Frontal cortical thinning and disease burden–related plasticity in episodic cluster headache: a whole-brain cortical and subcortical morphometry study

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Although the posterior hypothalamus has been implicated as a key structure in CH pathophysiology, evidence suggests that this disorder involves widespread alterations in cortical and subcortical networks. This study investigated whole-brain cortical thickness and subcortical volumetric differences in patients with episodic CH (eCH) compared with healthy controls (HC) and examined associations with clinical burden. Methods Twenty-six patients with eCH and 20 age- and sex-matched HC underwent 3T MRI scanning during the bout period but outside attacks. Cortical thickness and subcortical volumes were analyzed using FreeSurfer. Group differences were tested with FDR-corrected vertex-wise and ROI-based analyses. Associations between cortical thickness, sub-cortical volumes, and clinical variables (attack frequency and duration, disease duration, and pain intensity) were evaluated using general linear models adjusted for age and sex. Results Compared with HC, patients with eCH exhibited significant cortical thinning in two clusters: the right pars triangularis (inferior frontal gyrus, BA45) and the left superior frontal gyrus (p < 0.05, FDR-corrected). Positive correlations between cortical thickness and clinical burden were observed in multimodal associative cortices, including inferior temporal, postcentral, superior parietal, supramarginal, inferior parietal, and lateral occipital regions (p < 0.01, FDR-corrected). No significant subcortical volumetric alterations or correlations with clinical variables were detected. Conclusions Our findings demonstrate frontal cortical thinning and disease burden–related cortical thickness increases in associative temporal, parietal and occipital cortices in eCH, supporting a two-level model of cortical alterations. Frontal cortical thinning may represent a trait-like abnormality affecting executive control hubs, whereas cortical thickening in associative regions may reflect dynamic plasticity in response to clinical burden. These results extend the evidence that CH is a network-level disorder and highlight the potential for cortical thickness measures to serve as neuroimaging biomarkers of disease progression. cluster headache cortical thickness frontal cortex plasticity MRI Figures Figure 1 Introduction Cluster headache (CH) is the most common trigeminal autonomic cephalalgia, a primary headache disorder characterized by recurrent attacks of excruciating unilateral pain associated with ipsilateral cranial autonomic symptoms and circadian rhythmicity [ 1 ]. Although the posterior hypothalamus was initially identified as the main hub in CH pathophysiology based on early positron emission tomography studies [ 2 ], increasing evidence indicates that CH is a network-level disorder involving the trigeminovascular system, hypothalamus, thalamus, and higher-order cortical and subcortical areas [ 1 , 3 ]. Advanced neuroimaging techniques have revealed widespread structural and functional brain alterations in CH patients. Resting-state fMRI and diffusion tensor imaging (DTI) studies have demonstrated abnormal connectivity between the hypothalamus, the salience network, and executive control networks, as well as microstructural alterations in the hypothalamus and thalamus, even during headache-free periods [ 4 , 5 ]. Morphometric studies using voxel-based morphometry (VBM) or surface-based morphometry (SBM) have reported inconsistent findings, with some authors describing hypothalamic hypertrophy or cortical thinning in frontal, temporal, and parietal cortices [ 6 – 8 ], while others did not detect macrostructural differences [ 9 , 10 ]. Methodological differences, including patient selection (episodic vs chronic CH), timing of scanning (in- vs out-of-bout), and prophylactic medication use, may explain these discrepancies. Our group recently demonstrated that hypothalamic macrostructure is preserved in episodic CH (eCH) patients scanned during the in-bout period [ 9 ], while the same cohort exhibited hypothalamic and thalamic microstructural abnormalities and dysfunctional connectivity between cortical networks [ 4 ]. These findings suggest that structural alterations may preferentially affect distributed cortical and subcortical networks rather than being confined to the hypothalamus. Given these observations, we sought to further investigate whole-brain cortical thickness differences in the same cohort of eCH patients and matched healthy controls. In addition, we examined the relationship between cortical thickness and clinical variables, including disease duration, attack frequency, and pain intensity. We hypothesized that cortical alterations would involve multimodal associative regions and that their severity would correlate with clinical burden, thereby extending previous evidence of network-level dysfunction in CH. We also evaluated subcortical volumetric differences and their relationship with clinical burden. Methods This study included 26 patients with episodic cluster headache (eCH) (ICHD-3 code 3.1.1) and 20 age- and sex-matched healthy controls (HC). These patients were the same cohort described in our previous work [ 9 ]. All participants underwent MRI scanning during the bout period but outside of attacks. Exclusion criteria were the presence of other primary or secondary headache disorders, systemic, neurological, neuro-ophthalmological, or psychiatric diseases, and a family history of migraine in first-degree relatives. HC were free of medical illnesses and personal or family history of primary headaches or epilepsy and did not use medications habitually. All patients were also confirmed to be attack-free during the MRI session. All participants were provided with a comprehensive description of the study and provided written informed consent. The Faculty of Medicine's ethical review board at the University of Rome, Italy, approved the experiment (N° 0295/2023). MRI protocol MRI scans were acquired on a 3T scanner using a T1-weighted sagittal magnetization-prepared rapid gradient echo (MPRAGE) sequence (TR = 1900 ms, TE = 2.93 ms, 176 sagittal slices, voxel size = 0.508 × 0.508 × 1 mm³). Additional proton density and T2-weighted images were obtained with an interleaved double-echo turbo spin echo sequence (TR = 3320 ms, TE = 10/103 ms, matrix = 384 × 384, FOV = 220 mm, slice thickness = 4 mm, gap = 1.2 mm, 50 axial slices). Image processing Cortical reconstruction and volumetric segmentation were performed using FreeSurfer (version 7.4.1) following standard protocols [ 11 – 16 , 16 – 23 ]. Cortical parcellation and subcortical segmentation were based on the Desikan-Killiany atlas [ 24 ]. Default parameters values were used to process T1-weighted sequences and FWHM of 10 mm smooths partecipant’s resampled images. Quality control was performed by an experienced neuroradiologist (F.C.) who corrected segmentation errors. Statistical analysis Cortical thickness differences between eCH and HC were assessed using a two-sample t-test, adjusting for age and sex, and corrected for multiple comparisons using a false discovery rate (FDR - Bonferroni) at p < 0.05. Associations between cortical thickness and clinical variables (number of attacks, duration,of attacks, disease history, and pain intensity [VAS]) were evaluated with general linear models (GLM) controlling for age and sex, using a corrected significance threshold of p < 0.01 (FDR - Bonferroni) to compensate for multiple comparisons (number of clinical variables). Volumes of subcortical ROIs (cerebellar cortex, thalamus, caudate, putamen, pallidum, brainstem, and hippocampus) were analyzed with GLMs including age, sex, and estimated total intracranial volume (eTIV) as covariates. A p-value < 0.05 FDR corrected (Benjamini – Hochberg) was adopted for group comparisons