Bone shape, structure, and density as determinants of osteoporotic hip fracture: a pilot study investigating the combination of risk factors

Subchondral Bone Relative Area and Density in Human Osteoarthritic Femoral Heads Assessed with Micro-CT before and after Mechanical Embedding of the Innovative Multi-Spiked Connecting Scaffold for Resurfacing THA Endoprostheses: A Pilot Study

The multi-spiked connecting scaffold (MSC-Scaffold) prototype is the essential innovation in the fixation of components of resurfacing total hip arthroplasty (THRA) endoprostheses in the subchondral trabecular bone. We conducted the computed micro-tomography (micro-CT) assessment of the subchondral trabecular bone microarchitecture before and after the MSC-Scaffold embedding in femoral heads removed during long-stem endoprosthesis total hip arthroplasty (THA) of different bone densities from 4 patients with hip osteoarthritis (OA). The embedding of the MSC-Scaffold in subchondral trabecular bone causes the change in its relative area (BA/TA, bone area/total area ratio) ranged from 18.2% to 24.7% (translating to the calculated density ρ_B relative change 11.1–14.4%, and the compressive strength S relative change 75.3–122.7%) regardless of its initial density (before the MSC-Scaffold embedding). The densification of the trabecular microarchitecture of subchondral trabecular bone due to the MSC-Scaffold initial embedding gradually decreases with the increasing distance from the apexes of the MSC-Scaffold’s spikes while the spatial extent of this subchondral trabecular bone densification ranged from 1.5 to 2.5 mm (which is about half the height of the MSC-Scaffold’s spikes). It may be suggested, despite the limited number of examined femoral heads, that: (1) the magnitude of the effect of the MSC-Scaffold embedding on subchondral trabecular bone densification may be a factor contributing to the maintenance of the MSC-Scaffold also for decreased initial bone density values, (2) the deeper this effect of the subchondral trabecular bone densification, the better strength of subchondral trabecular bone, and as consequence, the better post-operative embedding of the MSC-Scaffold in the bone should be expected.

Hip Fracture Discrimination Based on Statistical Multi-parametric Modeling (SMPM)

Studies using quantitative computed tomography (QCT) and data-driven image analysis techniques have shown that trabecular and cortical volumetric bone mineral density (vBMD) can improve the hip fracture prediction of dual-energy X-ray absorptiometry areal BMD (aBMD). Here, we hypothesize that (1) QCT imaging features of shape, density and structure derived from data-driven image analysis techniques can improve the hip fracture discrimination of classification models based on mean femoral neck aBMD (Neck.aBMD), and (2) that data-driven cortical bone thickness (Ct.Th) features can improve the hip fracture discrimination of vBMD models. We tested our hypotheses using statistical multi-parametric modeling (SMPM) in a QCT study of acute hip fracture of 50 controls and 93 fragility fracture cases. SMPM was used to extract features of shape, vBMD, Ct.Th, cortical vBMD, and vBMD in a layer adjacent to the endosteal surface to develop hip fracture classification models with machine learning logistic LASSO. The performance of these classification models was evaluated in two aspects: (1) their hip fracture classification capability without Neck.aBMD, and (2) their capability to improve the hip fracture classification of the Neck.aBMD model. Assessments were done with 10-fold cross-validation, areas under the receiver operating characteristic curve (AUCs), differences of AUCs, and the integrated discrimination improvement (IDI) index. All LASSO models including SMPM-vBMD features, and the majority of models including SMPM-Ct.Th features performed significantly better than the Neck.aBMD model; and all SMPM features significantly improved the hip fracture discrimination of the Neck.aBMD model (Hypothesis 1). An interesting finding was that SMPM-features of vBMD also captured Ct.Th patterns, potentially explaining the superior classification performance of models based on SMPM-vBMD features (Hypothesis 2). Age, height and weight had a small impact on model performances, and the model of shape, vBMD and Ct.Th consistently yielded better performances than the Neck.aBMD models. Results of this study clearly support the relevance of bone density and quality on the assessment of hip fracture, and demonstrate their potential on patient and healthcare cost benefits.

