Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis

The purposes of this study were to investigate: 1) the effect of placement of region-of-interest (ROI) for texture analysis of subchondral bone in knee radiographs, and 2) the ability of several texture descriptors to distinguish between the knees with and without radiographic osteoarthritis (OA). Bilateral posterior-anterior knee radiographs were analyzed from the baseline of OAI and MOST datasets. A fully automatic method to locate the most informative region from subchondral bone using adaptive segmentation was developed. We used an oversegmentation strategy for partitioning knee images into the compact regions that follow natural texture boundaries. LBP, Fractal Dimension (FD), Haralick features, Shannon entropy, and HOG methods were computed within the standard ROI and within the proposed adaptive ROIs. Subsequently, we built logistic regression models to identify and compare the performances of each texture descriptor and each ROI placement method using 5-fold cross validation setting. Importantly, we also investigated the generalizability of our approach by training the models on OAI and testing them on MOST dataset.We used area under the receiver operating characteristic (ROC) curve (AUC) and average precision (AP) obtained from the precision-recall (PR) curve to compare the results. We found that the adaptive ROI improves the classification performance (OA vs. non-OA) over the commonly used standard ROI (up to 9% percent increase in AUC). We also observed that, from all texture parameters, LBP yielded the best performance in all settings with the best AUC of 0.840 [0.825, 0.852] and associated AP of 0.804 [0.786, 0.820]. Compared to the current state-of-the-art approaches, our results suggest that the proposed adaptive ROI approach in texture analysis of subchondral bone can increase the diagnostic performance for detecting the presence of radiographic OA

Quantifying the Tibiofemoral Joint Space Using X-ray Tomosynthesis

Purpose: Digital x-ray tomosynthesis (DTS) has the potential to provide 3D information about the knee joint in a load-bearing posture, which may improve diagnosis and monitoring of knee osteoarthritis compared with projection radiography, the current standard of care. Manually quantifying and visualizing the joint space width (JSW) from 3D tomosynthesis datasets may be challenging. This work developed a semiautomated algorithm for quantifying the 3D tibiofemoral JSW from reconstructed DTS images. The algorithm was validated through anthropomorphic phantom experiments and applied to three clinical datasets. Methods: A user-selected volume of interest within the reconstructed DTS volume was enhanced with 1D multiscale gradient kernels. The edge-enhanced volumes were divided by polarity into tibial and femoral edge maps and combined across kernel scales. A 2D connected components algorithm was performed to determine candidate tibial and femoral edges. A 2D joint space width map (JSW) was constructed to represent the 3D tibiofemoral joint space. To quantify the algorithm accuracy, an adjustable knee phantom was constructed, and eleven posterior–anterior (PA) and lateral DTS scans were acquired with the medial minimum JSW of the phantom set to 0–5 mm in 0.5 mm increments (VolumeRadTM, GE Healthcare, Chalfont St. Giles, United Kingdom). The accuracy of the algorithm was quantified by comparing the minimum JSW in a region of interest in the medial compartment of the JSW map to the measured phantom setting for each trial. In addition, the algorithm was applied to DTS scans of a static knee phantom and the JSW map compared to values estimated from a manually segmented computed tomography (CT) dataset. The algorithm was also applied to three clinical DTS datasets of osteoarthritic patients. Results: The algorithm segmented the JSW and generated a JSW map for all phantom and clinical datasets. For the adjustable phantom, the estimated minimum JSW values were plotted against the measured values for all trials. A linear fit estimated a slope of 0.887 (R2¼0.962) and a mean error across all trials of 0.34 mm for the PA phantom data. The estimated minimum JSW values for the lateral adjustable phantom acquisitions were found to have low correlation to the measured values (R2¼0.377), with a mean error of 2.13 mm. The error in the lateral adjustable-phantom datasets appeared to be caused by artifacts due to unrealistic features in the phantom bones. JSW maps generated by DTS and CT varied by a mean of 0.6 mm and 0.8 mm across the knee joint, for PA and lateral scans. The tibial and femoral edges were successfully segmented and JSW maps determined for PA and lateral clinical DTS datasets. Conclusions: A semiautomated method is presented for quantifying the 3D joint space in a 2D JSW map using tomosynthesis images. The proposed algorithm quantified the JSW across the knee joint to sub-millimeter accuracy for PA tomosynthesis acquisitions. Overall, the results suggest that x-ray tomosynthesis may be beneficial for diagnosing and monitoring disease progression or treatment of osteoarthritis by providing quantitative images of JSW in the load-bearing knee

Bone Marrow Lesions and Subchondral Cysts in Association with Severity of Structural Degeneration in Hip Osteoarthritis

