The Reliability of a Semi-automated Algorithm for Detection of Cortical Interruptions in Finger Joints on High Resolution CT Compared to MicroCT

Abstract

We developed a semi-automated algorithm for the detection of cortical interruptions in finger joints using high-resolution peripheral quantitative computed tomography (HR-pQCT). Here, we tested its reliability compared to microCT (A mu CT) as gold standard. Nineteen joints of 10 female anatomic index fingers were imaged by HR-pQCT and A mu CT (82 and 18 A mu m isotropic voxel sizes, respectively). The algorithm was applied for detection of cortical interruptions of different minimum diameters (range > 0.16 to > 0.50 mm). Reliability was tested at the joint level with intra-class correlation coefficient (ICC) for the number of interruptions and interruption surface, and at the level of a single interruption for matching between HR-pQCT and A mu CT with a fixed interruption diameter (> 0.10 mm) on A mu CT. The positive predictive value (PPV0.10mm) and sensitivity(0.10mm) were evaluated. The mean number of interruptions per joint depended on the diameter cut-off and ranged from 3.4 to 53.5 on HR-pQCT and from 1.8 to 45.1 on A mu CT for interruptions > 0.50 to > 0.16 mm, respectively. Reliability at the joint level was almost perfect (ICC >= 0.81) for both the number and surface of interruptions > 0.16 and > 0.33 mm. As expected, the PPV0.10mm increased with increasing interruption diameter from 84.9 to 100%, for interruptions > 0.16 and > 0.50 mm, respectively. However, the sensitivity(0.10mm) decreased with increasing interruption diameter from 62.4 to 4.7%. This semi-automated algorithm for HR-pQCT in finger joints performed best for the detection of cortical interruptions with a minimum diameter of > 0.16 or > 0.33 mm, showing almost perfect reliability at the joint level and interruptions matched with those on A mu CT.