Poster 173: Using Dynamic Digital Radiography to Measure Variation in Scapulohumeral Rhythm of Pathologic Shoulders

OBJECTIVES: Patients with various shoulder pathologies suffer from diminished range of motion and scapulohumeral rhythm (SHR), defined as the ratio of the respective contributions of glenohumeral and scapulothoracic motion to arm elevation. While previously challenging to measure SHR in a clinical setting, a novel technique known as Dynamic Digital Radiography (DDR) provides a safe and cost-effective method to directly evaluate aberrancies in motion. The purpose of this study was to measure the SHR of pathologic shoulders using Dynamic Digital Radiography (DDR). METHODS: Shoulders were prospectively analyzed using DDR via obtaining a series of pulsed radiographs at up to 15 Hz of the joint in motion. Scapulothoracic motion and glenohumeral motion were quantified based on DDR images (figure 1). Measurements were taken in humeral abduction at 0-30°, 30-60°, 60-90°, and full abduction using the Grashey view. SHR at different points was calculated by dividing humeral arc of motion by scapular arc of motion in each of the aforementioned ranges. ANOVA testing was conducted to analyze differences among treatment groups and post-hoc Tukey testing was utilized to identify the specific groups between which differences occurred. Pairwise t-testing was performed to isolate differences between preop and postop radiographs. An alpha of 0.05 was set for determining significance for all outcome measures. RESULTS: 121 shoulders were analyzed, including 40 controls, 13 small rotator cuff tears (SRT), 29 massive rotator cuff tears (MRCT), 16 adhesive capsulitis, and 23 glenohumeral osteoarthritis (table 1). The final angle calculations are displayed in Table 2. SHR for full arc of abduction differed significantly in patients with massive rotator cuff tear (1.91 ± 0.51), adhesive capsulitis (1.55 ± 0.13), and glenohumeral osteoarthritis (2.31 ± 1.03) compared to controls (3.39 ± 0.62). No statistically significant difference was found in overall SHR between small rotator cuff tear (3.04 ± 1.62) and controls (3.39 ± 0.62). When analyzed across 30-degree intervals of humeral abduction, there was a statistically significant lower SHR found at 0-30°, 30-60° and 60-90° of humeral abduction in MRCT, adhesive capsulitis and glenohumeral osteoarthritis patients compared to controls. No significant difference was found in the SHR of patients with SRCT compared to controls across all 30-degree intervals of humeral abduction. SHR changes across these intervals of humeral abduction are plotted in figure 2. Control patients had average overall humeral abduction range of motion of 103.40 ± 31.97° which was significantly larger compared to all included shoulder pathologies (MRCT: 75.75 ± 22.61, SRCT: 80.93 ± 20.71, adhesive capsulitis: 64.49 ± 27.02, osteoarthritis: 71.05 ± 34.88). During humeral abduction, control patients had average overall scapular range of motion of 32.57 ± 13.60 which was significantly smaller compared patients with a MRCT (45.57 ± 10.41) and adhesive capsulitis (64.49 ± 27.02). No statistically significant difference was found when comparing scapular range of motion during humeral abduction in patients with small rotator cuff tears (29.71 ± 12.91) and glenohumeral osteoarthritis (34.77 ± 17.52) compared to normal controls. CONCLUSIONS: DDR is sensitive enough to detect a lower SHR in massive rotator cuff tears, adhesive capsulitis, and glenohumeral osteoarthritis compared to normal shoulders. While SHR varies throughout the arc of motion, it remained drastically different these 3 pathologies compared to controls. Moreover, when isolating for humeral and scapular motion on DDR, all 4 pathologic shoulder conditions had decreased humeral abduction compared to normal controls. Patients with adhesive capsulitis and massive rotator cuff tear also had an increased reliance on scapular contribution to overall humeral elevation. Ultimately, further study and validation of this dynamic assessment of SHR has the potential to augment the diagnostic algorithm for various shoulder pathologies.