Xiaoguang Cheng

Pelvic body composition measurements by quantitative computed tomography: Association with recent hip fracture

INTRODUCTION Loss of subcutaneous fat, decreased muscle cross-sectional area (CSA) and increased muscle adiposity are related to declining physical function and disability in the elderly, but there is little information about the relationship of these tissue changes to hip fracture. Thus we have compared body composition measures in women with hip fractures to age-matched controls, using quantitative computed tomography (QCT) imaging of the hip to characterize total adiposity, muscle CSA and muscle attenuation coefficient, a measure of adiposity. MATERIALS AND METHODS 45 Chinese women (mean age 74.71+/-5.94) with hip fractures were compared to 66 healthy control subjects (mean age 70.70+/-4.66). Hip QCT scans were analyzed to compute total adipose CSA as well as CSA and attenuation values of muscle groups in the CT scan field of view, including hip extensors, abductors, adductors and flexors. The total femur areal BMD (aBMD) was estimated from the QCT images. Logistic regression was employed to compare body composition measures between fracture subjects and controls after adjustment for age, height, BMI and aBMD. Receiver-operator curve (ROC) analyses determined whether combinations of aBMD and body composition had higher area under curve (AUC) than aBMD alone. RESULTS AND CONCLUSIONS Fracture subjects had lower fat CSA (p<0.0001) than controls but had higher muscle adiposity as indicated by lower attenuation in the adductor, abductor and flexor groups (0.00001<p<0.02). Fracture subjects also had lower extensor and adductor CSA values (p<0.0001). After age and BMI adjustment, the total fat CSA, the extensor and adductor CSA values, and the adductor attenuation values remained significantly lower in the fracture subjects (0.001<p<0.05). In ROC analyses, models combining aBMD with soft tissue measures had higher AUC than models containing only BMD (0.001<p<0.05). Combining body composition with skeletal measures may improve fracture prediction compared to bone measures alone.

Identify fracture-critical regions inside the proximal femur using statistical parametric mapping

UNLABELLED We identified regions inside the proximal femur that are most strongly associated with hip fracture. Bone densitometry based on such fracture-critical regions showed improved power in discriminating fracture patients from controls. INTRODUCTION Hip fractures typically occur in lateral falls, with focal mechanical failure of the sub-volumes of tissue in which the applied stress exceeds the strength. In this study, we describe a new methodology to identify proximal femoral tissue elements with highest association with hip fracture. We hypothesize that bone mineral density (BMD) measured in such sub-volumes discriminates hip fracture risk better than BMD in standard anatomic regions such as the femoral neck and trochanter. MATERIALS AND METHODS We employed inter-subject registration to transform hip QCT images of 37 patients with hip fractures and 38 age-matched controls into a voxel-based statistical atlas. Within voxels, we performed t-tests between the two groups to identify the regions which differed most. We then randomly divided the 75 scans into a training set and a test set. From the training set, we derived a fracture-driven region of interest (ROI) based on association with fracture. In the test set, we measured BMD in this ROI to determine fracture discrimination efficacy using ROC analysis. Additionally, we compared the BMD distribution differences between the 29 patients with neck fractures and the 8 patients with trochanteric fractures. RESULTS By evaluating fracture discrimination power based on ROC analysis, the fracture-driven ROI had an AUC (area under curve) of 0.92, while anatomic ROIs (including the entire proximal femur, the femoral neck, trochanter and their cortical and trabecular compartments) had AUC values between 0.78 and 0.87. We also observed that the neck fracture patients had lower BMD (p=0.014) in a small region near the femoral neck and the femoral head, and patients with trochanteric fractures had lower BMD in trochanteric regions such as in the internal calcar septum (p=0.006). CONCLUSIONS We have identified the sub-volumes of proximal femoral tissue which have the strongest association with hip fracture. The power to predict fracture can be improved, by focusing on BMD measurements in the fracture-critical regions, rather than in standard ROIs.

Proximal femoral density distribution and structure in relation to age and hip fracture risk in women

