Correlation of Hounsfield Unit Measurements on Computed Tomography of the Shoulder With Dual-Energy X-ray Absorptiometry Scans and Fracture Risk Assessment Tool Scores: A Potential for Opportunistic Screening

Predicting Proximal Humerus Fracture Mechanical Complications: Are Computed Tomography Hounsfield Units the Answer?

INTRODUCTION

The purpose was to determine whether computed tomography (CT) Hounsfield units (HU) as a proxy for bone quality can predict postoperative complications following surgical treatment of proximal humerus fractures.

METHODS

Sixty-six patients with 2-, 3-, or 4-part proximal humerus fractures who underwent surgical fixation at single institution and had complete radiographic data available were included. Radiographic measurements included the deltoid tuberosity index (DTI) on preoperative anterior-posterior shoulder radiographs, and the HU value from the surgical proximal humerus was determined by measuring the humeral head at the midaxial/coronal/sagittal CT image using a circle-type region of interest (≥35 mm 2 ). Postoperative complications recorded were implant failure, development of osteonecrosis, nonunion, and acute periprosthetic fracture. Patients with and without complications were statistically compared, and binary logistic regression was performed to determine whether preoperative proximal humerus CT HU were predictive of complications.

RESULTS

Eight patients (12.1%) developed 11 overall complications, with three patients experiencing multiple complications each. Complications included osteonecrosis (4), implant failure (5), nonunion (1), and acute periprosthetic fracture (1). No difference was observed in demographics or Neer or AO/OTA classification between those with and without complications. Patients with complications had markedly lower DTI and overall HU as well as HU in the coronal and sagittal planes. Regression analysis for average DTI demonstrated a higher DTI and had a 10 times decreased risk of complication ( P = 0.040, odds ratio = -10.5, 95% confidence interval, 0.000 to 0.616). Regression analysis for average total HU also found a higher HU associated with a decreased risk of complications ( P = 0.034, odds ratio = -0.020, 95% confidence interval, 0.980 to 0.962). Logistic regression analysis, including age, age-adjusted Charlson Comorbidity Index, mean DTI, and mean total HU, only found mean total HU to be notable within the model.

DISCUSSION

CT HU may identify patients with poorer bone quality and thus help predict postoperative complications.

LEVEL OF EVIDENCE

Diagnostic Level III.

Comparison of Bone Mineral Density in Children and Adolescents on CT Versus DEXA Scan

STUDY DESIGN

Retrospective cross-sectional.

OBJECTIVES

To determine associations between Hounsfield units (HU) within a region of interest on computed tomography (CT) scans and dual energy X-ray absorptiometry (DEXA) measurements in children and adolescents.

SUMMARY OF BACKGROUND DATA

HU on CT scans as a proxy for bone mineral density (BMD) is widely used in adults. However, the utility of CT as a proxy for BMD have not been evaluated in children and adolescents.

MATERIALS AND METHODS

Patients younger than 18 years with a lumbar spine CT scan and a DEXA within 6 months of each other were identified. A region of interest was used to measure the HU at each lumbar vertebral body on midaxial cuts. Charts were reviewed for demographics, medical comorbidities, and DEXA reports. Correlation coefficients were calculated between the mean DEXA Z -score and the HU value. Patients were also stratified by Z -score (≥ -1.0, between -1.0 and -2.0, and ≤-2.0) and matched by age, sex and body mass index (BMI) to a cohort of healthy children and compared.

RESULTS

A moderate correlation between mean DEXA Z -score and mean HU on CT was found ( r2 =0.42, P <0.001). After matching for age, sex and BMI, 21 patients in each group between the ages of 4 and 17 years were analyzed. The mean HU value of the control group was 231.69. When stratified by Z -score (≥ -1.0, between -1.0 and -2.0, and ≤-2.0), the mean HU values were 244.59, 216.50, and 176.54, respectively. Patients with a Z -score of ≤-2.0 had a significantly lower mean HU than matched controls.

CONCLUSIONS

HU on lumbar CT in children and adolescents with DEXA Z -scores <-2.0, were lower when compared with healthy matched controls. This study suggests that HU on opportunistic CT scans of the spine may be used as a reasonable proxy for BMD in the pediatric population.

The role of humerus cortical thickness in predicting osteoporosis in MR imaging

Aim

This study aims to evaluate the efficacy of humerus cortical thickness on coronal T1-weighted images of the humerus in distinguishing patients with normal vs. abnormal bone mineral density (BMD).

Methods

Patients (n:138) with shoulder magnetic resonance imaging (MRI) and dual-energy x-ray absorptiometry (DXA) scans were evaluated. Patients were grouped into normal and low BMD (osteopenia and osteoporosis) according to DXA. An average cortical bone thickness (CBTavg) and gauge cortical bone thickness (CBTg) were calculated from the proximal humerus on coronal T1W MRI. Sensitivity and specificity for the prediction of osteoporosis were determined for several cortical bone thickness thresholds.

