Inter- and Intra-Observer Variability of the Volume of Cervical Ossification of the Posterior Longitudinal Ligament Using Medical Image Processing Software

Abstract

Objective: Computed tomography (CT)-based method of three dimensional (3D) analysis (MIMICS^®, Materialise, Leuven, Belgium) is reported as very useful software for evaluation of OPLL, but its reliability and reproducibility are obscure. This study was conducted to evaluate the accuracy of MIMICS^® system, and inter- and intra-observer reliability in the measurement of OPLL.

Methods: Three neurosurgeons independently analyzed the randomly selected 10 OPLL cases with medical image processing software (MIMICS^®) which create 3D model with Digital Imaging and Communication in Medicine (DICOM) data from CT images after brief explanation was given to examiners before the image construction steps. To assess the reliability of inter- and intra-examiner intraclass correlation coefficient (ICC), 3 examiners measured 4 parameters (volume, length, width, and length) in 10 cases 2 times with 1-week interval.

Results: The inter-examiner ICCs among 3 examiners were 0.996 (95% confidence interval [CI], 0.987-0.999) for volume measurement, 0.973 (95% CI, 0.907-0.978) for thickness, 0.969 (95% CI, 0.895-0.993) for width, and 0.995 (95% CI, 0.983-0.999) for length. The intra-examiner ICCs were 0.994 (range, 0.991-0.996) for volume, 0.996 (range, 0.944-0.998) for length, 0.930 (range, 0.873-0.947) for width, and 0.987 (range, 0.985-0.995) for length.

Conclusion: The medical image processing software (MIMICS^®) provided detailed quantification OPLL volume with minimal error of inter- and intra-observer reliability in the measurement of OPLL.

Keywords: 3D analysis; MIMICS; Ossification; Posterior longitudinal ligament; Volume.

Fig. 1

Steps for 3D reconstruction and measurement. A: CT scanning with 3 mm thickness. B: The obtained images are transmitted digitally via PACS. C: 3D software imports CT data in the DICOM format. D: The segmented object (visualized by a colored-mask) is obtained by including only those pixels of the image with a value higher than or equal to the threshold value (thresholding). E: The segmented object is further split by making another mask on OPLL and removing floating pixels (region growing). F: 3D representation is created and the volume is calculated automatically by the software. CT: computed tomography, DICOM: Digital Imaging and Communications in Medicine, OPLL: ossification of the posterior longitudinal ligament.

Fig. 2

Reconstructed 3D images of OPLL after the calculation of the 3D. A: Anterior view. B: Lateral view. C: Posterior view. D: A volumetric mesh with the material assignment for finite element analysis. OPLL: ossification of the posterior longitudinal ligament.

Fig. 3

Measurements. A: The width was defined as the maximum distance along the axis of the coronal plane of OPLL and the thickness was defined as the maximum distance along the axis of the sagittal plane of OPLL. B: The length was defined as the longest dimension of OPLL. C: The volume was calculated automatically by the software in the 3D-reconstructed image. OPLL: ossification of the posterior longitudinal ligament.

Fig. 4

Representative images obtained in a 47-year-old woman with cervical OPLL. A: Lateral X-ray showing an ossified lesion at the level of C3–4, however, the cervico-thoracic junction is not visualized adequately due to shoulder shadow. B: Sagittal-reconstruction CT showing mixed type OPLL. C: Axial CT image at the level of C4 demonstrating central OPLL. OPLL: ossification of the posterior longitudinal ligament, CT: computed tomography.