Automated Motion Analysis of Bony Joint Structures from Dynamic Computer Tomography Images: A Multi-Atlas Approach

Dynamic computer tomography (CT) is an emerging modality to analyze in-vivo joint kinematics at the bone level, but it requires manual bone segmentation and, in some instances, landmark identification. The objective of this study is to present an automated workflow for the assessment of three-dimensional in vivo joint kinematics from dynamic musculoskeletal CT images. The proposed method relies on a multi-atlas, multi-label segmentation and landmark propagation framework to extract bony structures and detect anatomical landmarks on the CT dataset. The segmented structures serve as regions of interest for the subsequent motion estimation across the dynamic sequence. The landmarks are propagated across the dynamic sequence for the construction of bone embedded reference frames from which kinematic parameters are estimated. We applied our workflow on dynamic CT images obtained from 15 healthy subjects on two different joints: thumb base (n = 5) and knee (n = 10). The proposed method resulted in segmentation accuracies of 0.90 ± 0.01 for the thumb dataset and 0.94 ± 0.02 for the knee as measured by the Dice score coefficient. In terms of motion estimation, mean differences in cardan angles between the automated algorithm and manual segmentation, and landmark identification performed by an expert were below 1◦. Intraclass correlation (ICC) between cardan angles from the algorithm and results from expert manual landmarks ranged from 0.72 to 0.99 for all joints across all axes. The proposed automated method resulted in reproducible and reliable measurements, enabling the assessment of joint kinematics using 4DCT in clinical routine

The cost-effectiveness of digital breast tomosynthesis in a population breast cancer screening program

OBJECTIVES: To evaluate at which sensitivity digital breast tomosynthesis (DBT) would become cost-effective compared to digital mammography (DM) in a population breast cancer screening program, given a constant estimate of specificity. METHODS: In a microsimulation model, the cost-effectiveness of biennial screening for women aged 50-75 was simulated for three scenarios: DBT for women with dense breasts and DM for women with fatty breasts (scenario 1), DBT for the whole population (scenario 2) or maintaining DM screening (reference). For DM, sensitivity was varied depending on breast density from 65 to 87%, and for DBT from 65 to 100%. The specificity was set at 96.5% for both DM and DBT. Direct medical costs were considered, including screening, biopsy and treatment costs. Scenarios were considered to be cost-effective if the incremental cost-effectiveness ratio (ICER) was below €20,000 per life year gain (LYG). RESULTS: For both scenarios, the ICER was more favourable at increasing DBT sensitivity. Compared with DM screening, 0.8-10.2% more LYGs were found when DBT sensitivity was at least 75% for scenario 1, and 4.7-18.7% when DBT sensitivity was at least 80% for scenario 2. At €96 per DBT, scenario 1 was cost-effective at a DBT sensitivity of at least 90%, and at least 95% for scenario 2. At €80 per DBT, these values decreased to 80% and 90%, respectively. CONCLUSION: DBT is more likely to be a cost-effective alternative to mammography in women with dense breasts. Whether DBT could be cost-effective in a general population highly depends on DBT costs. KEY POINTS: • DBT could be a cost-effective screening modality for women with dense breasts when its sensitivity is at least 90% at a maximum cost per screen of €96. • DBT has the potential to be cost-effective for screening all women when sensitivity is at least 90% at a maximum cost per screen of €80. • Whether DBT could be used as an alternative to mammography for screening all women is highly dependent on the cost of DBT per screen