Associations between body mass index across adult life and hip shapes at age 60 to 64: Evidence from the 1946 British birth cohort

OBJECTIVE

To examine the associations of body mass index (BMI) across adulthood with hip shapes at age 60-64years.

METHODS

Up to 1633 men and women from the MRC National Survey of Health and Development with repeat measures of BMI across adulthood and posterior-anterior dual-energy X-ray absorptiometry bone mineral density images of the proximal femur recorded at age 60-64 were included in analyses. Statistical shape modelling was applied to quantify independent variations in hip mode (HM), of which the first 6 were examined in relation to: i) BMI at each age of assessment; ii) BMI gain during different phases of adulthood; iii) age first overweight.

RESULTS

Higher BMI at all ages (i.e. 15 to 60-64) and greater gains in BMI were associated with higher HM2 scores in both sexes (with positive HM2 values representing a shorter femoral neck and a wider and flatter femoral head). Similarly, younger age first overweight was associated with higher HM2 scores but only in men once current BMI was accounted for. In men, higher BMI at all ages was also associated with lower HM4 scores (with negative HM4 values representing a flatter femoral head, a wider neck and smaller neck shaft angle) but no associations with BMI gain or prolonged exposure to high BMI were found. Less consistent evidence of associations was found between BMI and the other four HMs.

CONCLUSION

These results suggest that BMI across adulthood may be associated with specific variations in hip shapes in early old age.

ASSESSMENT OF OSTEOPOROTIC FEMORAL FRACTURE RISK: FINITE ELEMENT METHOD AS A POTENTIAL REPLACEMENT FOR CURRENT CLINICAL TECHNIQUES

Femoral fracture risk prediction is a necessary step preceding effective pharmacological intervention or pre-operative planning. Current clinical methods for fracture risk prediction rely on 2D imaging methods and have limited predictive value. Researchers are therefore trying to find improved methods for fracture prediction. During last few decades, many studies have focused on integration of 3D imaging techniques and the finite element (FE) method to improve the accuracy of fracture assessment techniques. In this paper, we review the recent advances in FE and other techniques for predicting the risk of femoral fractures. Based on a number of selected studies, the different steps that are involved in generation of patient-specific FE models are reviewed with particular emphasis on the fracture criteria. The inaccuracies that might arise due to the imperfections of the involved steps are also discussed. It is concluded that compared to image- and geometry-based techniques, FE is a more promising approach for prediction of fracture loads. However, certain technological advancements in FE modeling protocols are required before FE modeling can be recruited in clinical settings.

Fourier Transform Infrared Spectroscopic Imaging of Fracture Healing in the Normal Mouse

Fourier transform infrared spectroscopic imaging (FTIRI) was used to study bone healing with spatial analysis of various callus tissues in wild type mice. Femoral fractures were produced in 28 male C57BL mice by osteotomy. Animals were sacrificed at 1, 2, 4, and 8 weeks to obtain callus tissue at well-defined healing stages. Following microcomputerized tomography, bone samples were cut in consecutive sections for FTIRI and histology, allowing for spatial correlation of both imaging methods in different callus areas (early calcified cartilage, woven bone, areas of intramembranous and endochondral bone formation). Based on FTIRI, mineral/matrix ratio increased significantly during the first 4 weeks of fracture healing in all callus areas and correlated with bone mineral density measured by micro-CT. Carbonate/phosphate ratio was elevated in newly formed calcified tissue and at week 2 attained values comparable to cortical bone. Collagen maturity and mineral crystallinity increased during weeks 1-8 in most tissues while acid phosphate substitution decreased. Temporal and callus area dependent changes were detected throughout the healing period. These data assert the usefulness of FTIRI for evaluation of fracture healing in the mouse and its potential to evaluate pathologic fracture healing and the effects of therapeutic interventions.

