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Cluster headache is a highly disabling primary headache disorder, characterized by severe, excruciating, recurrent unilateral headache attacks. Typically, attacks' onset displays a circadian rhythm, and bout recurrence happens in a circannual fashion. Notably, the mechanisms underlying the shift between the remission phase and cluster bout are poorly understood.
Thus, the investigators aim to study brain connectivity in episodic cluster headache patients. Additionally, an explorative analysis of functional connectivity in chronic cluster headache patients will be performed.
Electroencephalogram (EEG) is widely available as a powerful mean to non-invasively study brain connectivity. High density EEG (HD-EEG), enables to record electrical brain activity with high temporal and spatial resolution. Through the analysis of brain oscillations across different frequency bands (from alpha to delta), it can evaluate sensory, pain processing and information integration, thus detecting potential markers or predictors for therapeutic interventions.
Previous neurophysiological studies focused on EEG and to assess functional connectivity or spectral analysis in migraine patients, with no data in cluster headache. Conventional studies found higher slow wave activity (predominantly theta) in the inter-ictal phase and higher excitability in the visual cortex during visual aura.
In 2016 a resting state study showed a predominance of low frequency bands in the ictal phase. The interictal and ictal phases patients also presented a diffuse lower coherence, suggesting low functional connectivity. Furthermore, an altered spatial connectivity for lower alpha-band activities was found in the interictal phases during sensory stimulation by means of HD-EEG, suggesting a thalamocortical dysrhythmia.
The primary aim of the study is to evaluate changes in functional connectivity in episodic cluster headache patients, comparing the active phase with the remission phase. Additionally, an explorative analysis of functional connectivity in chronic cluster headache patients will be performed.
Study design:
Episodic cluster headache patients (eCH) will be evaluated in two separate timepoints: during the active phase (T0), defined as at least one week of active bout, and in remission phase (T1), defined as at leat 14 days without headache and without any ongoing preventive medication. During each visit, clinical data will be collected, and an HD-EEG will be performed.
Chronic cluster headache patients (cCH) will be evaluated in a single timepoint, and healthy controls will undergo HD-EEG registration once.
HD-EEG registration:
Participants will perform 4 recordings (6 minutes each) in resting-state condition, 2 with opened eyes, and 2 with closed eyes, in a randomized order.
The investigators will analyze the resting state FC among six resting state networks (Default mode network, Dorsal attention network, Ventral attention network, Language network , Somatomotor network and Visual network) in the following frequency bands: alfa 8-12 Hz, beta 13-30 Hz, gamma 31-80 Hz, theta 4-7 Hz. delta 1-3 Hz.
Acquisition parameters will be: High-Pass: 0.5 Hz; Low-Pass: 100 Hz; Notch: 50 Hz. For analysis of HD-EEG data, a tailored analysis pipe-line that was previously developed and validated to reconstruct neural sources from cortical/subcortical gray matter will be performed. EEG signals will be band-pass filtered (1-80 Hz) and down-sampled at 250 Hz. Biological artifacts will be rejected using Independent Component Analysis (ICA). EEG signals will be referenced with a customized version of the Reference Electrode Standardization Technique (REST). A matrix will estimate the relationship between the measured scalp potentials and the dipoles corresponding to brain sources. Sources reconstruction will be performed with the exact low-resolution brain electromagnetic tomography (eLORETA) algorithm
Statistical plan:
The sample size was computed with the freeware online platform www.openepi.com. As there are no previous studies on HD-EEG functional connectivity in cluster headache, our sample size analysis was based on the work of Bjork (Bjork et al., 2009). A difference between groups in the theta relative power band equal to 0.04 (±0.04) will be considered as clinically meaningful. Considering a two-tailed t-test for the comparison with confidence interval 95%; power: 80%, the minimum suggested sample size was 20 subjects for group.
A preliminary normality analysis will be performed to decide whether to use parametric or non-parametric methods, through Shapiro Wilk test.
Numerical variables will be described as mean and standard deviation (or median and quartiles if appropriate), categorical variables as raw numbers and percentages.
