Literature DB >> 17278819

Computerized detection of vertebral compression fractures on lateral chest radiographs: preliminary results with a tool for early detection of osteoporosis.

Satoshi Kasai1, Feng Li, Junji Shiraishi, Qiang Li, Kunio Doi.   

Abstract

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.

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Year:  2006        PMID: 17278819     DOI: 10.1118/1.2364053

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  6 in total

Review 1.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

Review 2.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

Review 3.  Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

Authors:  Feng Li
Journal:  Radiol Phys Technol       Date:  2015-05-17

4.  High precision semiautomated computed tomography measurement of lumbar disk and vertebral heights.

Authors:  Sovira Tan; Jianhua Yao; Lawrence Yao; Michael M Ward
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

5.  Compression fracture diagnosis in lumbar: a clinical CAD system.

Authors:  Samah Al-Helo; Raja S Alomari; Subarna Ghosh; Vipin Chaudhary; Gurmeet Dhillon; Moh'd B Al-Zoubi; Hazem Hiary; Thair M Hamtini
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-11-20       Impact factor: 2.924

Review 6.  An engineering view on megatrends in radiology: digitization to quantitative tools of medicine.

Authors:  Namkug Kim; Jaesoon Choi; Jaeyoun Yi; Seungwook Choi; Seyoun Park; Yongjun Chang; Joon Beom Seo
Journal:  Korean J Radiol       Date:  2013-02-22       Impact factor: 3.500

  6 in total

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