Automated quantification of glenoid bone loss in CT scans for shoulder dislocation surgery planning

PurposeEstimation of glenoid bone loss in CT scans following shoulder dislocation is required to determine the type of surgery needed to restore shoulder stability. This paper presents a novel automatic method for the computation of glenoid bone loss in CT scans.MethodsThe model-based method is a pipeline that consists of four steps: (1) computation of an oblique plane in the CT scan that best matches the glenoid face orientation; (2) selection of the glenoid oblique CT slice; (3) computation of the circle that best fits the posteroinferior glenoid contour; (4) quantification of the glenoid bone loss. The best-fit circle is computed with newly defined Glenoid Clock Circle Constraints.ResultsThe pipeline and each of its steps were evaluated on 51 shoulder CT scans (44 patients). Ground truth oblique slice, best-fit circle, and glenoid bone loss measurements were obtained manually from three clinicians. The full pipeline yielded a mean absolute error (%) for the bone loss deficiency of 2.3 & PLUSMN; 2.9 mm (4.67 & PLUSMN; 3.32%). The mean oblique CT slice selection difference was 1.42 & PLUSMN; 1.32 slices, above the observer variability of 1.74 & PLUSMN; 1.82 slices. The glenoid bone loss deficiency measure (%) on the ground truth oblique glenoid CT slice has a mean average error of 0.54 & PLUSMN; 1.03 mm (4.76 & PLUSMN; 3.00%), close to the observer variability of 0.93 & PLUSMN; 1.40 mm (2.98 & PLUSMN; 4.97%).ConclusionOur pipeline is the first fully automatic method for the quantitative analysis of glenoid bone loss in CT scans. The computed glenoid bone loss report may assist orthopedists in selecting and planning surgical shoulder dislocation procedures.

Automated summary

This paper presents a novel automatic method for the computation of glenoid bone loss in CT scans. The method consists of four steps: computation of an oblique plane, selection of the glenoid oblique CT slice, computation of the best-fit circle, and quantification of the bone loss. The evaluation results show that the method has a mean absolute error of 2.3±2.9 mm (4.67±3.32%) and can assist orthopedists in surgical planning.