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Published:
Mar 6, 2025DOI:
10.4314/emj.v63i1.6Keywords:
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Main Article Content
Acute headaches: Patterns of MRI findings
Abstract
Background: There is a lack of research on imaging findings of acute headaches in Ethiopia. Most available studies for cross-reference are conducted in developed countries and do not consider clinical and epidemiologic factors unique to developing countries. This study aims to identify the most common radiologic findings in patients presenting with acute headaches and examine their relationship with sociodemographic and clinical variables in an Ethiopian context.
Methodology: A cross-sectional study was adopted in this study. The brain MRI reports and files of 497 patients who were referred for the evaluation of acute headache (less than or equal to one-month duration) to Wudassie Diagnostic Center in Addis Ababa, Ethiopia, from January 2016 to September 2018 were analyzed. The demographic variables and the clinical data of the patients were correlated to the imaging findings. Data analysis was done using IBM SPSS Statistics for Windows Version 20.0.
Results: 60.6% of the patients referred for the evaluation of acute headache had abnormal MRI findings. Nonspecific white matter lesions (which neither explain the reason for acute headache nor alter patient outcome and management) were the most frequently observed radiologic diagnosis (16%), followed by neoplasms (11.1%) and infections (7.7%). Tuberculoma was the most frequently diagnosed infectious cause. The majority of patients with comorbid illnesses (hypertension and HIV) had abnormal imaging findings. Age had a weak but significant positive correlation with abnormal imaging findings.
Conclusion: The findings suggest that acute headaches are frequently associated with significant underlying pathologies, particularly in older patients and those with comorbidities such as HIV or hypertension. The prominence of tuberculoma among infectious causes reflects the influence of local epidemiological factors. These results highlight the importance of targeted imaging protocols to enhance diagnostic accuracy and optimize patient management in resource-limited healthcare settings.