Results

Proximal humerus average cortical bone thickness measurements strongly correlated with DXA femur and lumbar scores (p < 0.01). Gauge cortical thickness measurements also correlated with DXA femur and lumbar scores (p < 0.01). Average cortical bone thickness measurement of 4.52 mm was determined to be a potential marker for predicting osteoporosis, with a sensitivity of 92.3% and a specificity of 84.9%.

Conclusion

Average cortical bone thickness measurements obtained from shoulder MRI are correlated with DXA. It appears to be effective in differentiating patients with normal and abnormal BMD and may help to opportunistically predict patients with osteoporosis in a rapid, simple and practical way, potentially guiding further diagnostic assessments.

Can we screen opportunistically for low bone mineral density using CT scans of the shoulder and artificial intelligence?

OBJECTIVE

To evaluate whether the CT attenuation of bones seen on shoulder CT scans could be used to predict low bone mineral density (BMD) (osteopenia/osteoporosis), and to compare the performance of two machine learning models to predict low BMD.

METHODS

In this study, we evaluated 194 patients aged 50 years or greater (69.2 ± 9.1 years; 170 females) who underwent unenhanced shoulder CT scans and dual-energy X-ray absorptiometry within 1 year of each other between January 1, 2010, and December 31, 2021. The CT attenuation of the humerus, glenoid, coracoid, acromion, clavicle, first, second, and third ribs was obtained using 3D-Slicer. Support vector machines (SVMs) and k-nearest neighbours (kNN) were used to predict low BMD. DeLong test was used to compare the areas under the curve (AUCs).

RESULTS

A CT attenuation of 195.4 Hounsfield Units of the clavicle had a sensitivity of 0.577, specificity of 0.781, and AUC of 0.701 to predict low BMD. In the test dataset, the SVM had sensitivity of 0.686, specificity of 1.00, and AUC of 0.857, while the kNN model had sensitivity of 0.966, specificity of 0.200, and AUC of 0.583. The SVM was superior to the CT attenuation of the clavicle (P = .003) but not better than the kNN model (P = .098).

CONCLUSION

The CT attenuation of the clavicle was best for predicting low BMD; however, a multivariable SVM was superior for predicting low BMD.

ADVANCES IN KNOWLEDGE

SVM utilizing the CT attenuations at many sites was best for predicting low BMD.

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study

BACKGROUND

The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT).

OBJECTIVE

To construct a novel predicting model based on bone turn-over markers and CT to identify patients who were more inclined to suffer spine refracture.

METHODS

CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U-net model was adopted to automatically segment ROI. Three-dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121-3D model to model the cropped region and simultaneously build a T-NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models.

RESULTS

The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer-Lemeshow goodness-of-fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p-value < 0.05) compared to using clinical features independently or using only 3D_RoiOnly.

CONCLUSION

T_P1NT was an independent risk factor of refracture. Our 3D-FULL model showed better performance in predicting high-risk population of spine refracture than other models and junior doctors do. This model can be applicable to real-world translation due to its automatic segmentation and detection.

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.

Osteoporosis: Molecular Pathology, Diagnostics, and Therapeutics

Osteoporosis is a major public health concern affecting millions of people worldwide and resulting in significant economic costs. The condition is characterized by changes in bone homeostasis, which lead to reduced bone mass, impaired bone quality, and an increased risk of fractures. The pathophysiology of osteoporosis is complex and multifactorial, involving imbalances in hormones, cytokines, and growth factors. Understanding the cellular and molecular mechanisms underlying osteoporosis is essential for appropriate diagnosis and management of the condition. This paper provides a comprehensive review of the normal cellular and molecular mechanisms of bone homeostasis, followed by an in-depth discussion of the proposed pathophysiology of osteoporosis through the osteoimmunological, gut microbiome, and cellular senescence models. Furthermore, the diagnostic tools used to assess osteoporosis, including bone mineral density measurements, biochemical markers of bone turnover, and diagnostic imaging modalities, are also discussed. Finally, both the current pharmacological and non-pharmacological treatment algorithms and management options for osteoporosis, including an exploration of the management of osteoporotic fragility fractures, are highlighted. This review reveals the need for further research to fully elucidate the molecular mechanisms underlying the condition and to develop more effective therapeutic strategies.

Bone quality in total shoulder arthroplasty: a prospective study correlating computed tomography Hounsfield units with thumb test and fracture risk assessment tool score

Background

To evaluate if Hounsfield units (HU) measured on preoperative computed tomography (CT) scans at the anatomic neck of the proximal humerus correlates with intraoperative findings of the "thumb test" in assessment of bone quality in shoulder arthroplasty patients.

Methods

Primary anatomic total shoulder and reverse total shoulder arthroplasty patients from 2019-2022 with an available preoperative CT scan of the operative shoulder were prospectively enrolled at a single center with 3 surgeons who perform shoulder arthroplasty. The "thumb test" was performed intraoperatively; a positive test signified "good bone." Demographic information, including prior dual x-ray absorptiometry scans, was extracted from the medical record. HU at the cut surface of the proximal humerus were calculated, as was cortical bone thickness on preoperative CT. Fracture risk assessment tool (FRAX) scores were calculated for 10-year risk of osteoporotic fracture.

