  A large database of brain imaging data from healthy, normal controls is
useful to describe physiologic and pathologic structural changes at a
population scale. In particular, these data can provide information about
structural changes throughout development and aging. However, scarcity of
control data as well as technical challenges during imaging acquisition has
made it difficult to collect large amounts of data in a healthy pediatric
population. In this study, we search the medical record at Vanderbilt
University Medical Center for pediatric patients who received brain imaging,
either CT or MRI, according to 7 common complaints: headache, seizure, altered
level of consciousness, nausea and vomiting, dizziness, head injury, and gait
abnormalities in order to find the percent of studies that demonstrated
pathologic findings. Using a text-search based algorithm, we show that an
average 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 results
suggest there is a wealth of pediatric imaging control data which can be used
to create normative descriptions of development as well as to establish
biomarkers for disease.
