An understanding of the complex anatomy of the clavicle is helpful in the treatment of clavicular fractures. Using three-dimensional (3D) statistical shape analysis, the author presents a novel method to assess geometric morphology of the clavicle. Fifteen fresh frozen shoulder specimens were scanned using high-resolution computerized tomography (CT) but four were excluded from the study. A further 16 high-resolution CT scans of the clavicle were obtained by searching the hospital database. All 27 scans were reconstructed and subsequently imported into and analyzed using a specifically developed statistical software package. Using statistical shape analysis, geometric parameters were then measured. Both gender as well as side specific geometric morphology were observed. Clavicles in men were longer, wider, and thicker than in women. Right clavicles had a greater medial depth than left clavicles, especially in women. Clavicles in men had a greater lateral depth than in women. The sternal angle in women was larger than in men. Using 3D statistical shape analysis and applying it to the clavicle standardizes the study of its anatomy, rules out any variability, and calculates morphological parameters that are accurate, precise, and reproducible. This unique approach provides information that is useful not only to the clinician but also in the modification of current or design of future clavicle fixation devices. More importantly, from an anatomy standpoint, implementation of this novel approach in anatomical studies would eliminate intra- and interobserver variation and allow all studies to be standardized and thus more comparable.

BackgroundPrincipal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories.Materials and methodsTwenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation.ResultsThe first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups.Discussion And ConclusionsThis unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

Aims: Several studies have been performed that compare the accuracy of Robotic-Assisted Total Knee Arthroplasty (RATKA) to conventional instrumentation as well as navigation to conventional instrumentation, yet there is a lack of studies comparing RATKA to navigation. The purpose of this study is to evaluate the accuracy of a contemporary image free navigation system for TKA in a cadaveric study using the same methodology as used previously to access the accuracy of a RATKA system and conventional instrumentation. Methods: Four orthopaedic surgeons performed bi-lateral TKA on 18 pelvis-to-toe cadaveric specimens without implantation using the BrainLab Knee3 navigation system. Preoperative and postoperative computed tomography (CT) scans were taken to access the resection accuracy of the navigation system relative to the planned alignment targets recorded intraoperatively. Results: The mean error in femoral coronal angle was 1.08° ± 0.87° compared to 1.39° ± 0.95° conventional and 0.63° ± 0.50° RATKA; the differences between navigation and RATKA were statistically significant. The mean error in the tibial coronal angle was 1.24° ± 1.13° compared to 1.65° ± 1.29° conventional and 0.93° ± 0.72° RATKA. The mean error in femoral flexion was 2.13° ± 1.87° compared to 3.27° ± 2.51° conventional and 1.21° ± 0.90° RATKA; the differences between navigation and manual and navigation and RATKA were statistically significant. The mean errors in the femoral rotation (navigation 1.30° ± 1.38°, conventional 1.00° ± 0.70°, RATKA 1.04° ± 0.81°) and tibial slope (navigation 1.89° ± 1.28°, conventional 1.63° ± 1.39°, RATKA 1.62° ± 1.13°) were similar between the groups. Conclusion: This study showed that for some metrics navigation improves resection accuracy compared to conventional instrumentation and RATKA further improves resection accuracy compared to CAS.

No abstract

Understanding morphological variations in bone has become an important topic, specifically for total knee arthroplasties (TKA). The need for implants to cater to differences in bone shape has been highly debated [1–2]. Equally important is understanding the relationship between bone shape and kinematic variations. Previous work has investigated the relationship of several anatomical measures on varus-valgus (VV) and internal-external (IE) laxity [3]. However, the relationship between VV and IE laxity is less understood. The first objective of this research was to understand the relationship between IE and VV laxity using a single principal component analysis (PCA) model. The second objective was to correlate the results of the laxity model with a more inclusive measure of shape variation using statistical shape modeling (SSM). The use of SSM allows for quantifications of variation between subjects to be expressed in a manner which provides a more thorough understanding of bone variation [4]. The purpose of this research was to identify the relationship between IE and VV laxity, and correlate those results with variations in bone morphology of the femur and tibia.