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. 2019 Jun;16(6):407-417.
doi: 10.30773/pi.2019.04.11. Epub 2019 Jun 25.

Diagnostic Neuroimaging in Headache Patients: A Systematic Review and Meta-Analysis

Ye Eun Jang  1 , Eun Young Cho  2 , Hee Yea Choi  1 , Sun Mi Kim  3 , Hye Youn Park  1
Affiliations

Diagnostic Neuroimaging in Headache Patients: A Systematic Review and Meta-Analysis

Ye Eun Jang et al. Psychiatry Investig. 2019 Jun.

Abstract

Objective: Neuroimaging in headache patients identifies clinically significant neurological abnormalities and plays an important role in excluding secondary headache diagnoses. We performed a systematic review and meta-analysis of the existing guidelines and studies surrounding neuroimaging in headache patients.

Methods: The research question involved determining the prevalence of detecting clinically significant neurological abnormalities using neuroimaging in patients suspected of primary headache. Searches of the PubMed and Embase databases were conducted on English-language studies published from 1991 to 2016, and the reference lists of the retrieved articles were also checked manually. All headache subtypes and patients aged ≥15 years were included in the analysis.

Results: Ten studies met the selection criteria. The pooled prevalence of detecting clinically significant abnormalities in the neuroimaging of headache patients was 8.86% (95% confidence interval: 5.12-15.33%). Subsequently, diverse subgroup analyses were performed based on the detection method, headache type, study type, study region, age group, and disease type.

Conclusion: The present findings indicate that limited neuroimaging methods should be carefully considered for headache diagnostic purposes when there are red flag symptoms. Limitations and suggested directions for future studies on neuroimaging in headache patients are described.

Keywords: Headache; Magnetic resonance imaging; Neuroimaging; X-ray computed tomography.

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Conflict of interest statement

The authors have no potential conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
PRISMA flowchart of the study selection process. Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) flow chart.
Figure 2.
Figure 2.
Forest plot and funnel plot for the Research Question. Forest plot (A) showing the prevalence of detecting clinically significant abnormalities. The events refer to cases in which abnormal findings were observed when neuroimaging was performed on the patients in each study. The total refers to the number of patients participating in each study, and the x-axis represents the confidence interval. When the confidence interval does not include zero, the incidence is not zero. Publication bias was tested using funnel plots. Funnel plot (B) showing the log-transformed proportion of detecting clinically significant abnormalities. To calculate the pooled proportion, the data were log-transformed and evaluated by the Clopper-Pearson method to calculate 95% confidence intervals (CIs). Asymmetrical points indicate the presence of publication bias.
Figure 3.
Figure 3.
Forest plots for the subgroup analyses. Forest plot (A) showing the subgroup analysis by detection method. Forest plot (B) showing the subgroup analysis by headache type. Forest plot (C) showing the subgroup analysis by study type. Forest plot (D) showing the subgroup analysis by study region.
See this image and copyright information in PMC

References

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