Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Atomistic simulations of 2D bicomponent self-assembly: from molecular recognition to self-healing

Supramolecular two-dimensional engineering epitomizes the design of complex molecular architectures through recognition events in multicomponent self-assembly. Despite being the subject of in-depth experimental studies, such articulated phenomena have not been yet elucidated in time and space with atomic precision. Here we use atomistic molecular dynamics to simulate the recognition of complementary hydrogen-bonding modules forming 2D porous networks on graphite. We describe the transition path from the melt to the crystalline hexagonal phase and show that self-assembly proceeds through a series of intermediate states featuring a plethora of polygonal types. Finally, we design a novel bicomponent system possessing kinetically improved self-healing ability in silico, thus demonstrating that a priori engineering of 2D self-assembly is possible.

Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

Advanced morphological 3D magnetic resonance observation of cartilage repair tissue (MOCART) scoring using a new isotropic 3D proton-density, turbo spin echo sequence with variable flip angle distribution (PD-SPACE) compared to an isotropic 3D steady-state free precession sequence (True-FISP) and standard 2D sequences

To evaluate a new isotropic 3D proton-density, turbo-spin-echo sequence with variable flip-angle distribution (PD-SPACE) sequence compared to an isotropic 3D true-fast-imaging with steady-state-precession (True-FISP) sequence and 2D standard MR sequences with regard to the new 3D magnetic resonance observation of cartilage repair tissue (MOCART) score.

High-resolution imaging of 2D outer membrane protein F (OmpF) crystals by atomic force microscopy

In this chapter the methodological bases are provided to achieve subnanometer resolution on two-dimensional (2D) membrane protein crystals by atomic force microscopy (AFM). This is outlined in detail with the example of AFM studies of the outer membrane protein F (OmpF) from the bacterium Escherichia coli (E. coli). We describe in detail the high-resolution imaging of 2D OmpF crystals in aqueous solution and under near-physiological conditions. The topographs of OmpF, and stylus effects and artifacts encountered when imaging by AFM are discussed.

Interactions between selected photosensitizers and model membranes: an NMR classification

Membrane interactions of porphyrinic photosensitizers (PSs) are known to play a crucial role for PS efficiency in photodynamic therapy (PDT). In the current paper, the interactions between 15 different porphyrinic PSs with various hydrophilic/lipophilic properties and phospholipid bilayers were probed by NMR spectroscopy. Unilamellar vesicles consisting of dioleoyl-phosphatidyl-choline (DOPC) were used as membrane models. PS-membrane interactions were deduced from analysis of the main DOPC (1)H-NMR resonances (choline and lipid chain signals). Initial membrane adsorption of the PSs was indicated by induced changes to the DOPC choline signal, i.e. a split into inner and outer choline peaks. Based on this parameter, the PSs could be classified into two groups, Type-A PSs causing a split and the Type-B PSs causing no split. A further classification into two subgroups each, A1, A2 and B1, B2 was based on the observed time-dependent changes of the main DOPC NMR signals following initial PS adsorption. Four different time-correlated patterns were found indicating different levels and rates of PS penetration into the hydrophobic membrane interior. The type of interaction was mainly affected by the amphiphilicity and the overall lipophilicity of the applied PS structures. In conclusion, the NMR data provided valuable structural and dynamic insights into the PS-membrane interactions which allow deriving the structural constraints for high membrane affinity and high membrane penetration of a given PS. (C) 2011 Elsevier B.V. All rights reserved.