# Optimizing the approach to headache neuroimaging > **NIH VA I01** · VETERANS HEALTH ADMINISTRATION · 2020 · — ## Abstract Project Summary/abstract Headaches are the most common neurologic condition, affecting more than 90% of the population at some point in their lives. Even though headaches are one of the most common indications for MRI, the optimal MRI protocol for this prevalent condition is unknown. Furthermore, patients and physicians are often worried about brain tumors, but the yield of neuroimaging in those with chronic headaches is 1-3%, which is comparable to a healthy population. In response, multiple guidelines recommend against routine neuroimaging in certain headache populations, but which factors should prompt neuroimaging is not clear. Furthermore, false positives are likely common on headache MRI, yet downstream harms of false positive findings have not been studied. We propose three potential solutions to improve the care of veterans with headaches. In Aim 1, we plan to determine the optimal set of MRI sequences for patients presenting with headaches. Our hypothesis is that FLAIR only MRI studies are non-inferior to conventional MRI for identifying brain lesions in patients with headache. Two neuroradiologists will read each MRI scan obtained in veterans with a headache diagnosis that are receiving an MRI as part of their routine care. Our primary analysis will determine the sensitivity of FLAIR-only MRI compared to conventional MRI for identifying headache-causing lesions. If our hypothesis is correct, fewer sequences may lower the incidence of false positive findings without substantially reducing the yield of true positives. Fewer false positives may also decrease the downstream harms associated with current neuroimaging practices. In Aim 2, we plan to define the incidence of downstream harms after false positive findings, which our preliminary data indicates may be quite high. False positive results will be defined as all abnormal MRI findings in the clinical radiologist's report that did not lead to a change in clinical management as determined by two neurologists with adjudication via consensus committee. Downstream harms of diagnostic imaging will be defined as additional diagnostic testing, procedures and consultations. We will also identify the patient phenotypes that are predictive of headache-causing lesions including headache characteristics, headache classification, and high risk clinical features (“red flags”). Previous small studies from selected populations have attempted to address this question, but we will be able to overcome many of the limitations of prior work. By characterizing the harms and high risk patient phenotypes, we will be able to inform rational clinical neuroimaging decisions to improve the health of veterans. Third, in Aim 3, we will identify the core reasons behind MRI overuse in the headache population but surveying providers and patients using the Theoretical Domains Framework. All three of these approaches will directly lead to future implementation studies. Our project is innovative is many ways. If we are ab... ## Key facts - **NIH application ID:** 9858241 - **Project number:** 5I01CX001504-03 - **Recipient organization:** VETERANS HEALTH ADMINISTRATION - **Principal Investigator:** Brian Christopher Callaghan - **Activity code:** I01 (R01, R21, SBIR, etc.) - **Funding institute:** VA - **Fiscal year:** 2020 - **Award amount:** — - **Award type:** 5 - **Project period:** 2018-01-01 → 2021-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9858241 ## Citation > US National Institutes of Health, RePORTER application 9858241, Optimizing the approach to headache neuroimaging (5I01CX001504-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9858241. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*