Hip fracture risk rises exponentially with age, but there is little knowledge about how fracture‐related alterations in hip structure differ from those of aging. We employed computed tomography (CT) imaging to visualize the three‐dimensional (3D) spatial distribution of bone mineral density (BMD) in the hip in relation to age and incident hip fracture. We used intersubject image registration to integrate 3D hip CT images into a statistical atlas comprising women aged 21 to 97 years (n = 349) and a group of women with (n = 74) and without (n = 148) incident hip fracture 4 to 7 years after their imaging session. Voxel‐based morphometry was used to generate Students t test statistical maps from the atlas, which indicated regions that were significantly associated with age or with incident hip fracture. Scaling factors derived from intersubject image registration were employed as measures of bone size. BMD comparisons of young, middle‐aged, and older American women showed preservation of load‐bearing cortical and trabecular structures with aging, whereas extensive bone loss was observed in other trabecular and cortical regions. In contrast, comparisons of older Icelandic fracture women with age‐matched controls showed that hip fracture was associated with a global cortical bone deficit, including both the superior cortical margin and the load‐bearing inferior cortex. Bone size comparisons showed larger dimensions in older compared to younger American women and in older Icelandic fracture women compared to controls. The results indicate that older Icelandic women who sustain incident hip fracture have a structural phenotype that cannot be described as an accelerated pattern of normal age‐related loss. The fracture‐related cortical deficit noted in this study may provide a biomarker of increased hip fracture risk that may be translatable to dual‐energy X‐ray absorptiometry (DXA) and other clinical images.

Structural patterns of the proximal femur in relation to age and hip fracture risk in women

Fractures of the proximal femur are the most devastating outcome of osteoporosis. It is generally understood that age-related changes in hip structure confer increased risk, but there have been few explicit comparisons of such changes in healthy subjects to those with hip fracture. In this study, we used quantitative computed tomography and tensor-based morphometry (TBM) to identify three-dimensional internal structural patterns of the proximal femur associated with age and with incident hip fracture. A population-based cohort of 349 women representing a broad age range (21-97years) was included in this study, along with a cohort of 222 older women (mean age 79±7years) with (n=74) and without (n=148) incident hip fracture. Images were spatially normalized to a standardized space, and age- and fracture-specific morphometric features were identified based on statistical maps of shape features described as local changes of bone volume. Morphometric features were visualized as maps of local contractions and expansions, and significance was displayed as Students t-test statistical maps. Significant age-related changes included local expansions of regions low in volumetric bone mineral density (vBMD) and local contractions of regions high in vBMD. Some significant fracture-related features resembled an accentuated aging process, including local expansion of the superior aspect of the trabecular bone compartment in the femoral neck, with contraction of the adjoining cortical bone. However, other features were observed only in the comparison of hip fracture subjects with age-matched controls including focal contractions of the cortical bone at the superior aspect of the femoral neck, the lateral cortical bone just inferior to the greater trochanter, and the anterior intertrochanteric region. Results of this study support the idea that the spatial distribution of morphometric features is relevant to age-related changes in bone and independent to fracture risk. In women, the identification by TBM of fracture-specific morphometric alterations of the proximal femur, in conjunction with vBMD and clinical risk factors, may improve hip fracture prediction.

Bone fracture risk estimation based on image similarity.

We propose a fracture risk estimation technique based on image similarity. We employ image similarity indices to determine how images are similar to each other in their 3D bone mineral density distributions. Our premise for fracture risk estimation is that if a given scan is more similar to scans of subjects known to have fractures than to scans of control subjects, this subject is likely to have a higher degree of fracture risk. To test this hypothesis, we analyzed hip QCT scans of 37 patients with hip fractures and 38 age-matched controls. We divided the scans randomly into two groups: the Model Group and the Test Group. For each scan in the Test Group, the difference between the mean value of its image similarities to the Model fracture group and the mean value of its image similarities to the Model control group was used as index of fracture risk. We then used the estimated fracture risk indices to discriminate the fractured patients and controls in the Test Group. A test scan with a larger mean value of image similarities with respect to the Model fracture group was classified as a scan from a fractured patient, otherwise it was classified as a scan from a control subject. Based on ROC analysis, we compared the discrimination performances using image similarity measures with that obtained by using bone mineral density (BMD). When using BMD measured in the femoral neck, with the optimal BMD cutoff, the sensitivity and specificity were 86.5% and 73.7%. For the image similarity measures, the sensitivity ranged between 86.5% and 100%, and specificity ranged between 63.2% and 76.3%. By combining BMD with image similarity measures, the sensitivity and specificity reached 94.6% and 76.3% using linear discriminant analysis (LDA) algorithm, or 91.9% and 81.6% using recursive partitioning and regression trees (RPART) algorithm. In the RPART approach, the AUC value of the ROC curve was 0.923, higher than the AUC value of 0.835 when using BMD alone (p-value: 0.0046). Our results showed that combining BMD with image similarity measures resulted in improved hip fracture risk estimation.