Functional connectivity analyses will be conducted for separate bands and eyes closed registration.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy subjects |
| ||
| Episodic cluster headache, active |
| ||
| Episodic cluster headache, remission |
| ||
| Chronic cluster headache |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Resting state HD-EEG recording | Diagnostic Test | All subjects will be recorded with a resting state HD-EEG recording. 12 minutes in the eyes closed and 12 minutes in the eyes open condition. |
| Measure | Description | Time Frame |
|---|---|---|
| Difference in absolute functional connectivity values (continuous variable, without unit of measurement) in resting state networks (RSN-FC) in episodic cluster headache patients between active and remission phases | To compare HD-EEG functional connectivity in episodic cluster headache patients between the two phases of the disease | Through study completion, an average of 2 years |
| Differences in absolute functional connectivity values (continuous variable, without unit of measurement) in resting state networks (RSN-FC) between episodic cluster headache patients and healthy controls | To compare HD-EEG functional connectivity between episodic cluster headache patients in the two phases of the disease and healthy controls | Through study completion, an average of 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| Differences in absolute functional connectivity values (continuous variable, without unit of measurement) in resting state networks (RSN-FC) between episodic cluster headache patients and chronic cluster headache patients | To compare HD-EEG functional connectivity between episodic cluster headache patients and chronic cluster headache patients | Through study completion, an average of 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| To assess for correlations between clinical features of episodic cluster headache and absolute functional connectivity values in resting state networks (RSN-FC) | To search for correlations between clinical variables and HD-EEG functional connectivity in episodic cluster headache | Through study completion, an average of 2 years |
Inclusion Criteria:
Exclusion Criteria:
Healthy controls (HCs)
Inclusion Criteria:
Exclusion Criteria:
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Subjects with episodic and chronic cluster headache patients attending the outpatient clinic of the Headache Science & Neurorehabilitation Center of the IRCCS Mondino Foundation (Pavia, Italy).
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Cinzia Fattore, MD | Contact | 0382380385 | 0039 | cinzia.fattore@mondino.it |
| Roberto De Icco, MD | Contact | 0382 380425 | roberto.deicco@mondino.it |
| Name | Affiliation | Role |
|---|---|---|
| Roberto De Icco, MD | Headache Science ahd Neurorehabilitation Research Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Headache Science & Neurorehabilitation Center | Recruiting | Pavia | 27100 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29368949 | Background | Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd edition. Cephalalgia. 2018 Jan;38(1):1-211. doi: 10.1177/0333102417738202. No abstract available. | |
| 19705061 | Background | Bjork MH, Stovner LJ, Engstrom M, Stjern M, Hagen K, Sand T. Interictal quantitative EEG in migraine: a blinded controlled study. J Headache Pain. 2009 Oct;10(5):331-9. doi: 10.1007/s10194-009-0140-4. Epub 2009 Aug 25. |
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| ID | Term |
|---|---|
| D003027 | Cluster Headache |
| D020773 | Headache Disorders |
| ID | Term |
|---|---|
| D051303 | Trigeminal Autonomic Cephalalgias |
| D051270 | Headache Disorders, Primary |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| Differences in absolute functional connectivity values (continuous variable, without unit of measurement) in resting state networks (RSN-FC) between chronic cluster headache patients and healthy controls | To compare HD-EEG functional connectivity between chronic cluster headache patients and healthy controls | Single evaluation in chronic cluster headache (cCH) vs. healthy controls (HCs) |
| 31035929 | Background | Coppola G, Di Lorenzo C, Parisi V, Lisicki M, Serrao M, Pierelli F. Clinical neurophysiology of migraine with aura. J Headache Pain. 2019 Apr 29;20(1):42. doi: 10.1186/s10194-019-0997-9. |
| 28963615 | Background | de Tommaso M, Trotta G, Vecchio E, Ricci K, Siugzdaite R, Stramaglia S. Brain networking analysis in migraine with and without aura. J Headache Pain. 2017 Sep 29;18(1):98. doi: 10.1186/s10194-017-0803-5. |
| 27807767 | Background | Cao Z, Lin CT, Chuang CH, Lai KL, Yang AC, Fuh JL, Wang SJ. Resting-state EEG power and coherence vary between migraine phases. J Headache Pain. 2016 Dec;17(1):102. doi: 10.1186/s10194-016-0697-7. Epub 2016 Nov 2. |
| 34258580 | Background | Chamanzar A, Haigh SM, Grover P, Behrmann M. Abnormalities in cortical pattern of coherence in migraine detected using ultra high-density EEG. Brain Commun. 2021 Apr 2;3(2):fcab061. doi: 10.1093/braincomms/fcab061. eCollection 2021. |
| 33200500 | Background | Semprini M, Bonassi G, Barban F, Pelosin E, Iandolo R, Chiappalone M, Mantini D, Avanzino L. Modulation of neural oscillations during working memory update, maintenance, and readout: An hdEEG study. Hum Brain Mapp. 2021 Mar;42(4):1153-1166. doi: 10.1002/hbm.25283. Epub 2020 Nov 17. |
| 25713521 | Background | Aoki Y, Ishii R, Pascual-Marqui RD, Canuet L, Ikeda S, Hata M, Imajo K, Matsuzaki H, Musha T, Asada T, Iwase M, Takeda M. Detection of EEG-resting state independent networks by eLORETA-ICA method. Front Hum Neurosci. 2015 Feb 10;9:31. doi: 10.3389/fnhum.2015.00031. eCollection 2015. |
| D009422 | Nervous System Diseases |