We have developed an algorithm that can be used to distinguish the central part of the vertebral body from an
abdominal X-ray CT image and to automatically calculate three measures to diagnose the degree of osteoporosis in a
patient. In addition, we examined whether it is possible to use these CT images as an aid in diagnosing osteoporosis.
Three measures that were automatically extracted from the central part of a vertebral body in the CT images were
compared with the bone mineral density (BMD) values that were obtained from the same vertebral body. We calculated
the mean CT number, coefficient of variation, and the first moment of power spectrum in the recognized vertebral body.
We judged whether a patient had osteoporosis using the diagnostic criteria for primary osteoporosis (Year 2000
revision, published by the Japanese Society for Bone and Mineral Research). We classified three measures for normal
and abnormal groups using the principal component analysis, and the two groups were compared with the results
obtained from the diagnostic criteria. As a result, it was found that the algorithm could be used to distinguish the central
part of the vertebral body in the CT images and to calculate these measures automatically. When distinguishing whether
a patient was osteoporotic or not with the three measures obtained from the CT images, the ratio (sensitivity) usable for
diagnosing a patient as osteoporotic was 0.93 (14/15), and the ratio (specificity) usable for diagnosing a patient as
normal was 0.64 (7/11). Based on these results, we believe that it is possible to utilize the measures obtained from these
CT images to aid in diagnosing osteoporosis.