Prevalent vertebral fractures on chest CT: higher risk for future hip fracture

Subclinical or undiagnosed vertebral fractures on routine chest computed tomography (CT) may be useful for detecting patients at increased risk of future hip fractures who might benefit from preventive interventions. We investigated whether prevalent vertebral fractures on routine chest CT are associated with future hip fractures. From a source population of 5679 patients ≥40 years old undergoing chest CT in one of three Dutch hospitals between 2002 and 2005, patients hospitalized for hip fractures (n = 149) during a median follow-up of 4.4 years were identified. Following a case-cohort design, a random sample of 576 patients was drawn from the source population and added to the cases. In this group, the presence and severity of vertebral fractures was determined using semiquantitative vertebral fracture assessment and multivariate case-cohort appropriate Cox modeling. We found that cases were older (69 versus 63 years) and more often female (48% versus 38%) than the source population. Compared with those with no fracture, patients with any vertebral fracture had triple the risk of future hip fracture (age- and gender-adjusted hazard ratio [HR] = 3.1, 95% confidence interval [CI] 2.1-4.7). This HR rose to 3.8 (CI 2.6-5.6) if mild fractures were discounted. Future fracture risk increased significantly with increasing severity of vertebral fracture status: from mild (HR = 2.4, CI 1.5-3.7) and moderate (HR = 4.8, CI 2.5-9.2) to severe (HR = 6.7, CI 2.9-15.5). The same was true for having higher cumulative fracture grades: 1 to 3 (HR = 2.7, CI 1.8-4.1), 4 to 6 (HR = 4.8, CI 2.2-10.5), or ≥7 (HR = 11.2, CI 3.7-34.6). In conclusion, prevalent vertebral fractures on routine clinical chest CT are associated with future hip fracture risk.

Computational anatomy in the study of bone structure

Osteoporosis is a major public health threat for millions of Americans with billions of dollars per year of national direct costs for osteoporotic fractures. Osteoporosis results in a decrease in overall bone mass and subsequent increase in the risk of bone fracture. Bone strength arises from the combination of bone size and shape, the distribution of bone mass throughout the structure, and the quality of the bone material. Advances in medical imaging have enabled a comprehensive assessment of bone structure through the analysis of high-resolution scans of relevant anatomical sites, eg, the proximal femur. However, conventional imaging analysis techniques use predefined regions of interest that do not take full advantage of such scans. Recently, computational anatomy, a set of imaging-based analysis algorithms, has emerged as a promising technique in studies of osteoporosis. Computational anatomy enables analyses that are not biased to one particular region and provide a more complete assessment of the whole structure. In this article, we review studies that have used computational anatomy to investigate the structure of the proximal femur in relation to age, fracture, osteoporotic treatment, and spaceflight effects.

Can we improve the prediction of hip fracture by assessing bone structure using shape and appearance modelling?

PURPOSE

There is a continuing need to improve the prediction of hip fractures to identify those at highest risk, enabling cost-effective use of preventative therapies.

METHODS

The aim of this work was to validate an innovative imaging biomarker for hip fracture by modelling the shape and texture of the proximal femur assessed from dual energy X-ray absorptiometry (DXA) scans. Scans used were acquired at baseline from elderly patients participating in a prospective, placebo-controlled fracture prevention study of the bisphosphonate, clodronate. 182 subjects who subsequently suffered a hip fracture were age, weight and height matched with two controls who did not suffer a fracture during a median 4-year follow-up period. Logistic regression was used to test if variables were good predictors of fracture and adjust for bone mineral density (BMD).

RESULTS

Shape mode 2, reflecting variability in neck-shaft angle, neck width and the size of both trochanters (0.81 (OR), 0.68-0.97 (CI), 0.024 (P)), and appearance mode 6, recording grey-level contrast (1.33, 1.11-1.59, 0.002), were significant predictors of hip fracture and remained so after adjustment for BMD (shape mode 2 (0.77, 0.64-0.93, 0.006), appearance mode 6 (1.32, 1.10-1.59, 0.003)). Receiver Operating Curve analysis showed the combination of shape mode 2, appearance mode 6 and BMD was 3% better than any single predictor.