and correlations with clinical variables. All cortical thickness analyses were conducted in FreeSurfer, and subcortical ROI analyses were performed using SPSS (version 21.0, IBM corp). Results Twenty-six patients with eCH and 20 HC were included in the analysis. Demographic and clinical data are summarized in Table 1 . There were no significant differences in age (p = 0.97) or sex distribution (p = 0.81) between the groups. Table 1 Demographic and clinical characteristics of patients with episodic cluster headache (eCH) and healthy controls (HC). Data are presented as mean ± standard deviation (SD) or absolute number. Variable eCH (n = 26) HC (n = 20) p -value Age (years, mean ± SD) 40.3 ± 10.3 40.2 ± 9.2 0.97¹ Sex (M/F) 24 / 2 19 / 1 0.81² Pain laterality (Right/Left) 15 / 11 – – Daily attack frequency 2.7 ± 2.0 – – Mean attack severity (VAS 0–10) 9.7 ± 0.7 – – Attack duration (min) 85.0 ± 55.7 – – Duration of eCH history (years) 14.3 ± 11.0 Prophylactic medications None in the 3 months prior to scanning – – ¹ Independent-samples t-test ; ² Fisher’s exact test Whole-brain cortical thickness analysis revealed two significant clusters of cortical thinning in eCH patients compared with HC (corrected p < 0.05, FDR): one in the right pars triangularis (inferior frontal gyrus, BA45) and one in the left superior frontal gyrus (Table 2 , Fig. 1 ). Table 2 Cortical thickness differences between patients with episodic cluster headache (eCH) and healthy controls (HC). Two clusters showing reduced number of vertex, i.e. cortical thinning was found in the right pars triangularis (inferior frontal gyrus, BA45) and in the superior frontal gyrus in eCH patients compared to HC. Results are corrected for multiple comparisons (corrected p < 0.05, FDR)). clusters Max (-log 10 p) Vertex max Size (mm 2 ) X (MNI) Y (MNI) Z (MNI) Num Vertex Area 1 3.1554 27020 9.86 53.4 23.0 9.0 16 Pars triangularis 2 3.2097 32330 10.69 -16.3 45.9 37.8 18 Superior frontal Significant positive associations between cortical thickness and clinical variables were observed in both hemispheres (corrected p < 0.01, FDR). In the left hemisphere, a higher number of daily attacks correlated with greater thickness in the inferior temporal cortex. Longer duration of attacks was associated with greater thickness in the postcentral cortex, whereas higher pain intensity (VAS scores) correlated with greater thickness in the superior parietal cortex (Table 3 ). In the right hemisphere, the number of attacks correlated with greater thickness in the supramarginal cortex, and longer attack duration was associated with greater thickness in the superior parietal cortex. Duration of disease history correlated with greater thickness in the inferior parietal cortex, while higher pain intensity (VAS scores) was associated with greater thickness in the lateral occipital cortex (Table 4 ). Table 3 Left hemisphere: correlations between cortical thickness and clinical variables in eCH patients (corrected p < 0.01, FDR). Significant correlations between cortical thickness and clinical variables were observed in the left inferior temporal, postcentral, and superior parietal, cortices in eCH patients. Clinical variables clusters Max (-log 10 p) Vertex max Size (mm 2 ) X (MNI) Y (MNI) Z (MNI) Num Vertex Area Daily attack frequency 1 4.0394 75452 70.49 -52.8 -32.7 -22.7 100 Inferior temporal Duration of attacks 1 3.2864 140302 16.18 -10.8 -37.4 75.1 48 Post-central VAS 1 4.0095 50161 105.13 -28.3 -56.3 56.1 256 Superior parietal Table 4 Right hemisphere: correlations between cortical thickness and clinical variables in eCH patients (corrected p < 0.01, FDR). Significant correlations between cortical thickness and clinical variables were observed in the right supramarginal, superior parietal, inferior parietal, and lateral occipital cortices in eCH patients. Clinical variables clusters Max (-log 10 p) Vertex max Size (mm 2 ) X (MNI) Y (MNI) Z (MNI) Num Vertex Area Daily attack frequency 1 4.0550 31542 41.25 53.8 -44.4 38.8 81 Supra-marginal Duration of attacks 1 3.4632 12269 16.88 14.9 -50.7 62.7 32 Superior parietal Duration of eCH history 1 3.7884 158402 34.15 43.2 -63.7 24.6 60 Inferior parietal VAS 1 4.5301 87751 109.87 45.6 -79.1 6.9 160 Lateral occipital No significant differences were detected in the volumes of the sub-cortical ROIs (cerebellar cortex, thalamus, caudate, putamen, pallidum, brainstem, and hippocampus) between eCH and HC after correction for multiple comparisons. Similarly, no significant correlations were found between subcortical volumes and clinical variables. No significant differences in cortical thickness or sub-cortical volumes were observed between patients with right-sided pain, left-sided pain, and controls, and correlation analyses restricted to each subgroup did not reveal any additional significant findings. Discussion In this study, we investigated whole-brain cortical thickness in patients with episodic cluster headache (eCH) compared with healthy controls (HC) and examined associations with clinical variables. We identified two distinct clusters of cortical thinning: one in the right pars triangularis of the inferior frontal gyrus (IFG, BA45) and a second in the left superior frontal gyrus (SFG). We also observed robust positive associations between cortical thickness and clinical burden, including attack frequency, and duration, disease duration, and pain intensity, in multimodal associative cortices of the temporal, parietal and occipital lobes. No significant subcortical volumetric alterations or correlations with clinical variables were detected. These findings add to the growing body of evidence that CH is a disorder of distributed network dysfunction rather than a focal hypothalamic pathology. Early neuroimaging studies identified the posterior hypothalamus as a key node in CH pathophysiology [ 2 ], but more recent work has demonstrated widespread alterations in cortical and subcortical regions involved in pain modulation, attention, and sensory integration [ 3 , 5 ]. Cortical abnormalities in multimodal associative regions, such as the inferior parietal lobule and supramarginal gyrus, have previously been reported in CH [ 6 , 7 ] and in other primary headaches, but their functional significance has remained unclear. Notably, no prior morphometric studies have reported alterations in the pars triangularis or the inferior frontal gyrus in CH, making the thinning observed in our cohort a novel finding. The inferior frontal gyrus, and particularly the pars triangularis (BA 45), has been consistently implicated in the decoding and integration of pain-related social signals. Functional imaging and stimulation studies show that this region is selectively engaged when perceiving others in pain and may serve to extract the meaning and salience of nociceptive stimuli, even when conveyed through non-facial sensory cues [ 25 , 26 ]. Structural alterations in this region, as observed in our study, may thus reflect a disrupted capacity to process pain-related contextual information, potentially contributing to dysfunctional salience attribution and impaired integration within pain empathy or regulation networks. In addition, the cortical thinning we observed in the superior frontal gyrus (SFG) is consistent with prior VBM and SBM studies in CH that have reported structural alterations in the dorsolateral prefrontal cortex, which overlaps with the SFG [ 27 , 28 ]. The SFG, particularly its medial subdivision within the prefrontal cortex, plays a central role in executive control and pain modulation through its connections with the cingulate cortex, thalamus, and hypothalamus. Recent studies in cluster headache patients have identified altered functional activity in this region, supporting its involvement in disrupted top-down modulation of pain and reward processing [ 29 ]. Beyond these frontal clusters, we observed significant positive correlations between cortical thickness and clinical