Three-Dimensional Mapping of Scapular Body, Neck, and Glenoid Fractures.

OBJECTIVES: The purpose of this study was to report patterns of scapular fractures and define them with a contemporary methodology. METHODS: . DESIGN: Retrospective study, 2015-2021. SETTING: Single, academic, Level 1 trauma center. PATIENT SELECTION CRITERIA: Consecutive patients ≥18 years, presenting with unilateral scapula fracture, with thin-slice (≤0.5-mm) bilateral computed tomography (CT) scans of the entirety of both the injured and uninjured scapulae. OUTCOME MEASURES AND COMPARISONS: Thin-slice (0.5-mm) CT scans of injured and normal scapulae were obtained to create three-dimensional (3D) virtual models. 3D modeling software (Stryker Orthopedics Modeling and Analytics, Stryker Trauma GmbH, Kiel, Germany aka SOMA) was used to create a 3D map of fracture location and frequency. Fracture zones were delineated using anatomic landmarks to characterize fracture patterns. RESULTS: Eighty-seven patients were identified with 75 (86%) extra-articular and 12 (14%) intra-articular fractures. The dominant fracture pattern emanated from the superior lateral border (zone E) to an area inferior to the spinomedial angle (zone B) and was present in 80% of extra-articular fractures. A second-most common fracture line propagated from the primary (most-common) line toward the inferior medial scapular border with a frequency of 36%. Bare zones (with 1 or no fractures present) were identified in 4 unique areas. Furthermore, intra-articular fractures were found to be heterogenous. CONCLUSIONS: The 3D fracture map created in this study confirmed that extra-articular scapular fractures occur in certain patterns with a relatively high frequency. Results provide greater insight into scapular fracture locations and may help to study prognosis of injury and improve treatment strategy including operative approaches and surgical tactics.

Algorithms for Particle Detection in Complex Plasmas.

In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel accuracy from the recorded images. Typically, a straightforward algorithm such as the moment method is used for this task. Here, we combine different variations of the moment method with common techniques for image pre- and post-processing (e.g., noise reduction and fitting), and we investigate the impact of the choice of threshold parameters, including an automatic threshold detection, on synthetic data with known attributes. The results quantitatively show that each algorithm and method has its own advantage, often depending on the problem at hand. This knowledge is applicable not only to complex plasmas, but useful for any kind of comparable image-based particle tracking, e.g., in the field of colloids or granular matter.