People living with HIV have low trabecular bone mineral density, high bone marrow adiposity, and poor trabecular bone microarchitecture at the proximal femur.

People living with HIV (PLWH) have increased risk of osteoporosis and fractures. We assessed the proximal femur of PLWH and age-matched seronegative controls using quantitative computed tomography and magnetic resonance imaging. Results suggest that the trabecular compartment is compromised at fracture-prone regions in the proximal femur of PLWH. INTRODUCTION: People living with HIV (PLWH) have increased risk of osteoporosis and fractures. However, studies assessing the main determinants of bone strength in the proximal femur exclude this vulnerable population. We assessed the proximal femur of 40 PLWH and 26 age-matched seronegative controls using quantitative computed tomography and magnetic resonance imaging. METHODS: We examined cortical volumetric bone mineral density (Ct.vBMD), trabecular vBMD (Tb.vBMD), cortical thickness (Ct.Th), bone marrow adiposity (BMA), and trabecular number, separation, and bone volume fraction. Parametric comparisons between the two groups were made for the femoral head, femoral neck, trochanter, and total hip using linear regression adjusting for several covariates, including metrics of body composition. In addition, we investigated the associations of BMA with Tb.vBMD and trabecular microarchitecture with Spearman's rank partial correlations. RESULTS: PLWH had lower Tb.vBMD and deteriorated trabecular microarchitecture in the femoral neck, trochanter and total hip, and elevated BMA in the femoral head, femoral neck, and total hip. Ct.vBMD and Ct.Th were not significantly different between the two groups. BMA was significantly associated with lower Tb.vBMD and deteriorated trabecular microarchitecture in both groups albeit at different femoral regions. CONCLUSIONS: Our findings suggest that the trabecular, and not the cortical, compartment is compromised in the proximal femur of PLWH. The observed impairments in fracture-prone regions in PLWH indicate lower femoral strength and suggest higher fracture risk. The inverse associations of BMA with trabecular bone density and microarchitecture quality agree with findings at other anatomic sites and in other populations, suggesting that excess BMA possibly due to a switch from the osteoblast to the adipocyte lineage may be implicated in the pathogenesis of bone fragility at the femur in PLWH.

Baseline mean and heterogeneity of MR cartilage T2 are associated with morphologic degeneration of cartilage, meniscus, and bone marrow over 3 years--data from the Osteoarthritis Initiative.

OBJECTIVE: The purpose of this study is to determine whether the mean and heterogeneity of magnetic resonance (MR) knee cartilage T(2) relaxation time measurements at baseline are associated with morphologic degeneration of cartilage, meniscus, and bone marrow tissues over 3 years in subjects with risk factors for osteoarthritis (OA). DESIGN: Subjects with risk factors for OA (n=289) with an age range of 45-55 years were selected from the Osteoarthritis Initiative (OAI) database. 3.0 Tesla MR images were analyzed using morphological gradings of cartilage, bone marrow and menisci whole-organ magnetic resonance imaging scores (WORMS scoring). A T(2) mapping sequence was used to assess the mean and heterogeneity of cartilage T(2) (gray level co-occurrence matrix texture analysis). Regression models were used to assess the relationship between baseline T(2) parameters and changes in morphologic knee WORMS scores over 3 years. RESULTS: The prevalence of knee abnormalities in the cartilage (P<0.0005), meniscus (P<0.00001), and bone marrow significantly (P<0.00001) increased from baseline to 3 years in all compartments combined. The baseline mean and heterogeneity of cartilage T(2) were significantly (P<0.05) associated with morphologic joint degeneration in the cartilage, meniscus and bone marrow over 3 years. CONCLUSIONS: The prevalence of knee abnormalities significantly increased over 3 years; increased cartilage T(2) at baseline predicted longitudinal morphologic degeneration in the cartilage, meniscus, and bone marrow over 3 years in subjects with risk factors for OA.

A novel fast knee cartilage segmentation technique for T2 measurements at MR imaging--data from the Osteoarthritis Initiative.

Magnetic resonance imaging (MRI) T(2) relaxation time assesses non-invasively cartilage composition and can be used as early biomarker for knee osteoarthritis. Most knee cartilage segmentation techniques were primarily developed for volume measurements in DESS or SPGR sequences. For T(2) quantifications, these segmentations need to be superimposed on T(2) maps. However, given that these procedures are time consuming and require manual alignment, using them for analysis of T(2) maps in large clinical trials like the Osteoarthritis Initiative (OAI) is challenging. A novel direct segmentation technique (DST) for T(2) maps was therefore developed. Using the DST, T(2) measurements were performed and compared with those determined with an established segmentation superimposition technique (SST). MR images of five OAI participants were analysed with both techniques three times by one reader and five different images sets additionally with DST three times by two readers. Segmentations and T(2) measurements of one knee required on average 63±3min with DST (vs 302±13min for volume and T(2) measurements with SST). Bland-Altman plots indicated good agreement between the two segmentation techniques, respectively the two readers. Reproducibility errors of both techniques (DST vs SST) were similar (P>0.05) for whole knee cartilage mean T(2) (1.46% vs 2.18%), laminar (up to 2.53% vs 3.19%) and texture analysis (up to 8.34% vs 9.45%). Inter-reader reproducibility errors of DST were higher for texture analysis (up to 15.59%) than for mean T(2) (1.57%) and laminar analysis (up to 2.17%). Due to these results, the novel DST can be recommended for T(2) measurements in large clinical trials like the OAI.