Results

A total of 149 patients were enrolled. Mean age was 67.6 ± 8.5 years with 69 (46.3%) being males. Patients with a negative thumb test were significantly older (72.3 ± 6.6 vs. 66.5 ± 8.6 years; P < .001) than those with a positive thumb test. Males were more likely to have a positive thumb test than females (P = .014). Patients with a negative thumb test had significantly lower HUs on preoperative CT (16.3 ± 29.7 vs. 51.9 ± 35.2; P < .001). Patients with a negative thumb test had a higher mean FRAX score (14.1 ± 7.9 vs. 8.0 ± 4.8; P < .001). Receiver operator curve analysis was performed to identify a cut-off value for CT HU of 36.67, above which the thumb test is likely to be positive. Furthermore, receiver operator curve analysis also identified optimal cut-off values for 10-year risk of fracture by FRAX score of 7.75 HU, below which the thumb test is likely to be positive. Fifty patients were at high risk based on FRAX and HU; surgeons classified 21 (42%) as having "poor bone" quality through a negative thumb test. High-risk patients had a negative thumb test 33.8% (23/68) and 37.1% (26/71) of the time for HU and FRAX, respectively.

Conclusions

Surgeons are poor at identifying suboptimal bone quality at the anatomic neck of the proximal humerus based on intraoperative thumb test when referencing against CT HU and FRAX scores. The objective measures of CT HU and FRAX scoring may be useful metrics to incorporate into surgeons' preoperative plans for humeral stem fixation using readily available imaging and demographic data.

Age- and sex-specific normative values of bone mineral density in the adult glenoid

The objective of this study was to determine the normative bone mineral density (BMD) of cortical and trabecular bone regions in the adult glenoid and its dependence on the subject's age and sex. We analyzed computed tomography (CT) scans of 441 shoulders (310 males, 18-69 years) without any signs of glenohumeral joint pathology. Glenoid BMD was automatically quantified in six volumes of interest (VOIs): cortical bone (CO), subchondral cortical plate (SC), subchondral trabecular bone (ST), and three adjacent layers of trabecular bone (T1, T2, and T3). BMD was measured in Hounsfield unit (HU). We evaluated the association between glenoid BMD and sex and age with the Student's t test and Pearson's correlation coefficient (r), respectively. The lambda-mu-sigma method was used to determine age- and sex-specific normative values of glenoid BMD in cortical (CO and SC) and trabecular (ST, T1, T2, and T3) bone. Glenoid BMD was higher in males than females, in most age groups and most VOIs. Before 40 years old, the effect of age on BMD was very weak in both males and females. After 40 years old, BMD declined over time in all VOIs. This BMD decline with age was greater in females (cortical: r = -0.45, trabecular: r = -0.41) than in males (cortical: r = -0.30; trabecular: r = -0.32). These normative glenoid BMD values could prove clinically relevant in the diagnosis and management of patients with various shoulder disorders, in particular glenohumeral osteoarthritis and shoulder arthroplasty or shoulder instability, as well as in related research.

Evaluating bone quality and asymmetrical aplasia of the thoracic vertebral body in Lenke 1A adolescent idiopathic scoliosis using hounsfield units

Study Design

Retrospective analysis.

Objective

To evaluate bone quality and investigate asymmetrical development of the thoracic vertebral body in adolescent idiopathic scoliosis (AIS) based on Hounsfield unit (HU) measurements obtained from computed-tomography (CT) scans.

Summary of Background Data

HU value demonstrated higher reliability and accuracy than the traditional method, indicating that they could be used to individually evaluate and effectively assess the bone quality of every vertebra in the CT films.

Methods

Total 30 AIS patients classified as Lenke Type 1A and 30 paired controls were included in this study. Regions of interest for HU value were measured on three horizontal images of the thoracic vertebrae. HU measurements of the whole vertebral body in each vertebra were obtained. Using HU value, we separately measured the concave and convex sides of each vertebral body in patients' group, as well as within the left and right sides in controls.

Results

In controls, the mean HU value of T1–T12 thoracic vertebral bodies was 240.03 ± 39.77, with no statistical differences among different levels. As for AIS patients, in the structural curve, the apical region had a significantly lower HU compared with the other regions, and asymmetrical change was found between the concave and convex sides, most significantly in the apical region. In the non-structural curve, the average HU value was 254.99 ± 44.48, and no significant difference was found either among the different levels of vertebrae or between the concave and convex sides.

Conclusions

Abnormal and asymmetrical changes in bone quality of the thoracic vertebral body in patients with Lenke 1A AIS were indicated. Low bone quality in the convex side of the structural curve indicated stronger internal fixation in surgery to correct the deformity.