variables in associative cortices, including the inferior temporal, postcentral, superior parietal, supramarginal, inferior parietal, and lateral occipital regions. This pattern indicates that patients with greater disease burden exhibit thicker cortex in these areas. The involvement of these associative cortices is consistent with their known role in sensory integration, attentional processing, and higher-order modulation of pain. Parietal and occipital areas—particularly the superior and inferior parietal lobules and lateral occipital cortex—have been implicated in the spatial localization and cognitive appraisal of painful stimuli, while the inferior temporal cortex may contribute to the contextual decoding and memory-based evaluation of pain. These regions are frequently engaged in attentional and perceptual networks activated during nociceptive processing and may undergo structural remodeling as part of an adaptive response to repeated noxious input [ 30 – 32 ]. Notably, several of these correlations emerged in areas that did not differ between patients and controls at the group level. Similar associations have been reported in prior studies. Seifert et al. [ 33 ] described a positive correlation between cortical thickness in the primary somatosensory cortex and disease duration in eCH, despite the absence of significant differences in group comparisons. These observations support the view that some morphometric changes in CH may reflect progressive, compensatory, or plastic mechanisms related to clinical burden rather than fixed structural abnormalities. The interpretation of these correlations is complex. One possibility is that the observed cortical thickening reflects activity-dependent plasticity induced by repeated nociceptive inputs, as previously described in other chronic pain disorders [ 34 , 35 ]. In this framework, associative cortices may undergo adaptive or maladaptive structural remodeling in response to the cumulative clinical burden. Alternatively, these findings could represent state-dependent fluctuations in cortical morphology that are not captured by group-level comparisons. As May [ 36 ] highlighted, morphometric changes in headache disorders should be interpreted with caution: they may reflect reversible and fluctuating processes related to attack frequency and disease chronicity rather than permanent neuronal loss. Taken together, our results support a two-level model of cortical alterations in eCH. The cortical thinning observed in the pars triangularis and SFG likely represents a stable trait-like abnormality affecting frontal-executive hubs involved in pain modulation and salience processing. In parallel, cortical thickness increases in associative parietal and occipital regions appear to track the clinical burden and may represent a form of dynamic plasticity in response to repeated attacks. This interpretation is consistent with our previous findings in the same cohort, which showed preserved hypothalamic macrostructure but microstructural alterations and dysfunctional connectivity between the hypothalamus, thalamus, and cortical salience and executive control networks [ 4 , 9 ]. Our findings extend the evidence that CH is a network-level disorder involving both frontal trait abnormalities and burden-related plastic changes in distributed cortical networks. The identification of frontal cortical thinning in the pars triangularis and SFG highlights the potential role of executive control dysfunction in CH pathophysiology, while the burden-related correlations in associative cortices underscore the dynamic and potentially reversible nature of cortical remodeling in response to clinical disease load. Longitudinal multimodal imaging studies are needed to determine whether these cortical alterations normalize after remission or treatment and to clarify their relationship with functional network dynamics. Limitations This study has several limitations. First, the relatively small sample size may have reduced the statistical power to detect subtle cortical and subcortical alterations, particularly in regions with high interindividual variability. Second, the cross-sectional design does not allow us to establish causal relationships or to determine whether the observed cortical abnormalities are reversible with treatment or represent stable disease-related traits. Third, although all patients were scanned during the bout period but outside attacks, we cannot completely exclude the influence of ictal or peri-ictal state-related factors on cortical thickness measurements. Fourth, we did not stratify the analyses according to the side of pain in the main comparisons. Exploratory subgroup analyses comparing patients with right-sided versus left-sided pain, as well as each subgroup versus controls, revealed no significant differences, and correlation analyses restricted to each subgroup did not reveal additional significant findings. Finally, we focused primarily on cortical thickness and volumetric macrostructural measures, which may be less sensitive to subtle microstructural or functional alterations detectable with diffusion MRI or resting-state functional connectivity analyses [ 4 , 36 ]. Conclusions In conclusion, we demonstrated significant cortical thinning in the right pars triangularis and left superior frontal gyrus, together with positive, disease burden–related cortical thickness increases in multimodal associative cortices in patients with eCH. These findings extend previous work in the same cohort showing preserved hypothalamic macrostructure but microstructural abnormalities and dysfunctional connectivity in hypothalamic–thalamic–cortical networks [ 4 , 9 ]. The observation that cortical thickness in associative and sensory cortices correlates positively with clinical variables suggests that these areas may undergo activity-dependent structural remodeling in response to recurrent attacks. Our results support the view that CH is a network-level disorder involving distributed cortical and subcortical hubs rather than a focal hypothalamic abnormality. The identification of frontal cortical hubs as potential trait markers and the observation that associative cortical thickening parallels clinical burden may help guide future efforts to identify neuroimaging biomarkers predictive of disease progression and treatment response. Future longitudinal studies in larger cohorts, ideally distinguishing between episodic and chronic CH and accounting for pain laterality, are warranted to further elucidate the pathophysiological mechanisms underlying CH and to identify novel therapeutic targets. Declarations Ethics approval and consent to participate: The study was approved by the Ethics Committee of the Policlinico Umberto I – University Sapienza of Rome in accordance with the ethical principles of the Declaration of Helsinki (N° 0295/2023). Consent for publication: All authors consent for the publication. Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare no competing interests. Funding: Not applicable Authors' contributions: FCar, AdR and GC conceived and designed the study. 