Automated 3D trabecular bone structure analysis of the proximal femur--prediction of biomechanical strength by CT and DXA.

SUMMARY: The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone. INTRODUCTION: An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique. METHODS: One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter. RESULTS: The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone. CONCLUSION: A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs.

PURPOSE: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between various different texture analysis methods and the femurs' anchorage strength. METHODS: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. RESULTS: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R2=0.61 (MF and MG features, p<0.01) and were partially independent of BMD. The correlations were dependent on the choice of the ROI and the texture measure. The best predictive multiregression model for failure load R2adj=0.86 (p<0.001) included a set of recently developed texture methods (MF and SIM) but excluded bone mineral density and commonly used texture measures. CONCLUSIONS: The results suggest that texture information contained in trabecular bone structure visualized on radiographs may predict whether an implant anchorage can be used and may determine the local bone quality from preoperative radiographs.

The feasibility of characterizing the spatial distribution of cartilage T(2) using texture analysis.

OBJECTIVE: The purpose of this study was (1) to characterize the spatial distribution of cartilage T(2) in postmenopausal osteoarthritis (OA) patients and age-matched healthy subjects using second order texture measures at baseline, and (2) to analyze changes in the texture of cartilage T(2) after 9 months. METHODS: 3.0T-MRI of the knee was performed in 8 mild OA patients and 10 age-matched controls at baseline and after 9 months. Cartilage T(2), volume, and average thickness were calculated in all patients. Texture analysis, based on the gray level co-occurrence matrix, was performed on the cartilage T(2) maps. Texture parameters, including entropy and angular second moment, were calculated at 0 degrees (corresponding to the anterior-posterior axis) and at 90 degrees (corresponding to the superior-inferior axis), with pixel offsets ranging from 1 to 3 pixels. RESULTS: Least square means analysis showed that mean T(2) values, their standard deviation (SD), and their entropy were greater (P<0.05) in OA patients than in controls. Over 9 months, the SD and entropy of cartilage T(2) significantly (P<0.05) decreased in OA patients, while no significant changes were evident in cartilage thickness or volume. CONCLUSION: The mean cartilage T(2) values, their SD, and their entropy were greater in OA patients than in controls, indicating that the T(2) values in osteoarthritic cartilage are not only elevated, but also more heterogeneous than those in healthy cartilage. The longitudinal results demonstrate that changes in texture parameters of cartilage T(2) may precede morphological changes in thickness and volume in the progression of OA.

Assessment of trabecular bone structure comparing magnetic resonance imaging at 3 Tesla with high-resolution peripheral quantitative computed tomography ex vivo and in vivo.

UNLABELLED: In vivo high-resolution peripheral quantitative micro-CT (HR-pQCT) is a new modality for imaging peripheral sites like the distal tibia and the distal radius, providing structural bone parameters. Comparing HR-pQCT with MRI, we found that both modalities are capable of offering meaningful information on trabecular structure. BACKGROUND: Magnetic resonance imaging (MRI) has emerged as the leading in vivo method for measuring trabecular bone micro-architecture and providing structural information. Recently, an in vivo HR-pQCT modality was introduced for imaging peripheral sites like the distal tibia and the distal radius, providing structural bone parameters. The goal of this work was to compare and evaluate the performances and in vivo capabilities of HR-pQCT in comparison with MRI at 3 Tesla. METHODS: To this end images of 8 human specimens (5 tibiae and 3 radii) and 11 participants (6 tibia and 5 radii) were acquired with both modalities. Additionally, the radius specimens were scanned with micro-CT (muCT), which was used as a standard of reference. Structural parameters calculated from MRI were compared with results from HR-pQCT images and additionally muCT for the radii specimens. RESULTS: High correlations (r > 0.7) were found for trabecular number and trabecular spacing between the two modalities in vivo and ex vivo. 2D and 3D analysis revealed high correlations (r > 0.8) in structural bone parameters for all measurements. Using micro-CT as standard of reference both results from QCT and MRI correlated well. CONCLUSION: Both imaging modalities were found to perform equally well regarding trabecular bone measurements.

MRI-derived T2 relaxation times and cartilage morphometry of the tibio-femoral joint in subjects with and without osteoarthritis during a 1-year follow-up.