CONCLUSION

Variables derived from shape and appearance models gave a prediction of fracture comparable to BMD and in combination with BMD gave an improvement in the prediction of hip fracture that could predict an additional 2000 hip fracture cases per year in the UK, potentially saving more than £20 million per year and 10,000 cases in the US.

Advances in bone imaging for osteoporosis

The diagnosis and management of osteoporosis have been improved by the development of new quantitative methods of skeletal assessment and by the availability of an increasing number of therapeutic options, respectively. A number of imaging methods exist and all have advantages and disadvantages. Dual-energy X-ray absorptiometry (DXA) is the most widely available and commonly utilized method for clinical diagnosis of osteoporosis and will remain so for the foreseeable future. The WHO 10-year fracture risk assessment tool (FRAX(®)) will improve clinical use of DXA and the cost-effectiveness of therapeutic intervention. Improved reporting of radiographic features that suggest osteoporosis and the presence of vertebral fracture, which are powerful predictors of future fractures, could increase the frequency of appropriate DXA referrals. Quantitative CT remains predominantly a research tool, but has advantages over DXA--allowing measurement of volumetric density, separate measures of cortical and trabecular bone density, and evaluation of bone shape and size. High resolution imaging, using both CT and MRI, has been introduced to measure trabecular and cortical bone microstructure. Although these methods provide detailed insights into the effects of disease and therapies on bone, they are technically challenging and not widely available, so they are unlikely to be used in clinical practice.

Hip fracture discrimination from dual-energy X-ray absorptiometry by statistical model registration

Although the areal Bone Mineral Density (BMD) measurements from dual-energy X-ray absorptiometry (DXA) are able to discriminate between hip fracture cases and controls, the femoral strength is largely determined by the 3D bone structure. In a previous work a statistical model was presented which parameterizes the 3D shape and BMD distribution of the proximal femur. In this study the parameter values resulting from the registration of the model onto DXA images are evaluated for their hip fracture discrimination ability with respect to regular DXA derived areal BMD measurements. The statistical model was constructed from a large database of QCT scans of females with an average age of 67.8 ± 17.0 years. This model was subsequently registered onto the DXA images of a fracture and control group. The fracture group consisted of 175 female patients with an average age of 66.4 ± 9.9 years who suffered a fracture on the contra lateral femur. The control group consisted of 175 female subjects with an average age of 65.3 ± 10.0 years and no fracture history. The discrimination ability of the resulting model parameter values, as well as the areal BMD measurements extracted from the DXA images were evaluated using a logistic regression analysis. The area under the receiver operating curve (AUC) of the combined model parameters and areal BMD values was 0.840 (95% CI 0.799-0.881), whilst using only the areal BMD values resulted in an AUC of 0.802 (95% CI 0.757-0.848). These results indicate that the discrimination ability of the areal BMD values is improved by supplementing them with the model parameter values, which give a more complete representation of the subject specific shape and internal bone distribution. Thus, the presented method potentially allows for an improved hip fracture risk estimation whilst maintaining DXA as the current standard modality.

Shape-based assessment of vertebral fracture risk in postmenopausal women using discriminative shape alignment

RATIONALE AND OBJECTIVES

Risk assessment of future osteoporotic vertebral fractures is currently based mainly on risk factors, such as bone mineral density, age, prior fragility fractures, and smoking. It can be argued that an osteoporotic vertebral fracture is not exclusively an abrupt event but the result of a decaying process. To evaluate fracture risk, a shape-based classifier, identifying possible small prefracture deformities, may be constructed.

MATERIALS AND METHODS

During a longitudinal case-control study, a large population of postmenopausal women, fracture free at baseline, were followed. The 22 women who sustained at least one lumbar fracture on follow-up represented the case group. The control group comprised 91 women who maintained skeletal integrity and matched the case group according to the standard osteoporosis risk factors. On radiographs, a radiologist and two technicians independently performed manual annotations of the vertebrae, and fracture prediction using shape features extracted from the baseline annotations was performed. This was implemented using posterior probabilities from a standard linear classifier.

