Holger F. Boehm

Reproducibility and Side Differences of Mechanical Tests for Determining the Structural Strength of the Proximal Femur

In this experimental study, we evaluated the reproducibility error of mechanical strength tests of the proximal femur when simulating a fall on the trochanter. Based on side differences in femoral failure loads in 55 pairs of femora, we estimated the upper limit of the precision error to be 15% for the side impact test, whereas the intersubject variability was >40%.

Measuring perfusion and permeability in renal cell carcinoma with dynamic contrast-enhanced MRI: A pilot study

To retrospectively assess an improved quantitative methodology with separate assessment of perfusion and permeability for characterization of primary renal cell carcinoma (RCC) and monitoring antiangiogenic treatment.

Local 3D scaling properties for the analysis of trabecular bone extracted from high-resolution magnetic resonance imaging of human trabecular bone : Comparison with bone mineral density in the prediction of biomechanical strength in vitro

Rationale and Objectives. A novel, nonlinear morphologic measure [&Dgr;P(&agr;)] based on local 3D scaling properties was applied to high-resolution magnetic resonance images (HR-MRI) of human trabecular bone to predict biomechanical strength in vitro. Methods. We extracted &Dgr;P(&agr;) and traditional morphologic parameters (apparent trabecular volume fraction, apparent trabecular separation) from HR-MR images of 32 femoral and 13 spinal bone specimens. Furthermore, bone mineral density (BMD) and maximum compressive strength (MCS) were determined. The morphologic measures were compared with BMD in predicting the biomechanical strength. Results. In the vertebral (femoral) specimens, R2 for MCS versus &Dgr;P(&agr;) was 0.87 (0.61) (P < 0.001). Correlation between BMD and MCS was 0.53 (P = 0.05) (0.79 [P < 0.001]) for the vertebral (femoral) specimens. For the femoral specimens, prediction of MCS could be improved further by combining BMD and morphologic parameters by multiple regression (R2 = 0.88). Conclusions. Morphologic measures extracted from HR-MRI considering local 3D-scaling properties can be used to predict biomechanical properties of bone in vitro. They are superior to 2-dimensional standard linear morphometric measures and, depending on the anatomic location, more reliably predict bone strength as measured by MCS than does BMD.

Prediction of the fracture load of whole proximal femur specimens by topological analysis of the mineral distribution in DXA-scan images.

OBJECTIVE To evaluate scanner-generated images of hip specimens obtained from dual energy X-ray absorptiometry (DXA) by quantitative image analysis of bone mineral distribution in the standard regions of interest (ROI), to predict the ultimate mechanical strength, and to compare the predictive potential with standard densitometry. MATERIALS AND METHODS Femoral bone mineral density (BMD) of 100 hip specimens was obtained by DXA in the total hip, shaft, trochanteric, and neck ROI. Maximum compressive strength (MCS) of the specimens was measured in a mechanical loading device simulating a fall on the greater trochanter. The topology of bone mineral distribution in the scan images was evaluated by image processing methods based on the Minkowski functionals (MF) using the optimized topological parameter MF2D. Correlation and multivariate analysis were employed to assess the statistical potential of BMD and MF2D with respect to predict the mechanical strength of the femur specimens. RESULTS R2 for the correlation between load-to-failure and BMD varied between 0.73 and 0.79 (exponential curve fit, p<0.001), being highest in the trochanteric ROI. Correlation between load-to-failure of the specimens with the topological parameter MF2D ranged from R2 =0.8 to 0.91 (p<0.001). In a multivariate model combining the topological information from all ROIs, correlation with MCS rose to R2 =0.94. CONCLUSION The topological parameter MF2D can be employed to predict the mechanical strength of proximal femur specimens from DXA-generated images. Performance is superior to standard evaluation of DXA. In the future, the proposed image processing method may serve to improve the assessment of an individuals fracture risk.

Evaluation of a CT triage protocol for mass casualty incidents: results from two large-scale exercises

The purpose of this study was to evaluate the feasibility, stability, and reproducibility of a dedicated CT protocol for the triage of patients in two separate large-scale exercises that simulated a mass casualty incident (MCI). In both exercises, a bomb explosion at the local soccer stadium that had caused about 100 casualties was simulated. Seven casualties who were rated “critical” by on-site field triage were admitted to the emergency department and underwent whole-body CT. The CT workflow was simulated with phantoms. The history of the casualties was matched to existing CT examinations that were used for evaluation of image reading under MCI conditions. The times needed for transfer and preparation of patients, examination, image reconstruction, total time in the CT examination room, image transfer to PACS, and image reading were recorded, and mean capacities were calculated and compared using the Mann–Whitney U test. We found no significant time differences in transfer and preparation of patients, duration of CT data acquisition, image reconstruction, total time in the CT room, and reading of the images. The calculated capacities per hour were 9.4 vs. 9.8 for examinations completed, and 8.2 vs. 7.2 for reports completed. In conclusion, CT triage is feasible and produced constant results with this dedicated and fast protocol.

Improving the textural characterization of trabecular bone structure to quantify its changes: the locally adapted scaling vector method

We extend the recently introduced scaling vector method (SVM) to improve the textural characterization of oriented trabecular bone structures in the context of osteoporosis. Using the concept of scaling vectors one obtains non-linear structural information from data sets, which can account for global anisotropies. In this work we present a method which allows us to determine the local directionalities in images by using scaling vectors. Thus it becomes possible to better account for local anisotropies and to implement this knowledge in the calculation of the scaling properties of the image. By applying this adaptive technique, a refined quantification of the image structure is possible: we test and evaluate our new method using realistic two-dimensional simulations of bone structures, which model the effect of osteoblasts and osteoclasts on the local change of relative bone density. The partial differential equations involved in the model are solved numerically using cellular automata (CA). Different realizations with slightly varying control parameters are considered. Our results show that even small changes in the trabecular structures, which are induced by variation of a control parameters of the system, become discernible by applying the locally adapted scaling vector method. The results are superior to those obtained by isotropic and/or bulk measures. These findings may be especially important for monitoring the treatment of patients, where the early recognition of (drug-induced) changes in the trabecular structure is crucial.

