Summary

Three-Dimensional evaluation of bipolar defect volumes enable surgeons to clearly visualize the defects, understand the pathology and perfectly shape bone grafts intra-operatively, if needed.

Abstract

Background

Glenoid and humeral head bone defects have long been recognized as major determinants in recurrent shoulder instability as well as main predictors of outcomes after surgical stabilization. The utility of 3-dimensional (3D) computed tomography (CT) has been largely proved over other imaging modalities. Previous knowledge has been recently called into question. The purpose of the present study is to describe a new CT method to quantify bipolar bone defects volume on a virtually generated 3D model and to evaluate its reproducibility.

Methods

A cross-sectional observational study has been conducted. Forty CT scans of both shoulders were randomly selected from a series of exams previously acquired on patients prospectively enlisted for an imaging study on anterior shoulder instability. Inclusion criterion was unilateral anterior shoulder instability with at least one episode of dislocation. Exclusion criteria were: patients affected by instability without dislocation (subluxation or athlete’s painful shoulder without instability); bilateral shoulder instability; posterior or multidirectional instability, previous fractures and/or surgery to both shoulders; congenital or acquired inflammatory, neurological, or degenerative diseases (systemic or local) involving the shoulder girdles. For all patients, CT exams of both shoulders were acquired at the same time following a standardized imaging protocol. The CT data sets were analyzed on a standard desktop PC using the software 3D Slicer (https://www.slicer.org). Computer-based reconstruction of the Hill-Sachs and glenoid bone defect were performed through Boolean subtraction of the affected side from the contralateral one, resulting in a virtually generated bone fragment accurately fitting the defect. The volume of the virtual bone fragments was then calculated. All measurements were conducted by two fellowship-trained orthopaedic shoulder surgeons. Each measurement was performed twice by one observer to assess intra-observer reliability. Two weeks elapsed between the observation series. For every series of measurement, CT images segmentation and 3D model generation and matching were repeated. Sample size was calculated to ensure a power of 80%. Inter and intra-observer reliability were calculated with R statistical software (v4.0.0, R Foundation for Statistical Computing, Vienna, Austria). Intraclass Correlation Coefficients (ICCs) were calculated using a two-way random effect model and evaluation of absolute agreement. Confidence intervals (CI) were calculated at 95% confidence level for reliability coefficients. Reliability values range from 0 (no agreement) to 1 (maximum agreement).

Results

The study included 34 males and 6 females. Mean age (+ SD) of patients was 36.7 + 10.10 years (range: 25 – 73 years). A bipolar bone defect was observed in all cases. Reliability of humeral head bone fragment measurements showed excellent intra-observer agreement (ICC: 0.92, CI 95%: 0.85 – 0.96) and very good interobserver agreement (ICC: 0.89, CI 95%: 0.80 – 0.94). Similarly, glenoid bone loss measurement resulted in excellent intra-observer reliability (ICC: 0.92, CI 95%: 0.85 – 0.96) and very good inter-observer agreement (ICC: 0.84, CI 95%:0.72 – 0.91).

Conclusion

Matching affected and intact contralateral humeral head and glenoid by reconstruction on a computer-based virtual model allows identification of bipolar bone defects and enables quantitative determination of bone loss.