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Cephalalgia 45:03331024251341204. https://doi.org/10.1177/03331024251341204 May A (2009) Morphing voxels: the hype around structural imaging of headache patients. Brain 132:1419–1425. https://doi.org/10.1093/brain/awp116 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7328382","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":501971761,"identity":"289b5d17-7b40-495f-be72-2c0c47b58790","order_by":0,"name":"Francesca Caramia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABHUlEQVRIie3OMWvCQBjG8fcIJMtLsyakmK+QUIgUBD9Il5symVUySDgRnKSzXdqvUJdMHQ4OdAl0rdyiFJw6CAWJizSNhYK5dO5w/+l44Md7ADrdP8xiFwPWE/1+GgBcQfByxHqqiVURhWkQAIf+PGxQnkFP7DZlmvk2M7af6Si/th8+os32pXdnT4CIvYJcxd1wVohwzs0bt1hKdOSgG9BdnMyF+mN9hMgjU06BI7jMlAhyEDmUi4S1EETr4JFTRn2OxpGdJPrr4kyeWglWV5hBA46mO55KDN7wTJ7bydCdLUW4EGZ0O76XGBbxsCJxshCE8UL5sdwpR5nfWU3e1+wg+52VyN2S95LHVyH2aZP8ZjQnwv4COp1Op2vvCwQ0a4E9j3wMAAAAAElFTkSuQmCC","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":true,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Caramia","suffix":""},{"id":501971762,"identity":"dac84fa3-d2fb-4c5e-8293-29909e6aaed7","order_by":1,"name":"Antonio Renzo","email":"","orcid":"","institution":"IRCCS – Fondazione Bietti, Rare Diseases of the Eye","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"","lastName":"Renzo","suffix":""},{"id":501971763,"identity":"1d1c8417-442f-4351-8bc3-692eb0307298","order_by":2,"name":"Irene Giardina","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Irene","middleName":"","lastName":"Giardina","suffix":""},{"id":501971764,"identity":"df936c22-99c6-45bb-814a-15cfcaadb9d4","order_by":3,"name":"Davide Chiffi","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Davide","middleName":"","lastName":"Chiffi","suffix":""},{"id":501971765,"identity":"88f4a09d-a271-4f63-a580-185d6a28d40a","order_by":4,"name":"Giada Giuliani","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Giada","middleName":"","lastName":"Giuliani","suffix":""},{"id":501971766,"identity":"507119f7-ee78-4e7d-8a73-097c33f8a039","order_by":5,"name":"Gabriele Sebastianelli","email":"","orcid":"","institution":"Sapienza University of Rome Polo Pontino ICOT","correspondingAuthor":false,"prefix":"","firstName":"Gabriele","middleName":"","lastName":"Sebastianelli","suffix":""},{"id":501971767,"identity":"6f2a4460-03b7-42e4-897a-5fcef8f8bf1a","order_by":6,"name":"Francesco Casillo","email":"","orcid":"","institution":"Sapienza University of Rome Polo Pontino ICOT","correspondingAuthor":false,"prefix":"","firstName":"Francesco","middleName":"","lastName":"Casillo","suffix":""},{"id":501971768,"identity":"38baadc2-8cba-4074-9fbe-b49620b8c9b5","order_by":7,"name":"Chiara Abagnale","email":"","orcid":"","institution":"Sapienza University of Rome Polo Pontino ICOT","correspondingAuthor":false,"prefix":"","firstName":"Chiara","middleName":"","lastName":"Abagnale","suffix":""},{"id":501971769,"identity":"b4b5c86a-d64e-4f69-84d6-5d24625bc927","order_by":8,"name":"Francesca Conti","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Conti","suffix":""},{"id":501971770,"identity":"0f322def-cac8-4f0b-b809-17ffe6287635","order_by":9,"name":"Francesca Lafavia","email":"","orcid":"","institution":"Policlinico Umberto I","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Lafavia","suffix":""},{"id":501971771,"identity":"7c11c307-ffed-4e9e-908a-2d575f973ec5","order_by":10,"name":"Marta Altieri","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Altieri","suffix":""},{"id":501971773,"identity":"b8cff0d1-ee70-42cf-876e-cee0cf469556","order_by":11,"name":"Vittorio Piero","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Vittorio","middleName":"","lastName":"Piero","suffix":""},{"id":501971774,"identity":"680f67c3-db58-4731-a3f6-2cd5602aca25","order_by":12,"name":"Gianluca Coppola","email":"","orcid":"","institution":"Sapienza University of Rome Polo Pontino ICOT","correspondingAuthor":false,"prefix":"","firstName":"Gianluca","middleName":"","lastName":"Coppola","suffix":""}],"badges":[],"createdAt":"2025-08-08 14:53:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7328382/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7328382/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89384821,"identity":"924d9fc3-6deb-467f-b2f2-e48a345c7b25","added_by":"auto","created_at":"2025-08-19 12:26:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":370229,"visible":true,"origin":"","legend":"\u003cp\u003eCortical map of cortical thickness differences between patients with episodic cluster headache (eCH) and healthy controls (HC). Vertex-wise analysis revealed a significant cluster of cortical thinning in the right pars triangularis (inferior frontal gyrus, BA45, A), and one in the left superior frontal gyrus (B) in eCH patients compared with HC (corrected \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, FDR). Clusters are displayed on an inflated template surface in MNI space (lateral view and frontal view).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7328382/v1/401b5e7bf36f1db9d34dff8b.jpeg"},{"id":89952142,"identity":"f8208fe8-1037-4e2a-bbd8-e73ccfca970d","added_by":"auto","created_at":"2025-08-26 19:46:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1162312,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7328382/v1/7a9db638-a010-4098-81aa-012894d97932.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Frontal cortical thinning and disease burden–related plasticity in episodic cluster headache: a whole-brain cortical and subcortical morphometry study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCluster headache (CH) is the most common trigeminal autonomic cephalalgia, a primary headache disorder characterized by recurrent attacks of excruciating unilateral pain associated with ipsilateral cranial autonomic symptoms and circadian rhythmicity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although the posterior hypothalamus was initially identified as the main hub in CH pathophysiology based on early positron emission tomography studies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], increasing evidence indicates that CH is a network-level disorder involving the trigeminovascular system, hypothalamus, thalamus, and higher-order cortical and subcortical areas [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdvanced neuroimaging techniques have revealed widespread structural and functional brain alterations in CH patients. Resting-state fMRI and diffusion tensor imaging (DTI) studies have demonstrated abnormal connectivity between the hypothalamus, the salience network, and executive control networks, as well as microstructural alterations in the hypothalamus and thalamus, even during headache-free periods [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Morphometric studies using voxel-based morphometry (VBM) or surface-based morphometry (SBM) have reported inconsistent findings, with some authors describing hypothalamic hypertrophy or cortical thinning in frontal, temporal, and parietal cortices [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], while others did not detect macrostructural differences [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Methodological differences, including patient selection (episodic vs chronic CH), timing of scanning (in- vs out-of-bout), and prophylactic medication use, may explain these discrepancies.\u003c/p\u003e\u003cp\u003eOur group recently demonstrated that hypothalamic macrostructure is preserved in episodic CH (eCH) patients scanned during the in-bout period [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], while the same cohort exhibited hypothalamic and thalamic microstructural abnormalities and dysfunctional connectivity between cortical networks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These findings suggest that structural alterations may preferentially affect distributed cortical and subcortical networks rather than being confined to the hypothalamus.\u003c/p\u003e\u003cp\u003eGiven these observations, we sought to further investigate whole-brain cortical thickness differences in the same cohort of eCH patients and matched healthy controls. In addition, we examined the relationship between cortical thickness and clinical variables, including disease duration, attack frequency, and pain intensity. We hypothesized that cortical alterations would involve multimodal associative regions and that their severity would correlate with clinical burden, thereby extending previous evidence of network-level dysfunction in CH. We also evaluated subcortical volumetric differences and their relationship with clinical burden.