The use of cardiac CT acquisition mode for dynamic musculoskeletal imaging

Objectives To quantitatively evaluate the impact of a cardiac acquisition CT mode on motion artifacts in comparison to a conventional cine mode for dynamic musculoskeletal (MSK) imaging. Methods A rotating PMMA phantom with air-filled holes drilled at varying distances from the disk center corresponding to linear hole speeds of 0.75 cm/s, 2.0 cm/s, and 3.6 cm/s was designed. Dynamic scans were obtained in cardiac and cine modes while the phantom was rotating at 48°/s in the CT scanner. An automated workflow to compute the Jaccard distance (JD) was established to quantify degree of motion artifacts in the reconstructed phantom images. JD values between the cardiac and cine scan modes were compared using a paired sample t-test. In addition, three healthy volunteers were scanned with both modes during a cyclic flexion–extension motion of the knee and analysed using the proposed metric. Results For all hole sizes and speeds, the cardiac scan mode had significantly lower (p-value <0.001) JD values. (0.39 [0.32–0.46]) i.e less motion artifacts in comparison to the cine mode (0.72 [0.68–0.76]). For both modes, a progressive increase in JD was also observed as the linear speed of the holes increased from 0.75 cm/s to 3.6 cm/s. The dynamic images of the three healthy volunteers showed less artifacts when scanned in cardiac mode compared to cine mode, and this was quantitatively confirmed by the JD values. Conclusions A cardiac scan mode could be used to study dynamic musculoskeletal phenomena especially of fast-moving joints since it significantly minimized motion artifacts

An Inside Perspective on Magma Intrusion: Quantifying 3D Displacement and Strain in Laboratory Experiments by Dynamic X-Ray Computed Tomography

Magma intrusions grow to their final geometries by deforming the Earth's crust internally and by displacing the Earth's surface. Interpreting the related displacements in terms of intrusion geometry is key to forecasting a volcanic eruption. While scaled laboratory models enable us to study the relationships between surface displacement and intrusion geometry, past approaches entailed limitations regarding imaging of the laboratory model interior or simplicity of the simulated crustal rheology. Here we apply cutting-edge medical wide beam X-ray Computed Tomography (CT) to quantify in 4D the deformation induced in laboratory models by an intrusion of a magma analog (golden syrup) into a rheologically-complex granular host rock analog (sand and plaster). We extract the surface deformation and we quantify the strain field of the entire experimental volume in 3D over time by using Digital Volume Correlation (DVC). By varying the strength and height of the host material, and intrusion velocity, we observe how intrusions of contrasting geometries grow, and induce contrasting strain field characteristics and surface deformation in 4D. The novel application of CT and DVC reveals that distributed strain accommodation and mixed-mode (opening and shear) fracturing dominates in low-cohesion material overburden, and leads to the growth of thick cryptodomes or cup-shaped intrusions. More localized strain accommodation and opening-mode fracturing dominates in high-cohesion material overburden, and leads to the growth of cone sheets or thin dikes. The results demonstrate how the combination of CT and DVC can greatly enhance the utility of optically non-transparent crustal rock analogs in obtaining insights into shallow crustal deformation processes. This unprecedented perspective on the spatio-temporal interaction of intrusion growth coupled with host material deformation provides a conceptual framework that can be tested by field observations at eroded volcanic systems and by the ever increasing spatial and temporal resolution of geodetic data at active volcanoes

Automated Motion Analysis of Bony Joint Structures from Dynamic Computer Tomography Images: A Multi-Atlas Approach

Dynamic computer tomography (CT) is an emerging modality to analyze in-vivo joint kinematics at the bone level, but it requires manual bone segmentation and, in some instances, landmark identification. The objective of this study is to present an automated workflow for the assessment of three-dimensional in vivo joint kinematics from dynamic musculoskeletal CT images. The proposed method relies on a multi-atlas, multi-label segmentation and landmark propagation framework to extract bony structures and detect anatomical landmarks on the CT dataset. The segmented structures serve as regions of interest for the subsequent motion estimation across the dynamic sequence. The landmarks are propagated across the dynamic sequence for the construction of bone embedded reference frames from which kinematic parameters are estimated. We applied our workflow on dynamic CT images obtained from 15 healthy subjects on two different joints: thumb base (n = 5) and knee (n = 10). The proposed method resulted in segmentation accuracies of 0.90 ± 0.01 for the thumb dataset and 0.94 ± 0.02 for the knee as measured by the Dice score coefficient. In terms of motion estimation, mean differences in cardan angles between the automated algorithm and manual segmentation, and landmark identification performed by an expert were below 1°. Intraclass correlation (ICC) between cardan angles from the algorithm and results from expert manual landmarks ranged from 0.72 to 0.99 for all joints across all axes. The proposed automated method resulted in reproducible and reliable measurements, enabling the assessment of joint kinematics using 4DCT in clinical routine