RESULTS

The classifier tested on the study population quantified vertebral fracture risk, giving statistically significant results for the radiologist annotations (area under the curve, 0.71 ± 0.013; odds ratio, 4.9; 95% confidence interval, 2.94-8.05).

CONCLUSIONS

The shape-based classifier provided meaningful information for the prediction of vertebral fractures. The approach was tested on case and control groups matched for osteoporosis risk factors. Therefore, the method can be considered an additional biomarker, which combined with traditional risk factors can improve population selection (eg, in clinical trials), identifying patients with high fracture risk.

Active shape modeling of the hip in the prediction of incident hip fracture

The objective of this study was to evaluate right proximal femur shape as a risk factor for incident hip fracture using active shape modeling (ASM). A nested case-control study of white women 65 years of age and older enrolled in the Study of Osteoporotic Fractures (SOF) was performed. Subjects (n = 168) were randomly selected from study participants who experienced hip fracture during the follow-up period (mean 8.3 years). Controls (n = 231) had no fracture during follow-up. Subjects with baseline radiographic hip osteoarthritis were excluded. ASM of digitized right hip radiographs generated 10 independent modes of variation in proximal femur shape that together accounted for 95% of the variance in proximal femur shape. The association of ASM modes with incident hip fracture was analyzed by logistic regression. Together, the 10 ASM modes demonstrated good discrimination of incident hip fracture. In models controlling for age and body mass index (BMI), the area under receiver operating characteristic (AUROC) curve for hip shape was 0.813, 95% confidence interval (CI) 0.771-0.854 compared with models containing femoral neck bone mineral density (AUROC = 0.675, 95% CI 0.620-0.730), intertrochanteric bone mineral density (AUROC = 0.645, 95% CI 0.589-0.701), femoral neck length (AUROC = 0.631, 95% CI 0.573-0.690), or femoral neck width (AUROC = 0.633, 95% CI 0.574-0.691). The accuracy of fracture discrimination was improved by combining ASM modes with femoral neck bone mineral density (AUROC = 0.835, 95% CI 0.795-0.875) or with intertrochanteric bone mineral density (AUROC = 0.834, 95% CI 0.794-0.875). Hips with positive standard deviations of ASM mode 4 had the highest risk of incident hip fracture (odds ratio = 2.48, 95% CI 1.68-3.31, p < .001). We conclude that variations in the relative size of the femoral head and neck are important determinants of incident hip fracture. The addition of hip shape to fracture-prediction tools may improve the risk assessment for osteoporotic hip fractures.

Prediction of the fracture load of whole proximal femur specimens by topological analysis of the mineral distribution in DXA-scan images

OBJECTIVE

To evaluate scanner-generated images of hip specimens obtained from dual energy X-ray absorptiometry (DXA) by quantitative image analysis of bone mineral distribution in the standard regions of interest (ROI), to predict the ultimate mechanical strength, and to compare the predictive potential with standard densitometry.

MATERIALS AND METHODS

Femoral bone mineral density (BMD) of 100 hip specimens was obtained by DXA in the total hip, shaft, trochanteric, and neck ROI. Maximum compressive strength (MCS) of the specimens was measured in a mechanical loading device simulating a fall on the greater trochanter. The topology of bone mineral distribution in the scan images was evaluated by image processing methods based on the Minkowski functionals (MF) using the optimized topological parameter MF2D. Correlation and multivariate analysis were employed to assess the statistical potential of BMD and MF2D with respect to predict the mechanical strength of the femur specimens.

RESULTS

R2 for the correlation between load-to-failure and BMD varied between 0.73 and 0.79 (exponential curve fit, p<0.001), being highest in the trochanteric ROI. Correlation between load-to-failure of the specimens with the topological parameter MF2D ranged from R2 =0.8 to 0.91 (p<0.001). In a multivariate model combining the topological information from all ROIs, correlation with MCS rose to R2 =0.94.