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study included 26 patients with episodic cluster headache (eCH) (ICHD-3 code 3.1.1) and 20 age- and sex-matched healthy controls (HC). These patients were the same cohort described in our previous work [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. All participants underwent MRI scanning during the bout period but outside of attacks. Exclusion criteria were the presence of other primary or secondary headache disorders, systemic, neurological, neuro-ophthalmological, or psychiatric diseases, and a family history of migraine in first-degree relatives. HC were free of medical illnesses and personal or family history of primary headaches or epilepsy and did not use medications habitually.\u003c/p\u003e\u003cp\u003eAll patients were also confirmed to be attack-free during the MRI session.\u003c/p\u003e\u003cp\u003e All participants were provided with a comprehensive description of the study and provided written informed consent. The Faculty of Medicine's ethical review board at the University of Rome, Italy, approved the experiment (N\u0026deg; 0295/2023).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMRI protocol\u003c/h2\u003e\u003cp\u003eMRI scans were acquired on a 3T scanner using a T1-weighted sagittal magnetization-prepared rapid gradient echo (MPRAGE) sequence (TR\u0026thinsp;=\u0026thinsp;1900 ms, TE\u0026thinsp;=\u0026thinsp;2.93 ms, 176 sagittal slices, voxel size\u0026thinsp;=\u0026thinsp;0.508 \u0026times; 0.508 \u0026times; 1 mm\u0026sup3;). Additional proton density and T2-weighted images were obtained with an interleaved double-echo turbo spin echo sequence (TR\u0026thinsp;=\u0026thinsp;3320 ms, TE\u0026thinsp;=\u0026thinsp;10/103 ms, matrix\u0026thinsp;=\u0026thinsp;384 \u0026times; 384, FOV\u0026thinsp;=\u0026thinsp;220 mm, slice thickness\u0026thinsp;=\u0026thinsp;4 mm, gap\u0026thinsp;=\u0026thinsp;1.2 mm, 50 axial slices).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImage processing\u003c/h3\u003e\n\u003cp\u003eCortical reconstruction and volumetric segmentation were performed using FreeSurfer (version 7.4.1) following standard protocols [\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20 CR21 CR22\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Cortical parcellation and subcortical segmentation were based on the Desikan-Killiany atlas [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Default parameters values were used to process T1-weighted sequences and FWHM of 10 mm smooths partecipant\u0026rsquo;s resampled images. Quality control was performed by an experienced neuroradiologist (F.C.) who corrected segmentation errors.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eCortical thickness differences between eCH and HC were assessed using a two-sample t-test, adjusting for age and sex, and corrected for multiple comparisons using a false discovery rate (FDR - Bonferroni) at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Associations between cortical thickness and clinical variables (number of attacks, duration,of attacks, disease history, and pain intensity [VAS]) were evaluated with general linear models (GLM) controlling for age and sex, using a corrected significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (FDR - Bonferroni) to compensate for multiple comparisons (number of clinical variables). Volumes of subcortical ROIs (cerebellar cortex, thalamus, caudate, putamen, pallidum, brainstem, and hippocampus) were analyzed with GLMs including age, sex, and estimated total intracranial volume (eTIV) as covariates. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 FDR corrected (Benjamini \u0026ndash; Hochberg) was adopted for group comparisons and correlations with clinical variables. All cortical thickness analyses were conducted in FreeSurfer, and subcortical ROI analyses were performed using SPSS (version 21.0, IBM corp).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTwenty-six patients with eCH and 20 HC were included in the analysis. Demographic and clinical data are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no significant differences in age (p\u0026thinsp;=\u0026thinsp;0.97) or sex distribution (p\u0026thinsp;=\u0026thinsp;0.81) between the groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic and clinical characteristics of patients with episodic cluster headache (eCH) and healthy controls (HC). Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or absolute number.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eeCH (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHC (n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97\u0026sup1;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex (M/F)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 / 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 / 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.81\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePain laterality (Right/Left)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 / 11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDaily attack frequency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMean attack severity (VAS 0\u0026ndash;10)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAttack duration (min)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.0\u0026thinsp;\u0026plusmn;\u0026thinsp;55.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration of eCH history (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eProphylactic medications\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone in the 3 months prior to scanning\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u0026sup1; \u003cb\u003eIndependent-samples t-test\u003c/b\u003e; \u0026sup2; \u003cb\u003eFisher\u0026rsquo;s exact test\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhole-brain cortical thickness analysis revealed two significant clusters of cortical thinning in eCH patients compared with HC (corrected p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, FDR): one in the right pars triangularis (inferior frontal gyrus, BA45) and one in the left superior frontal gyrus (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCortical thickness differences between patients with episodic cluster headache (eCH) and healthy controls (HC). Two clusters showing reduced number of vertex, i.e. cortical thinning was found in the right pars triangularis (inferior frontal gyrus, BA45) and in the superior frontal gyrus in eCH patients compared to HC. Results are corrected for multiple comparisons (corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, FDR)).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eclusters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003cp\u003e(-log\u003csub\u003e10\u003c/sub\u003e p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVertex\u003c/p\u003e\u003cp\u003emax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSize\u003c/p\u003e\u003cp\u003e(mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eX\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eY\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNum\u003c/p\u003e\u003cp\u003eVertex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eArea\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.1554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e53.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e23.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e9.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ePars triangularis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.2097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32330\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-16.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e45.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e37.