Assessment of femur geometrical parameters using EOS™ imaging technology in patients with atypical femur fractures; preliminary results.

Atypical femur fractures (AFF) arise in the subtrochanteric and diaphyseal regions. Because of this unique distribution, we hypothesized that patients with AFF demonstrate specific geometrical variations of their lower limb whereby baseline tensile forces applied to the lateral cortex are higher and might favor the appearance of these rare stress fractures, when exposed to bisphosphonates. Using the low irradiation 2D-3D X-ray scanner EOS™ imaging technology we aimed to characterize and compare femur geometric parameters between women who sustained bisphosphonate-associated AFF and those who had experienced similar duration of exposure to bisphosphonates but did not sustain fractures. Conditional logistic regression models were constructed to estimate the association between selected geometric parameters and the occurrence of AFF. We identified 16 Caucasian women with AFF and recruited 16 ethnicity-, sex-, age-, height- and cumulative bisphosphonate exposure-matched controls from local osteoporosis clinics. Compared to controls, those with AFF had more lateral femur bowing (-3.2° SD [3.4] versus -0.8° SD [1.9] p=0.02). In regression analysis, lateral femur bowing was associated with the risk of AFF (aOR 1.54; 95% CI 1.04-2.28, p=0.03). Women who sustained a subtrochanteric AFF demonstrated a lesser femoral neck shaft angle (varus geometry) than those with a fracture at a diaphyseal site (121.9 [3.6]° versus 127.6 [7.2]°, p=0.07), whereas femur bowing was more prominent in those with a diaphyseal fracture compared to those with a subtrochanteric fracture (-4.3 [3.2]° versus -0.9 [2.7]°, p=0.07). Our analyses support that subjects with AFF exhibit femoral geometry parameters that result in higher tensile mechanical load on the lateral femur. This may play a critical role in the pathogenesis of AFF and requires further evaluation in a larger size population.

3D elastic registration of vessel structures from IVUS data on biplane angiography.

RATIONALE AND OBJECTIVES: Planar angiograms and intravascular ultrasound (IVUS) imaging provide important insight for the evaluation of atherosclerotic diseases and blood flow abnormalities. The construction of realistic three-dimensional models is essential to efficiently follow the progression of arterial plaque. This requires an explicit localization of IVUS frames from angiograms. Because of the difficulties encountered when trying to track the position of an IVUS transducer, we propose an elastic registration approach that relies on a virtual catheter path. MATERIALS AND METHODS: Deformable surface models of the lumen and external wall are constructed from segmented IVUS contours. A crude registration is obtained using a three-dimensional vessel centerline, reconstructed from two calibrated angiograms. Robust optimization of the virtual catheter path, position, absolute orientation, and regulation of the external wall shape is performed until near-perfect alignment of the back-projected silhouettes on image edges is reached. RESULTS: Visual assessment of the reconstructed vessels showed a good superposition of virtual models on the angiograms. We measured a 0.4-mm residual error value. A preliminary study of convergence properties on 15 datasets showed that initial absolute orientation may affect the solution. However, for follow-ups, coherent solutions were found among datasets. CONCLUSION: The advantages of the virtual catheter path approach are demonstrated. Future work will look at ways to single out the true solution with a better use of the available information in both modalities and additional validation studies on improved datasets.

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model.

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps, defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.

Semi-automation of the 3D reconstruction of the spine using wavelets and splines.

We propose a wavelet multi-resolution analysis to localize specific features in both lateral and frontal radiographs. This analysis allows an elegant spectral investigation that leads simultaneously to image de-noising and edge extraction. It is combined with an a priori knowledge of the spine's morphology and a 3D spline curve characterization of its global shape. Actual work deals with identifying the contours of the vertebral bodies and the localization of vertebrae's endplates. However, this information could also lead to the selection of a 3D statistical model of the spine suited for the studied deformation. Working with retro-projections of the model, we aim at creating edge models for each vertebra that will be used to geometrically match the wavelet's edges. The manual feature identification could then be replaced in the reconstruction of the 3D representation of the spine.