CONCLUSION

The topological parameter MF2D can be employed to predict the mechanical strength of proximal femur specimens from DXA-generated images. Performance is superior to standard evaluation of DXA. In the future, the proposed image processing method may serve to improve the assessment of an individual's fracture risk.

Characterizing the shape of the lumbar spine using an active shape model: reliability and precision of the method

STUDY DESIGN

Analysis of positional magnetic resonance images of normal volunteers.

OBJECTIVE

To compare the reliability and precision of an active shape model to that of conventional lordosis measurements.

SUMMARY OF BACKGROUND DATA

Characterization of lumbar lordosis commonly relies on measurement of angles; these have been found to have errors of around 10 degrees .

METHODS

T2 weighted sagittal images of the lumbar spines of 24 male volunteers in the standing posture were acquired using a positional magnetic resonance scanner. An active shape model of the vertebral bodies from S1 to L1 was created. Lumbar lordosis was also determined by measuring the angles of the superior endplates. All measurements were performed twice by one observer and once by a second observer.

RESULTS

The shape model identified 2 modes of variation to describe the shape of the lumbar spine (mode 1 described curvature and mode 2 described evenness of curvature). Significant correlations were found between mode 1 and total lordosis (R = 0.97, P < 0.001) and between mode 2 and mean absolute deviation of segmental lordosis (R = 0.80, P < 0.001). Intra- and interobserver reliability was higher for the shape model (intraclass correlation coefficients, 0.98-1.00) than for the lordosis angle measurements (intraclass correlation coefficients, 0.68-0.99). The relative error of the shape model (mode 1 = 4%; mode 2 = 9%) was lower than the conventional measurements (total lordosis = 10%).

CONCLUSION

The shape of the lumbar spine in the sagittal plane can be comprehensively characterized using a shape model. The results are more reliable and precise than measurements of lordosis calculated from endplate angles.

Bone density and geometry in assessing hip fracture risk in post-menopausal women

We used femoral neck structural parameters (FNSPs), calculated from bone mineral density (BMD) measurements of the femoral neck by dual X-ray absorptiometry, to discriminate osteoporotic fractures of the proximal femur in post-menopausal women. We compared 1646 women without fracture and 429 women with hip fractures, including 273 with femoral neck (FN) and 156 with trochanter (TR) fractures. The association between the studied parameters and the fractures was modelled using multiple logistic regression, and included age, height and weight. Fracture-predicted probability (FPP) was also calculated for each predictor tested. Receiver operating characteristic (ROC) curve areas with their standard errors (SEs) were calculated for the fracture status, having the calculated FPP as a test variable. The areas were compared by the Hanley-McNeil test. Hip fracture had lower BMD, cross-sectional area (CSA), section modulus (SM) and cortical thickness (CT), and higher buckling ratio (BR), than controls. To the same extent as FN BMD, BR best predicted the risk for each fracture, showing ROC curve areas of 0.809 (SE 0.011) for hip fracture, 0.789 (SE 0.014) for FN fracture, and 0.848 (SE 0.016) for TR fracture. The association of BR with fracture risk did not differ from that of FN BMD, which has a ROC curve area of 0.801 (SE 0.011) for hip fracture, 0.778 (SE 0.014) for FN fracture, and 0.852 (SE 0.016) for TR fracture. Both FN BMD and BR predicted TR fracture significantly better than they did FN fracture. FNSPs, although interesting in understanding the biomechanics of bone fragility, do not appear to add diagnostic value to the simple measurement of BMD.

Differentiation between post-menopausal women with and without hip fractures: enhanced evaluation of clinical DXA by topological analysis of the mineral distribution in the scan images

We introduce an algorithm to evaluate hip DXA scans using quantitative image analysis procedures based on the Minkowski functionals (MF) for differentiation between post-menopausal women with and without hip fracture. In a population of 30 post-menopausal women, the new parameter has a highly discriminative potential with a performance superior to standard densitometry providing complementary information compared to BMD.

INTRODUCTION

We introduce a novel algorithm to evaluate DXA scans of the hip using quantitative image analysis based on the Minkowski functionals (MF) to identify post-menopausal women with hip-fracture and to compare the results with densitometry.