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eSuperior frontal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSignificant positive associations between cortical thickness and clinical variables were observed in both hemispheres (corrected p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, FDR). In the left hemisphere, a higher number of daily attacks correlated with greater thickness in the inferior temporal cortex. Longer duration of attacks was associated with greater thickness in the postcentral cortex, whereas higher pain intensity (VAS scores) correlated with greater thickness in the superior parietal cortex (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the right hemisphere, the number of attacks correlated with greater thickness in the supramarginal cortex, and longer attack duration was associated with greater thickness in the superior parietal cortex. Duration of disease history correlated with greater thickness in the inferior parietal cortex, while higher pain intensity (VAS scores) was associated with greater thickness in the lateral occipital cortex (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLeft hemisphere: correlations between cortical thickness and clinical variables in eCH patients (corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, FDR). Significant correlations between cortical thickness and clinical variables were observed in the left inferior temporal, postcentral, and superior parietal, cortices in eCH patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eclusters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003cp\u003e(-log\u003csub\u003e10\u003c/sub\u003e p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVertex\u003c/p\u003e\u003cp\u003emax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSize\u003c/p\u003e\u003cp\u003e(mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eX\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eY\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNum\u003c/p\u003e\u003cp\u003eVertex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eArea\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDaily attack frequency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.0394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75452\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e70.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-52.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-32.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-22.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInferior temporal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eof attacks\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.2864\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e140302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e16.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-37.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e75.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003ePost-central\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVAS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.0095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e105.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-28.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-56.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e56.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSuperior parietal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRight hemisphere: correlations between cortical thickness and clinical variables in eCH patients (corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, FDR). Significant correlations between cortical thickness and clinical variables were observed in the right supramarginal, superior parietal, inferior parietal, and lateral occipital cortices in eCH patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eclusters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003cp\u003e(-log\u003csub\u003e10\u003c/sub\u003e p)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVertex\u003c/p\u003e\u003cp\u003emax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSize\u003c/p\u003e\u003cp\u003e(mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eX\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eY\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003cp\u003e(MNI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNum\u003c/p\u003e\u003cp\u003eVertex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eArea\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDaily attack frequency\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.0550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e31542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e41.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e53.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-44.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e38.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSupra-marginal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eof attacks\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.4632\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e16.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-50.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e62.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eSuperior parietal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration of eCH history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.7884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e158402\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e34.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e43.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-63.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e24.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eInferior parietal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVAS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.5301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e87751\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e109.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e45.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-79.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLateral occipital\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNo significant differences were detected in the volumes of the sub-cortical ROIs (cerebellar cortex, thalamus, caudate, putamen, pallidum, brainstem, and hippocampus) between eCH and HC after correction for multiple comparisons. Similarly, no significant correlations were found between subcortical volumes and clinical variables.\u003c/p\u003e\u003cp\u003eNo significant differences in cortical thickness or sub-cortical volumes were observed between patients with right-sided pain, left-sided pain, and controls, and correlation analyses restricted to each subgroup did not reveal any additional significant findings.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated whole-brain cortical thickness in patients with episodic cluster headache (eCH) compared with healthy controls (HC) and examined associations with clinical variables. We identified two distinct clusters of cortical thinning: one in the right pars triangularis of the inferior frontal gyrus (IFG, BA45) and a second in the left superior frontal gyrus (SFG). We also observed robust positive associations between cortical thickness and clinical burden, including attack frequency, and duration, disease duration, and pain intensity, in multimodal associative cortices of the temporal, parietal and occipital lobes. No significant subcortical volumetric alterations or correlations with clinical variables were detected.\u003c/p\u003e\u003cp\u003eThese findings add to the growing body of evidence that CH is a disorder of distributed network dysfunction rather than a focal hypothalamic pathology. Early neuroimaging studies identified the posterior hypothalamus as a key node in CH pathophysiology [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], but more recent work has demonstrated widespread alterations in cortical and subcortical regions involved in pain modulation, attention, and sensory integration [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Cortical abnormalities in multimodal associative regions, such as the inferior parietal lobule and supramarginal gyrus, have previously been reported in CH [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and in other primary headaches, but their functional significance has remained unclear.