Segmentation and quantification of bone erosions in high-resolution peripheral quantitative computed tomography datasets of the metacarpophalangeal joints of patients with rheumatoid arthritis

Objective: To develop a precise three-dimensional (3D) segmentation technique for bone erosions in high-resolution peripheral quantitative CT (HR-pQCT) datasets to measure their volume, surface area and shape parameters. Assessment of bone erosions in patients with RA is important for diagnosis and evaluation of treatment efficacy. HR-pQCT allows quantifying periarticular bone loss in arthritis. Methods: HR-pQCT scans with a spatial resolution of about 120 µm of the second to fourth metacarpophalangeal joints were acquired in patients with RA. Erosions were identified by placing a seed point in each of them. After applying 3D segmentation, the volume, surface area and sphericity of erosions were calculated. Results were compared with an approximation method using manual measurements. Intra- and interoperator precision analysis was performed for both the 3D segmentation and the manual technique. Results: Forty-three erosions were assessed in 18 datasets. Intra- and interoperator precisions (RMSCV/RMSSD) for erosion volume were 5.66%/0.49 mm3 and 7.76%/0.76 mm3, respectively. The correlation between manual measurements and their simulation using segmentation volumes was r = 0.87. Precision errors for the manual method were 15.39% and 0.36 mm3, respectively. Conclusion: We developed a new precise 3D segmentation technique for quantification of bone erosions in HR-pQCT datasets that correlates to the volume, shape and surface area of the erosion. The technique allows fast and effective measurement of the erosion size and could therefore be helpful for rapid and quantitative assessment of erosion size

Prediction of Hip Failure Load: In Vitro Study of 80 Femurs Using Three Imaging Methods and Finite Element Models-The European Fracture Study (EFFECT).

Purpose To evaluate the performance of three imaging methods (radiography, dual-energy x-ray absorptiometry DXA, and quantitative computed tomography CT) and that of a numerical analysis with finite element modeling (FEM) in the prediction of failure load of the proximal femur and to identify the best densitometric or geometric predictors of hip failure load.Supported by the European Commission “Quality of Life And Management of Living Resources Program” (QLK6-CT-2002-02440-3DQCT)

Detailed view of HMPA-segmentation.

<p>(a) An example of an axial slice with proximal femur segmentation; (b) Magnified part of the cortex with profiles: original profiles are in blue/magenta, the green line exemplifies the cortical thickness measurement at a single voxel as a voxel-to-surface distance based on segmentation. Note how direction and length of a profile are related.</p

Relative error of the thickness estimation under two levels of simulated Gaussian noise.

<p>For the range of true thickness values normalized by the full width at half maximum (FWHM) of the Gaussian (), mean value and standard deviation of the corresponding relative error were computed after 250 simulations. These statistical parameters are shown for three methods using three different colors. True reference BMD was used (800 mg/mm), <i>σ</i> = 1.5 mm, <i>c</i> = 150, and <i>b</i> = 0 mg/mm. (a) Noise level = 30 mg/mm; (b) Noise level = 37 mg/mm.</p

Relative thickness estimation error with respect to the error in BMD_ref.

<p>The true level of BMD_ref was 800, <i>σ</i> = 1.5, and <i>c</i> = 150 mg/mm, . Note that with true BMD_ref both DM and MPA-methods produce no errors: the corresponding curves coincide with the x-axis.</p

Quantitative analysis of skeletal muscle by computed tomography imaging—State of the art

