
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| ID | Term |
|---|---|
| D008881 | Migraine Disorders |
| ID | Term |
|---|---|
| D051270 | Headache Disorders, Primary |
| D020773 | Headache Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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Among significant networks identified by ICA, we will identify altered networks which change in association with changes in headache frequency in follow-up resting-state fMRI in 1 year. |
| 1-year follow-up (2nd year) |
| D009422 | Nervous System Diseases |