Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries

Robust and accurate identification of intervertebral discs from low resolution, sparse MRI scans is essential for the automated scan planning of the MRI spine scan. This paper presents a graphical model based solution for the detection of both the positions and orientations of intervertebral discs from low resolution, sparse MRI scans. Compared with the existing graphical model based methods, the proposed method does not need a training process using training data and it also has the capability to automatically determine the number of vertebrae visible in the image. Experiments on 25 low resolution, sparse spine MRI data sets verified its performance.

Magnetic resonance imaging based determination of body compartments with the versatile, interactive sparse sampling (VISS) method

To investigate the inhomogeneity of radiofrequency fields at higher field strengths that can interfere with established volumetric methods, in particular for the determination of visceral (VAT) and subcutaneous adipose tissue (SCAT). A versatile, interactive sparse sampling (VISS) method is proposed to determine VAT, SCAT, and also total body volume (TBV).

Anisotropically oriented electrospun matrices with an imprinted periodic micropattern: a new scaffold for engineered muscle constructs

Engineered muscle constructs provide a promising perspective on the regeneration or substitution of irreversibly damaged skeletal muscle. However, the highly ordered structure of native muscle tissue necessitates special consideration during scaffold development. Multiple approaches to the design of anisotropically structured substrates with grooved micropatterns or parallel-aligned fibres have previously been undertaken. In this study we report the guidance effect of a scaffold that combines both approaches, oriented fibres and a grooved topography. By electrospinning onto a topographically structured collector, matrices of parallel-oriented poly(ε-caprolactone) fibres with an imprinted wavy topography of 90 µm periodicity were produced. Matrices of randomly oriented fibres or parallel-oriented fibres without micropatterns served as controls. As previously shown, un-patterned, parallel-oriented substrates induced myotube orientation that is parallel to fibre direction. Interestingly, pattern addition induced an orientation of myotubes at an angle of 24° (statistical median) relative to fibre orientation. Myotube length was significantly increased on aligned micropatterned substrates in comparison to that on aligned substrates without pattern (436 ± 245 µm versus 365 ± 212 µm; p < 0.05). We report an innovative, yet simple, design to produce micropatterned electrospun scaffolds that induce an unexpected myotube orientation and an increase in myotube length.

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Engineered fibrin matrices for functional display of cell membrane-bound growth factor-like activities: study of angiogenic signaling by ephrin-B2

With the rapid increase in approaches to pro- or anti-angiogenic therapy, new and effective methodologies for administration of cell-bound growth factors will be required. We sought to develop the natural hydrogel matrix fibrin as platform for extensive interactions and continuous signaling by the vascular morphogen ephrin-B2 that normally resides in the plasma membrane and requires multivalent presentation for ligation and activation of Eph receptors on apposing endothelial cell surfaces. Using fibrin and protein engineering technology to induce multivalent ligand presentation, a recombinant mutant ephrin-B2 receptor binding domain was covalently coupled to fibrin networks at variably high densities. The ability of fibrin-bound ephrin-B2 to act as ligand for endothelial cells was preserved, as demonstrated by a concomitant, dose-dependent increase of endothelial cell binding to engineered ephrin-B2-fibrin substrates in vitro. The therapeutic relevance of ephrin-B2-fibrin implant matrices was demonstrated by a local angiogenic response in the chick embryo chorioallontoic membrane evoked by the local and prolonged presentation of matrix-bound ephrin-B2 to tissue adjacing the implant. This new knowledge on biomimetic fibrin vehicles for precise local delivery of membrane-bound growth factor signals may help to elucidate specific biological growth factor function, and serve as starting point for development of new treatment strategies.