MétaCan
Menu
Back to cohort
Record W4324373902 · doi:10.3389/fnins.2023.1139086

Altered cerebral neurovascular coupling in medication-overuse headache: A study combining multi-modal resting-state fMRI with 3D PCASL

2023· article· en· W4324373902 on OpenAlexaboutno aff
Xin Li, Mengqi Liu, Wenping Fan, Huan Xu, Zhiye Chen

Bibliographic record

VenueFrontiers in Neuroscience · 2023
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsResting state fMRINeurovascular bundleMedicineNeuroscienceTriptansCardiologyPhysical medicine and rehabilitationInternal medicinePsychologyMigraineAnatomy

Abstract

fetched live from OpenAlex

Aim Structural and functional changes in the brain have been identified in individuals with medication-overuse headache (MOH) using MRI. However, it has not been clearly established whether neurovascular dysfunction occurs in MOH, which could be elucidated by examining neurovascular coupling (NVC) from the viewpoints of neuronal activity and cerebral blood flow. The aim of this study was to investigate potential alterations in NVC function of the brain in individuals with MOH using resting-state functional MRI (rs-fMRI) and 3D pseudo-continuous arterial spin labeling (3D PCASL) imaging techniques. Methods A total of 40 patients with MOH and 32 normal controls (NCs) were recruited, and rs-fMRI and 3D PCASL data were obtained using a 3.0 T MR scanner. Standard preprocessing of the rs-fMRI data was performed to generate images representing regional homogeneity (ReHo), fractional amplitude of low-frequency fluctuation (fALFF), and degree centrality (DC); cerebral blood flow (CBF) images were generated using 3D PCASL sequence data. These functional maps were all normalized into Montreal Neurological Institute (MNI) space, and NVC was subsequently determined on the basis of Pearson correlation coefficients between the rs-fMRI maps (ReHo, fALFF, and DC) and CBF maps. The statistical significance of differences between the MOH and NC groups in terms of NVC in different brain regions was established via Z-test. Further analysis was performed to examine correlations between NVC in the brain regions with NVC dysfunction and clinical variables among patients with MOH. Results NVC mainly presented a negative correlation in patients with MOH and NCs. No significant difference between the two groups was detected in terms of average NVC over the entire gray matter area. However, several brain regions with significantly decreased NVC in patients with MOH compared to NCs were identified: the left orbital region of the superior frontal gyrus, the bilateral gyrus rectus, and the olfactory cortex (P < 0.05). A correlation analysis revealed that the DC of the brain regions with NVC dysfunction was significantly positively correlated with disease duration (r = 0.323, P = 0.042), and DC–CBF connectivity was negatively correlated with VAS score (r = −0.424, P = 0.035). Conclusion The current study demonstrated that cerebral NVC dysfunction occurs in patients with MOH, and the NVC technique could function as a new imaging biomarker in headache research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.309
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeuroscienceSame topicMigraine and Headache StudiesFrench-language works237,207