Combination of radiograph-based trabecular and geometrical parameters can discriminate cervical hip fractures from controls in individuals with BMD in non-osteoporotic range

Discrimination of Low-Energy Acetabular Fractures from Controls Using Computed Tomography-Based Bone Characteristics

The incidence of low-energy acetabular fractures has increased. However, the structural factors for these fractures remain unclear. The objective of this study was to extract trabecular bone architecture and proximal femur geometry (PFG) measures from clinical computed tomography (CT) images to (1) identify possible structural risk factors of acetabular fractures, and (2) to discriminate fracture cases from controls using machine learning methods. CT images of 107 acetabular fracture subjects (25 females, 82 males) and 107 age-gender matched controls were examined. Three volumes of interest, one at the acetabulum and two at the femoral head, were extracted to calculate bone volume fraction (BV/TV), gray-level co-occurrence matrix and histogram of the gray values (GV). The PFG was defined by neck shaft angle and femoral neck axis length. Relationships between the variables were assessed by statistical mean comparisons and correlation analyses. Bayesian logistic regression and Elastic net machine learning models were implemented for classification. We found lower BV/TV at the femoral head (0.51 vs. 0.55, p = 0.012) and lower mean GV at both the acetabulum (98.81 vs. 115.33, p < 0.001) and femoral head (150.63 vs. 163.47, p = 0.005) of fracture subjects when compared to their matched controls. The trabeculae within the femoral heads of the acetabular fracture sides differed in structure, density and texture from the corresponding control sides of the fracture subjects. Moreover, the PFG and trabecular architectural variables, alone and in combination, were able to discriminate fracture cases from controls (area under the receiver operating characteristics curve 0.70 to 0.79). In conclusion, lower density in the acetabulum and femoral head with abnormal trabecular structure and texture at the femoral head, appear to be risk factors for low-energy acetabular fractures.

Structural risk factors for low-energy acetabular fractures

In this study, we aimed to clarify proximal femur and acetabular structural risk factors associated with low-energy acetabular fractures in the elderly using three-dimensional (3D) computed tomography (CT). Pelvic bones and femurs were segmented and modeled in 3D from abdominopelvic CT images of 121 acetabular fracture patients (mean age 72 ± 12 years, range 50-98 years, 31 females and 90 males) and 121 age-gender matched controls with no fracture. A set of geometric parameters of the proximal femur and the acetabulum was measured. An independent-samples t-test or a Mann-Whitney U test was used for statistical analyses. The fractured side was used for proximal femur geometry, while the contralateral side was used for acetabular geometry. The neck shaft angle (NSA) was significantly smaller (mean 122.1° [95% CI 121.1°-123.2°] vs. 124.6° [123.6°-125.6°], p = 0.001) and the femoral neck axis length (FNALb) was significantly longer (78.1 mm [77.0-79.2 mm] vs. 76.0 mm [74.8-77.2 mm], p = 0.026) in the fracture group than in the controls when genders were combined. The NSA was significantly smaller both for females (120.2° [117.8°-122.6°] vs. 124.7° [122.5°-127.0°], p = 0.007) and for males (122.7° [121.5°-123.8°] vs. 124.6° [123.4°-125.7°], p = 0.006) in the fracture group. However, only males showed a significantly longer FNALb (80.0 mm [78.9-81.1 mm] vs. 77.8 mm [76.6-79.0 mm], p = 0.025). No statistically significant associations of acetabular geometry with fractures were found. However, the mean values of the acetabular angle of Sharp (34°), the lateral center-edge angle (40°), the anterior center-edge angle (62°), and the posterior center-edge angle (105°) indicated possible over-coverage. In conclusion, our findings suggest that proximal femur geometry is associated with low-energy acetabular fractures. Especially elderly subjects with an NSA smaller than normal have an increased risk of acetabular fractures.

Quantitative imaging methods in osteoporosis

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Precision and Accuracy of Measurements on CT Scout View

OBJECTIVES

The purposes of this study were to (1) investigate the limits of measurements on scout view in three computed tomography axes, x, y and z and (2) develop a model to provide better understanding of measurement accuracy.