Relation of Visceral and Subcutaneous Adipose Tissue to Bone Mineral Density in Chinese Women

The relationship between adipose and bone tissues is still being debated. The purpose of our study was to evaluate whether the distribution and volume of abdomen adipose tissue are correlated to trabecular bone mineral density in the lumbar spine. In this cross-sectional study, 320 Chinese women, being divided into two groups according to age ≥55 years and <55 years, were evaluated with quantitative computed tomography (QCT) of the spine to simultaneously evaluate the average trabecular BMD of L2–L4, VAT, and SAT. Possible covariates of height, weight, age, and comorbidities were considered. In the <55-year-old sample, multiple linear regression analyses indicated that VAT volume was negatively correlated to trabecular BMD (P value = 0.0003) and SAT volume had no correlation to trabecular BMD. In contrast, there was no significant correlation between VAT or SAT and BMD in the ≥55-year-old sample. Our results indicate that high VAT volume is associated with low BMD in Chinese women aged <55 years and SAT has no relation with BMD.

Hip fracture risk estimation based on principal component analysis of QCT atlas: a preliminary study

We aim to capture and apply 3-dimensional bone fragility features for fracture risk estimation. Using inter-subject image registration, we constructed a hip QCT atlas comprising 37 patients with hip fractures and 38 age-matched controls. In the hip atlas space, we performed principal component analysis to identify the principal components (eigen images) that showed association with hip fracture. To develop and test a hip fracture risk model based on the principal components, we randomly divided the 75 QCT scans into two groups, one serving as the training set and the other as the test set. We applied this model to estimate a fracture risk index for each test subject, and used the fracture risk indices to discriminate the fracture patients and controls. To evaluate the fracture discrimination efficacy, we performed ROC analysis and calculated the AUC (area under curve). When using the first group as the training group and the second as the test group, the AUC was 0.880, compared to conventional fracture risk estimation methods based on bone densitometry, which had AUC values ranging between 0.782 and 0.871. When using the second group as the training group, the AUC was 0.839, compared to densitometric methods with AUC values ranging between 0.767 and 0.807. Our results demonstrate that principal components derived from hip QCT atlas are associated with hip fracture. Use of such features may provide new quantitative measures of interest to osteoporosis.

Spatial Differences in the Distribution of Bone Between Femoral Neck and Trochanteric Fractures

There is little knowledge about the spatial distribution differences in volumetric bone mineral density and cortical bone structure at the proximal femur between femoral neck fractures and trochanteric fractures. In this case‐control study, a total of 93 women with fragility hip fractures, 72 with femoral neck fractures (mean ± SD age: 70.6 ± 12.7 years) and 21 with trochanteric fractures (75.6 ± 9.3 years), and 50 control subjects (63.7 ± 7.0 years) were included for the comparisons. Differences in the spatial distributions of volumetric bone mineral density, cortical bone thickness, cortical volumetric bone mineral density, and volumetric bone mineral density in a layer adjacent to the endosteal surface were investigated using voxel‐based morphometry (VBM) and surface‐based statistical parametric mapping (SPM). We compared these spatial distributions between controls and both types of fracture, and between the two types of fracture. Using VBM, we found spatially heterogeneous volumetric bone mineral density differences between control subjects and subjects with hip fracture that varied by fracture type. Interestingly, femoral neck fracture subjects, but not subjects with trochanteric fracture, showed significantly lower volumetric bone mineral density in the superior aspect of the femoral neck compared with controls. Using surface‐based SPM, we found that compared with controls, both fracture types showed thinner cortices in regions in agreement with the type of fracture. Most outcomes of cortical and endocortical volumetric bone mineral density comparisons were consistent with VBM results. Our results suggest: 1) that the spatial distribution of trabecular volumetric bone mineral density might play a significant role in hip fracture; 2) that focal cortical bone thinning might be more relevant in femoral neck fractures; and 3) that areas of reduced cortical and endocortical volumetric bone mineral density might be more relevant for trochanteric fractures in Chinese women.

Osteoporosis: what the clinician needs to know?

Osteoporosis is a common condition and an important cause of disability. For this reason, early detection of the disease and patients at higher risk of bone fractures is compulsory. In the recent years, conventional quantitative methods have been spreading for the diagnosis of osteoporosis; moreover, new improvements in computed tomography (CT) and magnetic resonance imaging (MRI) have been made in this field and imaging findings may correlate to the morphological and structural changes within the bone.

What is changed in the diagnosis of osteoporosis: the role of radiologists

Osteoporosis (OP) is a very common condition with several repercussions on patients’ quality of life and health systems (1). OP is secondary to changes in normal bone turnover for decreased activity of osteoblasts (which produce bone matrix) or increased osteoclastic activity (2,3). These changes determine variation in bone mineral content (BMC) and then bone mineral density (BMD); thus, quantification of BMD correlate to changes in bone matrix.