A Computer-aided Method for Improving the Reliability of Lenke Classification for Scoliosis. Issue 2 (3rd June 2015)

• Record Type: Journal Article
• Authors: Zhang, Junhua; Li, Hongjian; Lv, Liang; Shi, Xinling; Guo, Fei; Zhang, Yufeng
• Is Part Of: Journal of healthcare engineering. Volume 6:Issue 2(2015)
• Page Start: 145
• Page End: 158
• Publication Date: 2015-06-03
• Subjects: Lenke classification -- scoliosis -- radiograph -- computer-aided diagnosis; Hospital buildings -- Environmental engineering -- Periodicals; Medical technology -- Periodicals; Medical informatics -- Periodicals; 610.28
• DOI: 10.1260/2040-2295.6.2.145
• Languages: English
• ISSNs: 2040-2295

Abstract

Abstract : Classification of the spinal curve pattern is crucial for assessment and treatment of scoliosis. We developed a computer-aided system to improve the reliability of three components of the Lenke classification. The system semi-automatically measured the Cobb angles and identified the apical lumbar vertebra and its pedicles on digitized radiographs. The system then classified the curve type, lumbar modifier, and thoracic sagittal modifier of the Lenke classification based on the computerized measurements and identifications. The system was tested by five operators for 62 scoliotic cases. The kappa statistic was used to assess the reliability. With the aid of computer, the average intra- and interobserver kappa values were improved to 0.89 and 0.81 for the curve type, to 0.83 and 0.81 for the lumbar modifier, and to 0.94 and 0.92 for the sagittal modifier of the Lenke classification, respectively, relative to the classification by two of the operators without the aid of computer. Results indicate that the computerized system can improve reliability for all three components of the Lenke classification.