Regional apparent density correlations within the proximal humerus

Preoperative 3-dimensional computed tomography bone density measures provide objective bone quality classifications for stemless anatomic total shoulder arthroplasty

BACKGROUND

Reproducible methods for determining adequate bone densities for stemless anatomic total shoulder arthroplasty (aTSA) are currently lacking. The purpose of this study was to evaluate the utility of preoperative computed tomography (CT) imaging for assessing the bone density of the proximal humerus for supportive differentiation in the decision making for stemless humeral component implantation. It was hypothesized that preoperative 3-dimensional (3-D) CT bone density measures provide objective classifications of the bone quality for stemless aTSA.

METHODS

A 3-part study was performed that included the analysis of cadaveric humerus CT scans followed by retrospective application to a clinical cohort and classification with a machine learning model. Thirty cadaveric humeri were evaluated with clinical CT and micro-CT (μCT) imaging. Phantom-calibrated CT data were used to extract 3-D regions of interest and defined radiographic scores. The final image processing script was applied retrospectively to a clinical cohort (n = 150) that had a preoperative CT and intraoperative bone density assessment using the "thumb test," followed by placement of an anatomic stemmed or stemless humeral component. Postscan patient-specific calibration was used to improve the functionality and accuracy of the density analysis. A machine learning model (Support vector machine [SVM]) was utilized to improve the classification of bone densities for a stemless humeral component.

RESULTS

The image processing of clinical CT images demonstrated good to excellent accuracy for cylindrical cancellous bone densities (metaphysis [ICC = 0.986] and epiphysis [ICC = 0.883]). Patient-specific internal calibration significantly reduced biases and unwanted variance compared with standard HU CT scans (P < .0001). The SVM showed optimized prediction accuracy compared with conventional statistics with an accuracy of 73.9% and an AUC of 0.83 based on the intraoperative decision of the surgeon. The SVM model based on density clusters increased the accuracy of the bone quality classification to 87.3% with an AUC of 0.93.

CONCLUSIONS

Preoperative CT imaging allows accurate evaluation of the bone densities in the proximal humerus. Three-dimensional regions of interest, rescaling using patient-specific calibration, and a machine learning model resulted in good to excellent prediction for objective bone quality classification. This approach may provide an objective tool extending preoperative selection criteria for stemless humeral component implantation.

Age-Related changes in the morphological features of medial column of the proximal humerus in the Chinese population

Background

Age-related changes in the medial column (MC) of the proximal humerus have a major impact on fracture management; however, the changes in the morphological features remain unclear. This study aimed to investigate the age-related changes in the morphological features of MC and present the morphological grading.

Methods

One hundred computed tomography (CT) images of the proximal humerus of 100 individuals (19-95 years) were retrospectively obtained. The individuals were categorized into five age groups to quantify the differences among different ages; the youngest group (18-44 years) served as the baseline group. Parameters of the morphological features were measured on CT images with multiplanar reconstruction based on an explicit definition of MC, including length, thickness, width, oblique thickness (DSM), humeral head diameter (DHM), and ratio (RSM) of DSM to DHM. The morphological grading of MC was presented based on the value of RSM deviating different standard deviations (SD) from the mean value in the baseline group.

Results

Significant negative correlations were observed between age and the morphological parameters of MC (r ranged from -0.875 to -0.926; all P < 0.05), excluding DHM (r = 0.081, P = 0.422). Significant differences in the values of morphological feature parameters were detected among the five age groups (all P < 0.001). The highest mean values of morphological feature parameters were observed in the youngest group (18-44 years), which decreased gradually with increasing age until the lowest mean values were observed in the oldest group (≥90 years) (all P < 0.05). The morphological features of MC were categorized into three grades based on the value of RSM deviating 1.5 SD or 3 SD from the mean value in the baseline group.

Conclusion

Our study shows that the parameter values of morphological features of MC decreased with increasing age. The morphological features of MC could be categorized into three grades. Our findings may provide a more comprehensive insight into age-related changes in the morphological features of MC that facilitate risk stratification and optimize the management of proximal humeral fractures.

Simple preoperative radiographic and computed tomography measurements predict adequate bone quality for stemless total shoulder arthroplasty

INTRODUCTION

Although there is increased utilization of stemless humeral implants in anatomic total shoulder arthroplasty (TSA), there are inadequate objective metrics to evaluate bone quality sufficient for fixation. Our goals are to: (1) compare patient characteristics in patients who had plans for stemless TSA but received stemmed TSA due to intraoperative assessments and (2) propose threshold values of bone density, using the deltoid tuberosity index (DTI) and proximal humerus Hounsfield units (HU), on preoperative X-ray and computed tomography (CT) to allow for preoperative determination of adequate bone stock for stemless TSA.

METHODS

This is an observational study conducted at an academic institution from 2019 to 2021, including consecutive primary TSAs templated to undergo stemless TSA based on 3-dimensional CT preoperative plans. Final implant selection was determined by intraoperative assessment of bone quality. Preoperative X-ray and CT images were assessed to obtain DTI and proximal humeral bone density in HU, respectively. A receiver operating characteristic curve was used to analyze the potential of preoperative X-ray and CT to classify patients as candidates for stemless TSA.

RESULTS

A total of 61 planned stemless TSAs were included, with 56 (91.8%) undergoing stemless TSA and 5 (8.2%) undergoing stemmed TSA after intraoperative assessment determined that the bone quality was inadequate for stemless fixation. There were no significant differences between the 2 groups in terms of gender (P = .640), body mass index (P = .296), and race (P = .580). The stem cohort was significantly older (mean age 69 ± 12 years vs. 59 ± 10 years, P = .029), had significantly lower DTI (1.45 ± 0.13 vs. 1.68 ± 0.18, P = .007), and had significantly less proximal humeral HU (-1.4 ± 17.7 vs. 78.8 ± 52.4, P = .001). The receiver operating characteristic curve for DTI had an area under the curve (AUC) of 0.86, and bone density in HU had an AUC of 0.98 in its ability to distinguish patients who underwent stemless TSA vs. short-stem TSA. A threshold cutoff of 1.41 for DTI resulted in a sensitivity of 98% and a specificity of 60%, and a cutoff value of 14.4 HU resulted in a sensitivity of 95% and a specificity of 100%.

CONCLUSIONS

Older age, lower DTI, and less proximal humeral bone density in HU were associated with the requirement to switch from stemless to short-stem humeral fixation in primary TSA. Preoperative DTI had good ability (AUC of 0.86) and preoperative HU had excellent ability (AUC of 0.98) to categorize patients as appropriate for stemless TSA. This can help surgeons adequately plan humeral fixation using standard preoperative imaging data.