\u003c/p\u003e\u003cp\u003eNotably, no prior morphometric studies have reported alterations in the pars triangularis or the inferior frontal gyrus in CH, making the thinning observed in our cohort a novel finding. The inferior frontal gyrus, and particularly the pars triangularis (BA 45), has been consistently implicated in the decoding and integration of pain-related social signals. Functional imaging and stimulation studies show that this region is selectively engaged when perceiving others in pain and may serve to extract the meaning and salience of nociceptive stimuli, even when conveyed through non-facial sensory cues [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Structural alterations in this region, as observed in our study, may thus reflect a disrupted capacity to process pain-related contextual information, potentially contributing to dysfunctional salience attribution and impaired integration within pain empathy or regulation networks.\u003c/p\u003e\u003cp\u003eIn addition, the cortical thinning we observed in the superior frontal gyrus (SFG) is consistent with prior VBM and SBM studies in CH that have reported structural alterations in the dorsolateral prefrontal cortex, which overlaps with the SFG [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The SFG, particularly its medial subdivision within the prefrontal cortex, plays a central role in executive control and pain modulation through its connections with the cingulate cortex, thalamus, and hypothalamus. Recent studies in cluster headache patients have identified altered functional activity in this region, supporting its involvement in disrupted top-down modulation of pain and reward processing [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Beyond these frontal clusters, we observed significant positive correlations between cortical thickness and clinical variables in associative cortices, including the inferior temporal, postcentral, superior parietal, supramarginal, inferior parietal, and lateral occipital regions. This pattern indicates that patients with greater disease burden exhibit thicker cortex in these areas. The involvement of these associative cortices is consistent with their known role in sensory integration, attentional processing, and higher-order modulation of pain. Parietal and occipital areas\u0026mdash;particularly the superior and inferior parietal lobules and lateral occipital cortex\u0026mdash;have been implicated in the spatial localization and cognitive appraisal of painful stimuli, while the inferior temporal cortex may contribute to the contextual decoding and memory-based evaluation of pain. These regions are frequently engaged in attentional and perceptual networks activated during nociceptive processing and may undergo structural remodeling as part of an adaptive response to repeated noxious input [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Notably, several of these correlations emerged in areas that did not differ between patients and controls at the group level. Similar associations have been reported in prior studies. Seifert et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] described a positive correlation between cortical thickness in the primary somatosensory cortex and disease duration in eCH, despite the absence of significant differences in group comparisons. These observations support the view that some morphometric changes in CH may reflect progressive, compensatory, or plastic mechanisms related to clinical burden rather than fixed structural abnormalities.\u003c/p\u003e\u003cp\u003eThe interpretation of these correlations is complex. One possibility is that the observed cortical thickening reflects activity-dependent plasticity induced by repeated nociceptive inputs, as previously described in other chronic pain disorders [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this framework, associative cortices may undergo adaptive or maladaptive structural remodeling in response to the cumulative clinical burden. Alternatively, these findings could represent state-dependent fluctuations in cortical morphology that are not captured by group-level comparisons.\u003c/p\u003e\u003cp\u003eAs May [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] highlighted, morphometric changes in headache disorders should be interpreted with caution: they may reflect reversible and fluctuating processes related to attack frequency and disease chronicity rather than permanent neuronal loss.\u003c/p\u003e\u003cp\u003eTaken together, our results support a two-level model of cortical alterations in eCH. The cortical thinning observed in the pars triangularis and SFG likely represents a stable trait-like abnormality affecting frontal-executive hubs involved in pain modulation and salience processing. In parallel, cortical thickness increases in associative parietal and occipital regions appear to track the clinical burden and may represent a form of dynamic plasticity in response to repeated attacks. This interpretation is consistent with our previous findings in the same cohort, which showed preserved hypothalamic macrostructure but microstructural alterations and dysfunctional connectivity between the hypothalamus, thalamus, and cortical salience and executive control networks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur findings extend the evidence that CH is a network-level disorder involving both frontal trait abnormalities and burden-related plastic changes in distributed cortical networks. The identification of frontal cortical thinning in the pars triangularis and SFG highlights the potential role of executive control dysfunction in CH pathophysiology, while the burden-related correlations in associative cortices underscore the dynamic and potentially reversible nature of cortical remodeling in response to clinical disease load. Longitudinal multimodal imaging studies are needed to determine whether these cortical alterations normalize after remission or treatment and to clarify their relationship with functional network dynamics.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has several limitations. First, the relatively small sample size may have reduced the statistical power to detect subtle cortical and subcortical alterations, particularly in regions with high interindividual variability. Second, the cross-sectional design does not allow us to establish causal relationships or to determine whether the observed cortical abnormalities are reversible with treatment or represent stable disease-related traits. Third, although all patients were scanned during the bout period but outside attacks, we cannot completely exclude the influence of ictal or peri-ictal state-related factors on cortical thickness measurements. Fourth, we did not stratify the analyses according to the side of pain in the main comparisons. Exploratory subgroup analyses comparing patients with right-sided versus left-sided pain, as well as each subgroup versus controls, revealed no significant differences, and correlation analyses restricted to each subgroup did not reveal additional significant findings. Finally, we focused primarily on cortical thickness and volumetric macrostructural measures, which may be less sensitive to subtle microstructural or functional alterations detectable with diffusion MRI or resting-state functional connectivity analyses [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, we demonstrated significant cortical thinning in the right pars triangularis and left superior frontal gyrus, together with positive, disease burden\u0026ndash;related cortical thickness increases in multimodal associative cortices in patients with eCH. These findings extend previous work in the same cohort showing preserved hypothalamic macrostructure but microstructural abnormalities and dysfunctional connectivity in hypothalamic\u0026ndash;thalamic\u0026ndash;cortical networks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The observation that cortical thickness in associative and sensory cortices correlates positively with clinical variables suggests that these areas may undergo activity-dependent structural remodeling in response to recurrent attacks.