Current Concepts in Management of Acromioclavicular Joint Injury

Background: The management of acromioclavicular joint injuries requires a thorough understanding of the anatomy and biomechanics of the joint, as well as knowledge of the pertinent physical exam findings and classification to determine an appropriate treatment approach, whether operative or nonoperative. In this article, we present a narrative review of the current state of understanding surrounding these issues. Although there are a large number of options for operative intervention, we additionally present our experience with anatomic coracoclavicular ligament reconstruction (ACCR) with imbrication of the deltoid fascia. Methods: A retrospective review of prospectively collected data on a total of 45 patients who had undergone ACCR between 2003 and 2016 were collected. Results: We found that improvements were seen in American Shoulder and Elbow Surgeons Score (ASES) (53 ± 19 to 81 ± 23), Simple Shoulder Test (SST) (6 ± 3 to 12 ± 13), Constant-Murley (CM) (60 ± 18 to 92 ± 8), and Rowe (67 ± 14 to 89 ± 11) and the mean post-operative SANE score was 86 ± 17. Conclusions: ACCR has the advantage of addressing both horizontal and vertical stability with good outcomes.

Subject-specific computational modeling of acromioclavicular and coracoclavicular ligaments

BACKGROUND

Disruption of the acromioclavicular joint is a common injury. Despite the different surgical procedures described for treating this injury, complications such as loss of reduction and failure of fixation remain unacceptably high. We developed a computer model of the acromioclavicular joint to better understand the biomechanical contributions of the ligaments that are typically injured.

METHODS

Six fresh frozen human cadaveric shoulders were tested on an AMTI VIVO 6-degree of freedom test platform to measure force-displacement in inferior translation, anteroposterior translation, and internal rotation before and after sequentially transecting the coracoclavicular and acromioclavicular ligaments. These data were used to construct computer models of each specimen. Three-dimensional computed tomographic scans were used to generate a rigid-body dynamics model using the AnyBody Modeling System. The scapula and clavicle were connected by the acromioclavicular joint capsule, the conoid ligament, and the trapezoid ligament. Subject-specific ligament properties were calculated by matching computer predictions to experimental force-displacement data.

RESULTS

The calculated free lengths of the conoid, trapezoid, and acromioclavicular ligaments were 13.5 (±3.2), 11.8 (±2.4), and 11.0 (±2.7) mm, respectively. The calculated stiffnesses of the conoid, trapezoid, and acromioclavicular ligaments were 34.3 (±6.3), 28.4 (±3.2), and 33.8 (±8.2) N/mm, respectively. Root mean square deviation (RMSD) of predicted force-displacement curves relative to experimental force-displacement curves (during inferior and anteroposterior translation) was less than 1 mm. For validation of subject-specific models, after ligament properties were calculated, the RMSD of the predicted torque over 15° of internal rotation was 12% of maximum rotational torque (average for 6 specimens).

DISCUSSION AND CONCLUSION

Acromioclavicular disruption results in multidirectional instability, which requires careful consideration of the individual contributions of the injured ligaments. In addition, variations in patient anatomy can significantly affect the biomechanical stability of the reconstruction. Subject-specific models can enhance our understanding of the individual and collective biomechanical contributions of the injured soft tissues to the multiaxial stability of the acromioclavicular joint. These models may also be useful for analyzing and assessing biomechanical stability after various types of surgical reconstruction.