Automatic method for vertebral morphometry measurements. Issue 4 (1st July 2016)

• Record Type: Journal Article
• Authors: Franchini, Roberto; Conversano, Francesco; Pisani, Paola; Casciaro, Ernesto; Peccarisi, Marco; Quarta, Eugenio; Grimaldi, Antonella; Muratore, Maurizio; Casciaro, Sergio
• Is Part Of: IET science, measurement & technology. Volume 10:Issue 4(2016)
• Page Start: 327
• Page End: 334
• Publication Date: 2016-07-01
• Subjects: fracture -- bone -- diagnostic radiography -- biomechanics; vertebral morphometry measurements -- spine lateral radiographs -- vertebra detection -- Bland–Altman analysis -- Pearson correlation coefficient -- optimal diagnostic coincidence -- manual morphometric measurement -- automatic morphometric measurement -- vertebral fractures; Measurement -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Periodicals; Nanotechnology -- Periodicals; Electromagnetism -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3
• DOI: 10.1049/iet-smt.2015.0172
• Languages: English
• ISSNs: 1751-8822

Abstract

Abstract : Aim of this study was to perform a detailed clinical validation of a novel fully automatic method for vertebral morphometry. About 80 spine lateral radiographs were evaluated both automatically, by the proposed algorithm, and manually, by an experienced radiologist. The following metrics were used for algorithm performance assessment: sensitivity and specificity in vertebra detection; errors in the localisation of characteristic points of vertebral border; errors in the measurement of six diagnostic parameters; level of agreement and correlation between manual and automatic morphometric measurements; overall accuracy of automatic diagnoses with respect to manual ones. Obtained results showed a very good performance in vertebra detection (sensitivity = 89.1% and specificity = 100.0%). Average errors in the localisation of vertebral characteristic points were always smaller than 3 mm (range 0.85–2.79 mm), causing relative errors in diagnostic parameter values ranging from −5.01 to +6.10%. Bland–Altman analysis documented a mean error in automatic measurements of diagnostic ratios of 0.01 ± 0.18 (bias ± 2 SDs), while Pearson's correlation coefficient resulted r = 0.71 ( p < 0.001). Finally, an optimal diagnostic coincidence (92.8%) was found between automatic and manual diagnoses. Therefore, the adopted method has a potential for an effective employment in clinical routine for reliable diagnosis of vertebral fractures.