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Vertebral fracture (or vertebral deformity) is a very common outcome of osteoporosis, which is one of the major public health concerns in the world. Early detection of vertebral fractures is important because timely pharmacologic intervention can reduce the risk of subsequent additional fractures. Chest radiographs are used routinely for detection of lung and heart diseases, and vertebral fractures can be visible on lateral chest radiographs. However, investigators noted that about 50% of vertebral fractures visible on lateral chest radiographs were underdiagnosed or under-reported, even when the fractures were severe. Therefore, our goal was to develop a computerized method for detection of vertebral fractures on lateral chest radiographs in order to assist radiologists' image interpretation and thus allow the early diagnosis of osteoporosis. The cases used in this study were 20 patients with severe vertebral fractures and 118 patients without fractures, as confirmed by the consensus of two radiologists. Radiologists identified the locations of fractured vertebrae, and they provided morphometric data on the vertebral shape for evaluation of the accuracy of detecting vertebral end plates by computer. In our computerized method, a curved search area, which included a number of vertebral end plates, was first extracted automatically, and was straightened so that vertebral end plates became oriented horizontally. Edge candidates were enhanced by use of a horizontal line-enhancement filter in the straightened image, and a multiple thresholding technique, followed by feature analysis, was used for identification of the vertebral end plates. The height of each vertebra was determined from locations of identified vertebral end plates, and fractured vertebrae were detected by comparison of the measured vertebral height with the expected height. The sensitivity of our computerized method for detection of fracture cases was 95% (19/20), with 1.03 (139/135) false-positive fractures per image. The accuracy of identifying vertebral end plates, marked by radiologists in a morphometric study, was 76.6% (400/522) and 70.9% (420/592) for cases used for training and those for testing, respectively. We prepared 32 additional fracture cases for a validation test, and we examined the detection accuracy of our computerized method. The sensitivity for these cases was 75% (24/32) at 1.03 (33/32) false-positive fractures per image. Our preliminary results show that the automated computerized scheme for detecting vertebral fractures on lateral chest radiographs has the potential to assist radiologists in detecting vertebral fractures.
Kasai et al. (2006) studied this question.