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A large database of brain imaging data from healthy, normal controls isuseful to describe physiologic and pathologic structural changes at apopulation scale. In particular, these data can provide information aboutstructural changes throughout development and aging. However, scarcity ofcontrol data as well as technical challenges during imaging acquisition hasmade it difficult to collect large amounts of data in a healthy pediatricpopulation. In this study, we search the medical record at VanderbiltUniversity Medical Center for pediatric patients who received brain imaging,either CT or MRI, according to 7 common complaints: headache, seizure, alteredlevel of consciousness, nausea and vomiting, dizziness, head injury, and gaitabnormalities in order to find the percent of studies that demonstratedpathologic findings. Using a text-search based algorithm, we show that anaverage of 59.3% of MRI studies and 37.3% of CT scans are classified as normal,resulting in the production of thousands of normal images. These resultssuggest there is a wealth of pediatric imaging control data which can be usedto create normative descriptions of development as well as to establishbiomarkers for disease.

Opportunities for Mining Radiology Archives for Pediatric Control Images