METHODS

For the first objective, anteroposterior and lateral scout views of a Catphan phantom 200 mm in diameter and length were acquired with a GE scanner at 21 different table heights. Phantom measurements on scout view were performed by two experienced readers. The comparison of their measures provided estimation of precision. The accuracy was assessed by determining the bias, calculated as the difference between the values measured on scout view and the real phantom size. Second, a model was developed investigating the relationship between the dimensions of the object, its image, and the table height. This relationship was tested on our data.

RESULTS

Scout view measurements were precise, with less than 0.53% difference between readers. In addition, small biases of about 1 mm were detected in the z-axis, whatever the table height. In the other axes, serious biases from -13 to +73 mm were measured. Furthermore, at isocentre, overestimations up to 7 mm were shown. The results also indicated that biases in scout view measurements are because of the geometrical projection related to the object-detector distance.

CONCLUSIONS

Measurements in the table movement axis are precise and accurate, conferring to scout views an added value for preoperative planning in orthopedic surgery.

Quantification of differences in bone texture from plain radiographs in knees with and without osteoarthritis

OBJECTIVE

To quantify differences in bone texture between subjects with different stages of knee osteoarthritis (OA) and age- and gender-matched controls from plain radiographs using advanced image analysis methods.

DESIGN

Altogether 203 knees were imaged using constant X-ray parameters and graded according to Kellgren-Lawrence (KL) grading scale (KL0: n = 110, KL1: n = 28, KL2: n = 27, KL3: n = 31, KL4: n = 7). Bone density-related and structure-related parameters were calculated from medial and lateral tibial subchondral bone plate and trabecular bone and from femur. Density-related parameters were derived from grayscale values and structure-related parameters from Laplacian- and local binary patterns (LBP)-based images.

RESULTS

Reproducibilities of structure-related parameters were better than bone density-related parameters. Bone density-related parameters were significantly (P < 0.05) higher in KL2-4 groups than in control group (KL0) in medial tibial subchondral bone plate and trabecular bone. LBP-based structure parameters differed significantly between KL0 and KL2-4 groups in medial subchondral bone plate, between KL0 and KL1-4 groups in medial and lateral trabecular bone, and between KL0 and KL1-4/KL2-4 in medial and lateral femur. Laplacian-based parameters differed significantly between KL0 and KL2-4 groups in medial side regions-of-interest (ROIs).

CONCLUSIONS

Our results indicate that the changes in bone texture in knee OA can be quantitatively evaluated from plain radiographs using advanced image analysis. Based on the results, increased bone density can be directly estimated if the X-ray imaging conditions are constant between patients. However, structural analysis of bone was more reproducible than direct evaluation of grayscale values, and is therefore better suited for quantitative analysis when imaging conditions are variable.

Assessment of risk of femoral neck fracture with radiographic texture parameters: a retrospective study

PURPOSE

To investigate whether femoral neck fracture can be predicted retrospectively on the basis of clinical radiographs by using the combined analysis of bone geometry, textural analysis of trabecular bone, and bone mineral density (BMD).

MATERIALS AND METHODS

Formal ethics committee approval was obtained for the study, and all participants gave informed written consent. Pelvic radiographs and proximal femur BMD measurements were obtained in 53 women aged 79-82 years in 2006. By 2012, 10 of these patients had experienced a low-impact femoral neck fracture. A Laplacian-based semiautomatic custom algorithm was applied to the radiographs to calculate the texture parameters along the trabecular fibers in the lower neck area for all subjects. Intra- and interobserver reproducibility was calculated by using the root mean square average coefficient of variation to evaluate the robustness of the method.

RESULTS

The best predictors of hip fracture were entropy (P = .007; reproducibility coefficient of variation < 1%), the neck-shaft angle (NSA) (P = .017), and the BMD (P = .13). For prediction of fracture, the area under the receiver operating characteristic curve was 0.753 for entropy, 0.608 for femoral neck BMD, and 0.698 for NSA. The area increased to 0.816 when entropy and NSA were combined and to 0.902 when entropy, NSA, and BMD were combined.

CONCLUSION

Textural analysis of pelvic radiographs enables discrimination of patients at risk for femoral neck fracture, and our results show the potential of this conventional imaging method to yield better prediction than that achieved with dual-energy x-ray absorptiometry-based BMD. The combination of the entropy parameter with NSA and BMD can further enhance predictive accuracy.