The radiological assessment of muscle properties—size, mass, density (also termed radiodensity), composition, and adipose tissue infiltration—is fundamental in muscle diseases. More recently, it also became obvious that muscle atrophy, also termed muscle wasting, is caused by or associated with many other diseases or conditions, such as inactivity, malnutrition, chronic obstructive pulmonary disorder, cancer-associated cachexia, diabetes, renal and cardiac failure, and sarcopenia and even potentially with osteoporotic hip fracture. Several techniques have been developed to quantify muscle morphology and function. This review is dedicated to quantitative computed tomography (CT) of skeletal muscle and only includes a brief comparison with magnetic resonance imaging. Strengths and limitations of CT techniques are discussed in detail, including CT scanner calibration, acquisition and reconstruction protocols, and the various quantitative parameters that can be measured with CT, starting from simple volume measures to advanced parameters describing the adipose tissue distribution within muscle. Finally, the use of CT in sarcopenia and cachexia and the relevance of muscle parameters for the assessment of osteoporotic fracture illustrate the application of CT in two emerging areas of medical interest. Keywords: Adipose tissue, Computed tomography, Fat infiltration, Muscle, Muscle densit

A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh

Many studies use threshold-based techniques to assess in vivo the muscle, bone and adipose tissue distribution of the legs using computed tomography (CT) imaging. More advanced techniques divide the legs into subcutaneous adipose tissue (SAT), anatomical muscle (muscle tissue and adipocytes within the muscle border) and intra- and perimuscular adipose tissue. In addition, a so-called muscle density directly derived from the CT-values is often measured. We introduce a new integrated approach to quantify the muscle-lipid system (MLS) using quantitative CT in patients with sarcopenia or osteoporosis. The analysis targets the thigh as many CT studies of the hip do not include entire legs The framework consists of an anatomic coordinate system, allowing delineation of reproducible volumes of interest, a robust semi-automatic 3D segmentation of the fascia and a comprehensive method to quantify of the muscle and lipid distribution within the fascia. CT density-dependent features are calibrated using subject-specific internal CT values of the SAT and external CT values of an in scan calibration phantom. Robustness of the framework with respect to operator interaction, image noise and calibration was evaluated. Specifically, the impact of inter- and intra-operator reanalysis precision and addition of Gaussian noise to simulate lower radiation exposure on muscle and AT volumes, muscle density and 3D texture features quantifying MLS within the fascia, were analyzed. Existing data of 25 subjects (age: 75.6 ± 8.7) with porous and low-contrast muscle structures were included in the analysis. Intra- and inter-operator reanalysis precision errors were below 1% and mostly comparable to 1% of cohort variation of the corresponding features. Doubling the noise changed most 3D texture features by up to 15% of the cohort variation but did not affect density and volume measurements. The application of the novel technique is easy with acceptable processing time. It can thus be employed for a comprehensive quantification of the muscle-lipid system enabling radiomics approaches to musculoskeletal disorders

Segmentation and quantification of bone erosions in high-resolution peripheral quantitative computed tomography datasets of the metacarpophalangeal joints of patients with rheumatoid arthritis

Objective: To develop a precise three-dimensional (3D) segmentation technique for bone erosions in high-resolution peripheral quantitative CT (HR-pQCT) datasets to measure their volume, surface area and shape parameters. Assessment of bone erosions in patients with RA is important for diagnosis and evaluation of treatment efficacy. HR-pQCT allows quantifying periarticular bone loss in arthritis. Methods: HR-pQCT scans with a spatial resolution of about 120 µm of the second to fourth metacarpophalangeal joints were acquired in patients with RA. Erosions were identified by placing a seed point in each of them. After applying 3D segmentation, the volume, surface area and sphericity of erosions were calculated. Results were compared with an approximation method using manual measurements. Intra- and interoperator precision analysis was performed for both the 3D segmentation and the manual technique. Results: Forty-three erosions were assessed in 18 datasets. Intra- and interoperator precisions (RMSCV/RMSSD) for erosion volume were 5.66%/0.49 mm3 and 7.76%/0.76 mm3, respectively. The correlation between manual measurements and their simulation using segmentation volumes was r = 0.87. Precision errors for the manual method were 15.39% and 0.36 mm3, respectively. Conclusion: We developed a new precise 3D segmentation technique for quantification of bone erosions in HR-pQCT datasets that correlates to the volume, shape and surface area of the erosion. The technique allows fast and effective measurement of the erosion size and could therefore be helpful for rapid and quantitative assessment of erosion size