\u003c/p\u003e\u003cp\u003eOur results support the view that CH is a network-level disorder involving distributed cortical and subcortical hubs rather than a focal hypothalamic abnormality. The identification of frontal cortical hubs as potential trait markers and the observation that associative cortical thickening parallels clinical burden may help guide future efforts to identify neuroimaging biomarkers predictive of disease progression and treatment response. Future longitudinal studies in larger cohorts, ideally distinguishing between episodic and chronic CH and accounting for pain laterality, are warranted to further elucidate the pathophysiological mechanisms underlying CH and to identify novel therapeutic targets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: The study was approved by the Ethics Committee of the Policlinico Umberto I \u0026ndash; University Sapienza of Rome in accordance with the ethical principles of the Declaration of Helsinki (N\u0026deg; 0295/2023).\u003c/p\u003e\n\u003cp\u003eConsent for publication: All authors consent for the publication.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding: Not applicable\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions: FCar, AdR and GC conceived and designed the study. FCar, IG, FCo, FL, DC, GG, GS, FCas, CA, MA and VdP contributed to data acquisition, analysis, and interpretation. AdR performed the MRI morphometric analysis. FC, AdR, and GC drafted the manuscript. All authors substantially revised the work and approved the final submitted version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWei DY, Goadsby PJ (2021) Cluster headache pathophysiology \u0026mdash; insights from current and emerging treatments. Nat Rev Neurol 17:308\u0026ndash;324. https://doi.org/10.1038/s41582-021-00477-w\u003c/li\u003e\n\u003cli\u003eMay A, Bahra A, B\u0026uuml;chel C, Frackowiak RS, Goadsby PJ (1998) Hypothalamic activation in cluster headache attacks. The Lancet 352:275\u0026ndash;278. https://doi.org/10.1016/S0140-6736(98)02470-2\u003c/li\u003e\n\u003cli\u003eCoppola G, Abagnale C, Sebastianelli G, Goadsby PJ (2024) Pathophysiology of cluster headache: From the trigeminovascular system to the cerebral networks. Cephalalgia 44:03331024231209317. https://doi.org/10.1177/03331024231209317\u003c/li\u003e\n\u003cli\u003eAbagnale C, Di Renzo A, Giuliani G, Sebastianelli G, Casillo F, Ziccardi L, Parisi V, Di Lorenzo C, Serrao M, Caramia F, Di Piero V, Coppola G (2025) MRI-based analysis of the microstructure of the thalamus and hypothalamus and functional connectivity between cortical networks in episodic cluster headache. J Headache Pain 26:12. https://doi.org/10.1186/s10194-024-01920-1\u003c/li\u003e\n\u003cli\u003eMessina R, Filippi M (2020) What We Gain From Machine Learning Studies in Headache Patients. Front Neurol 11:221. https://doi.org/10.3389/fneur.2020.00221\u003c/li\u003e\n\u003cli\u003eAbsinta M, Rocca MA, Colombo B, Falini A, Comi G, Filippi M (2012) Selective decreased grey matter volume of the pain-matrix network in cluster headache. 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Cephalalgia 38:662\u0026ndash;673. https://doi.org/10.1177/0333102417703762\u003c/li\u003e\n\u003cli\u003eChiffi D, Di Renzo A, Giuliani G, Abagnale C, Altieri M, Sebastianelli G, Casillo F, Di Piero V, Coppola G, Caramia F (2025) Assessment of hypothalamic macrostructure in episodic cluster headache: a volumetric segmentation MRI study. Radiol Med (Torino). https://doi.org/10.1007/s11547-025-02041-8\u003c/li\u003e\n\u003cli\u003eLee DA, Lee H-J, Kim HC, Park KM (2022) Alterations of the structural covariance network in the hypothalamus of patients with cluster headache. J Neurol 269:316\u0026ndash;322. https://doi.org/10.1007/s00415-021-10629-z\u003c/li\u003e\n\u003cli\u003eDale AM, Fischl B, Sereno MI (1999) Cortical Surface-Based Analysis. 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Brain 132:1419\u0026ndash;1425. https://doi.org/10.1093/brain/awp116\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cluster headache, cortical thickness, frontal cortex, plasticity, MRI","lastPublishedDoi":"10.21203/rs.3.rs-7328382/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7328382/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCluster headache (CH) is a primary headache disorder characterized by severe unilateral pain and cranial autonomic symptoms. Although the posterior hypothalamus has been implicated as a key structure in CH pathophysiology, evidence suggests that this disorder involves widespread alterations in cortical and subcortical networks. This study investigated whole-brain cortical thickness and subcortical volumetric differences in patients with episodic CH (eCH) compared with healthy controls (HC) and examined associations with clinical burden.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eTwenty-six patients with eCH and 20 age- and sex-matched HC underwent 3T MRI scanning during the bout period but outside attacks. Cortical thickness and subcortical volumes were analyzed using FreeSurfer. Group differences were tested with FDR-corrected vertex-wise and ROI-based analyses. Associations between cortical thickness, sub-cortical volumes, and clinical variables (attack frequency and duration, disease duration, and pain intensity) were evaluated using general linear models adjusted for age and sex.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eCompared with HC, patients with eCH exhibited significant cortical thinning in two clusters: the right pars triangularis (inferior frontal gyrus, BA45) and the left superior frontal gyrus (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, FDR-corrected). Positive correlations between cortical thickness and clinical burden were observed in multimodal associative cortices, including inferior temporal, postcentral, superior parietal, supramarginal, inferior parietal, and lateral occipital regions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, FDR-corrected). No significant subcortical volumetric alterations or correlations with clinical variables were detected.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur findings demonstrate frontal cortical thinning and disease burden\u0026ndash;related cortical thickness increases in associative temporal, parietal and occipital cortices in eCH, supporting a two-level model of cortical alterations. Frontal cortical thinning may represent a trait-like abnormality affecting executive control hubs, whereas cortical thickening in associative regions may reflect dynamic plasticity in response to clinical burden. These results extend the evidence that CH is a network-level disorder and highlight the potential for cortical thickness measures to serve as neuroimaging biomarkers of disease progression.\u003c/p\u003e","manuscriptTitle":"Frontal cortical thinning and disease burden–related plasticity in episodic cluster headache: a whole-brain cortical and subcortical morphometry study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 12:26:38","doi":"10.21203/rs.3.rs-7328382/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c4be9ab-ee56-4a86-b4a7-73e8fa2828e1","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-26T19:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 12:26:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7328382","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7328382","identity":"rs-7328382","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}