SciKit-SurgeryGlenoid, an Open Source Toolkit for Glenoid Version Measurement

Abstract

Correct understanding of the geometry of the glenoid (the socket of the shoulder joint) is key to successful planning of shoulder replacement surgery. This surgery typically involves placing an implant in the shoulder joint to restore joint function. The most relevant geometry is the glenoid version, which is the angular orientation of the glenoid surface relative to the long axis of the scapula in the axial plane. However, measuring the glenoid version is not straightforward and there are multiple measurement methods in the literature and used in commercial planning software. In this paper we introduce SciKit-SurgeryGlenoid, an open source toolkit for the measurement of glenoid version. SciKit-SurgeryGlenoid contains implementations of the 4 most frequently used glenoid version measurement algorithms enabling easy and unbiased comparison of the different techniques. We present the results of using the software on 10 sets of pre-operative CT scans taken from patients who have subsequently undergone shoulder replacement surgery. We further compare these results with those obtained from a commercial implant planning software. SciKit-SurgeryGlenoid currently requires manual segmentation of the relevant anatomical features for each method. Future work will look at automating the segmentation process to build an automatic and repeatable pipeline from CT or radiograph to quantitative glenoid version measurement.

Figure 1

A workflow diagram describing the current workflow. Relevant landmarks are currently identified using 3DSlicer and passed to SciKit-SurgeryGlenoid via the command line. For the corrected Friedman method the points are manually identified a second time after identification of the new axial slice.

Figure 2

Visualisations of the 2 plane, Friedman and Vault methods and of new axial slice plane used for corrected Friedman method. Additional visualisations of the axial slices of the Friedman and vault methods to show point selection. By default, SciKit-SurgeryGlenoid uses the colour blind friendly palette defined by Wong

Figure 3

The dependency graph for SciKit-SurgeryGlenoid. SciKit-Surgery dependencies are shown in blue, whilst 3rd party dependencies are shown in grey.

Figure 4. The Pearson correlation between the commercial software and the 3 methods that gave a statistically significant result.