METHODS

BMD of 30 women (73.9 +/- 10.3 years), 15 of whom had a recent hip fracture, is obtained by DXA using the "total hip" ROI. The topology of mineral distribution in the scan images is evaluated using the MF-based parameter MF2D. ROC analysis is employed to assess the discriminative potential (fracture/non-fracture).

RESULTS

The area-under-the-curve (AUC) for identification of patients with/without fractures by BMD is .72(p = 0.04), AUC for MF2D is .85(p = 0.001). No statistically significant correlation exists between MF2D and BMD. By discriminant analysis we can show that by combination of MF2D and BMD the outcome increases significantly: using BMD or MF2D alone, 63% and 70% of cases are classified correctly versus 77% of cases in the multivariate model.

CONCLUSION

The topology-based parameter has a high predictive potential with respect to identification of patients with high risk of hip fracture, performance is superior to densitometry. The new method provides information complementary to BMD. Best classification results are obtained when BMD and MF2D are combined in a multivariate model.

Vertebral Morphometry

OBJECTIVES

Manual point placement for vertebral morphometry is time-consuming and imprecise. We evaluated the accuracy of semiautomatic computer determination of the detailed vertebral shape.

MATERIALS AND METHODS

The shape and appearance of vertebrae on 250 lateral dual-energy x-ray absorptiometry (DXA) scans were statistically modeled using a sequence of active appearance models of vertebral triplets. The models were matched to unseen scans given an approximate initial location of the center of each vertebra. The segmentation accuracy was analyzed by fracture grade.

RESULTS

Segmentation accuracy comparable to manual precision was obtained in the case of normal vertebrae, but the accuracy decreased with increasing fracture severity. We propose methods for improving the robustness for severe fractures.

CONCLUSION

Vertebral morphometry measurements may be substantially automated even on noisy data with multiple fractures present. The shape and appearance parameters of the models could provide more powerful quantitative classifiers of osteoporotic vertebral fracture.

Computerized quantification of joint space narrowing and periarticular demineralization in patients with rheumatoid arthritis based on digital x-ray radiogrammetry

OBJECTIVES

The aim of our work was to evaluate digital x-ray radiogrammetry (DXR) for the quantification of disease-related periarticular demineralization and computerized analysis of joint space distances (JSDA) for the measurement of joint space narrowing as a new diagnostic method for the early detection of joint-associated alterations and for monitoring disease progression in patients with rheumatoid arthritis (RA).

MATERIALS AND METHODS

Digital radiographs in 313 patients with varying severity of RA were performed annually and assessed by 2 radiologists using modified Larsen and also the Sharp scores within an observation period of 3 years. The hand radiographs underwent measurements of bone mineral density (BMD) and metacarpal index (MCI) by DXR, as well as computerized JSDA at the metacarpal-phalangeal articulation (JSD-MCP) for a cross-sectional and longitudinal study design.

RESULTS

Both DXR-BMD (-29.6%; P < 0.01) and DXR-MCI (-31.0%; P < 0.01) revealed a notable reduction dependent on the severity of RA (from grade 1 to grade 5 of the modified Larsen score); the severity dependent decrease of mean JSD-MCP ranged from -31.9% (P < 0.01; Sharp erosion part) to -39.1% (P < 0.01) for the modified Larsen score. Over an observation period of 3 years, a significant decrease of DXR-BMD (-22.3%) and DXR-MCI (-23.3%) as well as JSD-MCP mean (-17.5%) was observed (P < 0.05), whereas an accentuated decline of DXR and JSDA parameters was verified for patients without disease-modifying antirheumatic drugs or methotrexate therapy.

CONCLUSION

Computerized analysis of hand radiographs by DXR and JSDA is a promising approach to assess the severity and to monitor the progression of RA because DXR and JSDA are timely able to measure periarticular demineralization and also narrowing of JSD-MCP dependent on the severity, the medical treatment and the course of RA.