Performance of linear and nonlinear texture measures in 2D and 3D for monitoring architectural changes in osteoporosis using computer-generated models of trabecular bone

Osteoporosis is a metabolic bone disease leading to de-mineralization and increased risk of fracture. The two major factors that determine the biomechanical competence of bone are the degree of mineralization and the micro-architectural integrity. Today, modern imaging modalities (high resolution MRI, micro-CT) are capable of depicting structural details of trabecular bone tissue. From the image data, structural properties obtained by quantitative measures are analysed with respect to the presence of osteoporotic fractures of the spine (in-vivo) or correlated with biomechanical strength as derived from destructive testing (in-vitro). Fairly well established are linear structural measures in 2D that are originally adopted from standard histo-morphometry. Recently, non-linear techniques in 2D and 3D based on the scaling index method (SIM), the standard Hough transform (SHT), and the Minkowski Functionals (MF) have been introduced, which show excellent performance in predicting bone strength and fracture risk. However, little is known about the performance of the various parameters with respect to monitoring structural changes due to progression of osteoporosis or as a result of medical treatment. In this contribution, we generate models of trabecular bone with pre-defined structural properties which are exposed to simulated osteoclastic activity. We apply linear and non-linear texture measures to the models and analyse their performance with respect to detecting architectural changes. This study demonstrates, that the texture measures are capable of monitoring structural changes of complex model data. The diagnostic potential varies for the different parameters and is found to depend on the topological composition of the model and initial “bone density”. In our models, non-linear texture measures tend to react more sensitively to small structural changes than linear measures. Best performance is observed for the 3rd and 4th Minkowski Functionals and for the scaling index method.

Application of the standard hough-transform to high resolution MRI of human trabecular bone to predict mechanical strength

In this study we introduce two non-linear structural measures based on the Standard Hough-Transform (SHT) that are applied to high resolution MR-images of human trabecular bone specimens in order to predict biomechanical properties. The results are compared to bone mineral density (BMD) and linear morphometric parameters. Axial MR-images (voxel-size: 117x156x300 mm3) of 33 human femoral and 10 spinal specimens are obtained using a 3D-gradient-echo-sequence. After measurement of BMD by quantitative computed tomography (QCT) all specimens are tested destructively for maximum compressive strength (MCS). The SHT is applied to the binarized and Sobel-filtered images and the peak-value (maxH) and its corresponding bin (posH) of the normalized Hough-spectrum are determined as well as linear measures (apparent bone fraction (app.BV/TV), apparent trabecular separation (app.Tb.Sp), apparent trabecular perimeter per unit area (app.Tb.Perim)). For the spinal [femoral] specimens, R2 for MCS vs. maxH is 0.72 (p=0.004) [0.49 (p<0.001)], R2 for MCS vs. posH is 0.56 (p=0.013) [0.55 (p<0.001)], and R2 for MCS vs. BMD is 0.43 (p=0.041) [0.72 (p<0.001)]. Correlations of the conventional, linear morphometric parameters and MCS are lower than those for the SHT-based measures or BMD, ranging from 0.20 (p=0.003) for app.BV/TV to 0.46 (p<0.001) for app.Tb.Sp. Prediction of MCS by maxH, posH, or BMD alone is improved by combination with the linear morphometric parameters in a linear regressional model (R2 =0.79). In conclusion, the biomechanical strength of human trabecular bone in vitro can effectively be predicted from High-Resolution MR-images by structural measures based on SHT. In the vertebral specimens these are superior to BMD or conventional structural measures in predicting bone strength.

Morphological filtering based on the Minkowski functionals in 3D for segmentation of macromolecular structures in intact eukaryotic cells depicted by cryo-electron tomography

In this contribution, we propose a novel approach to the segmentation of tomographic image data considering topological properties of binarized image components expressed in terms of the Minkowski Functionals in 3D. Electron tomography is a non-invasive method for three-dimensional (3D) reconstruction of cellular sub-structures from a series of projection images (i.e. from a tilt series) recorded with a transmission electron microscope. Data obtained by electron tomography provide a rich source of quantitative information concerning the structural composition and organization of cellular components. It allows to obtain 3D information on structural cellular arrangements at a significantly higher resolution than any other of the currently available imaging modalities. A major challenge, in this context, is the segmentation of the image data with respect to the identification macro-molecular structures such as the actin-cytoskeleton or cell organelles. We introduce a morphological filtering algorithm based on the Minkowski Functionals in 3D for segmentation of macromolecular structures in intact eukaryotic cells depicted by cryo-electron tomography. In mathematical topology, multi-dimensional convex objects can be characterized with respect to shape, structure, and the connectivity of their components using a set of morphological descriptors known as the Minkowski functionals. In a 3D-Euclidian space, these correspond to volume, surface area, mean integral curvature, and the Euler-Poincare characteristic. The morphological filtering procedure is applied to a 3D image data of an intact, ice-embedded Dictyostelium cell obtained by low dose transmission electron microscopy using a tilt series of -50° to +41.5° with an increment of 1.5°. Our method allows to separate cellular components with predefined textural properties, e.g. filamentary or globular structures, from the image data, which may then be studied and interpreted further.