OBJECTIVE: To assess differences in magnetic resonance imaging (MRI)-based compositional (T2) and morphometric (volume and thickness) parameters of the tibio-femoral joint cartilage in subjects with and without osteoarthritis (OA) and compare these with clinical assessment tools during a 1-year follow-up. METHOD: Three Tesla MRI of the knee joint was performed in eight female patients (body mass index [BMI]>30) with early OA and 10 age-matched female controls (BMI<30) at baseline (BL) and after 3, 6 and 12 months. Cartilage T2 maps, volume and average thickness were calculated in five compartments (medial/lateral femoral condyle, medial/lateral tibia and trochlea). These data were correlated with changes in clinical parameters and joint space width determined in standardized knee radiographs using a mixed random effects model. RESULTS: At BL, T2 was significantly higher (P<0.05) across the cartilage in patients (45.68+/-5.17ms) compared to controls (41.75+/-4.33ms). Patients had significantly (P<0.05) less cartilage volume and less average cartilage thickness in the tibia than controls (2.10+/-0.53cm(3) vs 2.91+/-0.49cm(3) and 1.59+/-0.24mm vs 1.90+/-0.29mm, respectively). A significant change in clinical parameters of OA, cartilage T2 values or a decrease of volume and average thickness could not be demonstrated within both groups. CONCLUSION: Significant differences between the groups indicate that both T2 and morphometric parameters may be useful in quantifying early OA related changes. In a 12-month follow-up, however, no significant alterations of the studied parameters were found, which may be due to the length of the observation interval.

In vivo T(1rho) and T(2) mapping of articular cartilage in osteoarthritis of the knee using 3 T MRI.

OBJECTIVE: Evaluation and treatment of patients with early stages of osteoarthritis (OA) is dependent upon an accurate assessment of the cartilage lesions. However, standard cartilage dedicated magnetic resonance (MR) techniques are inconclusive in quantifying early degenerative changes. The objective of this study was to determine the ability of MR T1rho (T(1rho)) and T(2) mapping to detect cartilage matrix degeneration between normal and early OA patients. METHOD: Sixteen healthy volunteers (mean age 41.3) without clinical or radiological evidence of OA and 10 patients (mean age 55.9) with OA were scanned using a 3Tesla (3T) MR scanner. Cartilage volume and thickness, and T(1rho) and T(2) values were compared between normal and OA patients. The relationship between T(1rho) and T(2) values, and Kellgren-Lawrence scores based on plain radiographs and the cartilage lesion grading based on MR images were studied. RESULTS: The average T(1rho) and T(2) values were significantly increased in OA patients compared with controls (52.04+/-2.97ms vs 45.53+/-3.28ms with P=0.0002 for T(1rho), and 39.63+/-2.69ms vs 34.74+/-2.48ms with P=0.001 for T(2)). Increased T(1rho) and T(2) values were correlated with increased severity in radiographic and MR grading of OA. T(1rho) has a larger range and higher effect size than T(2), 3.7 vs 3.0. CONCLUSION: Our results suggest that both in vivo T(1rho) and T(2) relaxation times increase with the degree of cartilage degeneration. T(1rho) relaxation time may be a more sensitive indicator for early cartilage degeneration than T(2). The ability to detect early cartilage degeneration prior to morphologic changes may allow us to critically monitor the course of OA and injury progression, and to evaluate the success of treatment to patients with early stages of OA.

Wavelet Based Characterization of Vertebral Trabecular Bone Structure from MR Images of Specimen at 3 Tesla Compared to MicroCT Measurements.

Trabecular bone structure and bone density contribute to the strength of bone and are important in the study of osteoporosis. Wavelets are a powerful tool to characterize and quantify texture in an image. In this study the thickness of trabecular bone was analyzed in 8 cylindrical cores of the vertebral spine. Images were obtained from 3 Tesla (T) magnetic resonance imaging (MRI) and micro-computed tomography (μCT). Results from the wavelet based analysis of trabecular bone were compared with standard two-dimensional (2D) structural parameters (analogous to bone histomorphometry) obtained using mean intercept length (MR images) and direct three-dimensional (3D) distance transformation methods (μCT images). Additionally, the bone volume fraction was determined from MR images. We conclude that the wavelet based analyses delivers comparable results to the established MR histomorphometric measurements. The average deviation in trabecular thickness was less than one pixel size between the wavelet and the standard approach for both MR and μCT analysis. Since the wavelet based method is less sensitive to image noise, we see an advantage of wavelet analysis of trabecular bone for MR imaging when going to higher resolution.

Quantification of breast tissue index from MR data using fuzzy clustering.

The study objective was to develop a segmentation technique to quantify breast tissue and total breast volume from magnetic resonance imaging (MRI) data to obtain a breast tissue index (BTI) related to breast density. Our goal is to quantify MR breast density to improve breast cancer risk assessment for certain high-risk populations for whom mammography is of limited usefulness due to high breast density. A semi-automatic 3D segmentation technique was implemented based on a fuzzy c-means technique (FCM) to segment fibroglandular tissue from fat in the breast images. After validation on a phantom, our FCM technique was first used to test the breast tissue measures reproducibility in two consecutive MR examinations of the same patients. The technique was then applied to measure the BTI on 10 high-risk patients. Results of BTI obtained with the semi-automated FCM method were compared with BTI results for the same patients using two other techniques, manual delineation and global threshold. BTI measures correlated well with mammographic densities (Pearson coefficients r = 0.78 using MR manual delineation, and r = 0.75 using MR FCM). The breast tissue index could therefore become a common measure for future studies of using noncontrast MRI data.