This item is only available electronically.Thesis (BHlthMSc(Hons)) -- University of Adelaide, Adelaide Medical School, YEA

MRI texture analysis of subchondral bone at the tibial plateau

OBJECTIVES: To determine the feasibility of MRI texture analysis as a method of quantifying subchondral bone architecture in knee osteoarthritis (OA).   METHODS: Asymptomatic subjects aged 20-30 (group 1, n = 10), symptomatic patients aged 40-50 (group 2, n = 10) and patients scheduled for knee replacement aged 55-85 (group 3, n = 10) underwent high spatial resolution T1-weighted coronal 3T knee MRI. Regions of interest were created in the medial (MT) and lateral (LT) tibial subchondral bone from which 20 texture parameters were calculated. T2 mapping of the tibial cartilage was performed in groups 1 and 2. Mean parameter values were compared between groups using ANOVA. Linear discriminant analysis (LDA) was used to evaluate the ability of texture analysis to classify subjects correctly.   RESULTS: Significant differences in 18/20 and 12/20 subchondral bone texture parameters were demonstrated between groups at the MT and LT respectively. There was no significant difference in mean MT or LT cartilage T2 values between group 1 and group 2. LDA demonstrated subject classification accuracy of 97 % (95 % CI 91-100 %).   CONCLUSION: MRI texture analysis of tibial subchondral bone may allow detection of alteration in subchondral bone architecture in OA. This has potential applications in understanding OA pathogenesis and assessing response to treatment.   KEY POINTS: • Improved techniques to monitor OA disease progression and treatment response are desirable • Subchondral bone (SB) may play significant role in the development of OA • MRI texture analysis is a method of quantifying changes in SB architecture • Pilot study showed that this technique is feasible and reliable • Significant differences in SB texture were demonstrated between individuals with/without OA

Multiscale Femoral Neck Imaging and Multimodal Trabeculae Quality Characterization in an Osteoporotic Bone Sample

: Although multiple structural, mechanical, and molecular factors are definitely involved in osteoporosis, the assessment of subregional bone mineral density remains the most commonly used diagnostic index. In this study, we characterized bone quality in the femoral neck of one osteoporotic patients as compared to an age-matched control subject, and so used a multiscale and multimodal approach including X-ray computed microtomography at different spatial resolutions (pixel size: 51.0, 4.95 and 0.9 µm), microindentation and Fourier transform infrared spectroscopy. Our results showed abnormalities in the osteocytes lacunae volume (358.08 ± 165.00 for the osteoporotic sample vs. 287.10 ± 160.00 for the control), whereas a statistical difference was found neither for shape nor for density. The osteoporotic femoral head and great trochanter reported reduced elastic modulus (Es) and hardness (H) compared to the control reference (-48% (p < 0.0001) and -34% (p < 0.0001), respectively for Es and H in the femoral head and -29% (p < 0.01) and -22% (p < 0.05), respectively for Es and H in the great trochanter), whereas the corresponding values in the femoral neck were in the same range. The spectral analysis could distinguish neither subregional differences in the osteoporotic sample nor between the osteoporotic and healthy samples. Although, infrared spectroscopic measurements were comparable among subregions, and so regardless of the bone osteoporotic status, the trabecular mechanical properties were comparable only in the femoral neck. These results illustrate that bone remodeling in osteoporosis is a non-uniform process with different rates in different bone anatomical regions, hence showing the interest of a clear analysis of the bone microarchitecture in the case of patients' osteoporotic evaluation

Texture Analysis in Magnetic Resonance Imaging: Review and Considerations for Future Applications

Texture analysis is a technique used for the quantification of image texture. It has been successfully used in many fields, and in the past years it has been applied in magnetic resonance imaging (MRI) as a computer-aided diagnostic tool. Quantification of the intrinsic heterogeneity of different tissues and lesions is necessary as they are usually imperceptible to the human eye. In the present chapter, we describe texture analysis as a process consisting of six steps: MRI acquisition, region of interest (ROI) definition, ROI preprocessing, feature extraction, feature selection, and classification. There is a great variety of methods and techniques to be chosen at each step and all of them can somehow affect the outcome of the texture analysis application. We reviewed the literature regarding texture analysis in clinical MRI focusing on the important considerations to be taken at each step of the process in order to obtain maximum benefits and to avoid misleading results

BONE AND JOINT SURGERY

Total hip arthroplasty with cemented Lubinus SP II prosthesis is well analyzed in the Sweden National Hip Arthroplasty Register. There are only few reports from the other countries concerning survival analysis of this implant in short and mid-term follow-up. Eesti Arst 2007; 86(8):533-60