Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model

This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.

Accuracy of linear measurements using three imaging modalities: two lateral cephalograms and one 3D model from CBCT data

BACKGROUND The aim of this study was to evaluate the accuracy of linear measurements on three imaging modalities: lateral cephalograms from a cephalometric machine with a 3 m source-to-mid-sagittal-plane distance (SMD), from a machine with 1.5 m SMD and 3D models from cone-beam computed tomography (CBCT) data. METHODS Twenty-one dry human skulls were used. Lateral cephalograms were taken, using two cephalometric devices: one with a 3 m SMD and one with a 1.5 m SMD. CBCT scans were taken by 3D Accuitomo® 170, and 3D surface models were created in Maxilim® software. Thirteen linear measurements were completed twice by two observers with a 4 week interval. Direct physical measurements by a digital calliper were defined as the gold standard. Statistical analysis was performed. RESULTS Nasion-Point A was significantly different from the gold standard in all methods. More statistically significant differences were found on the measurements of the 3 m SMD cephalograms in comparison to the other methods. Intra- and inter-observer agreement based on 3D measurements was slightly better than others. LIMITATIONS Dry human skulls without soft tissues were used. Therefore, the results have to be interpreted with caution, as they do not fully represent clinical conditions. CONCLUSIONS 3D measurements resulted in a better observer agreement. The accuracy of the measurements based on CBCT and 1.5 m SMD cephalogram was better than a 3 m SMD cephalogram. These findings demonstrated the linear measurements accuracy and reliability of 3D measurements based on CBCT data when compared to 2D techniques. Future studies should focus on the implementation of 3D cephalometry in clinical practice.

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.

Investigating the interaction of cellulose nanofibers derived from cotton with a sophisticated 3D human lung cell coculture

Cellulose nanofibers are an attractive component of a broad range of nanomaterials. Their intriguing mechanical properties and low cost, as well as the renewable nature of cellulose make them an appealing alternative to carbon nanotubes (CNTs), which may pose a considerable health risk when inhaled. Little is known, however, concerning the potential toxicity of aerosolized cellulose nanofibers. Using a 3D in vitro triple cell coculture model of the human epithelial airway barrier, it was observed that cellulose nanofibers isolated from cotton (CCN) elicited a significantly (p < 0.05) lower cytotoxicity and (pro-)inflammatory response than multiwalled CNTs (MWCNTs) and crocidolite asbestos fibers (CAFs). Electron tomography analysis also revealed that the intracellular localization of CCNs is different from that of both MWCNTs and CAFs, indicating fundamental differences between each different nanofibre type in their interaction with the human lung cell coculture. Thus, the data shown in the present study highlights that not only the length and stiffness determine the potential detrimental (biological) effects of any nanofiber, but that the material used can significantly affect nanofiber-cell interactions.

Adsorption behavior of redox-active suppressor additives: Combined electrochemical and STM studies

The redox chemistry and the related surface phase behavior of Safranine (SAF) and Janus Green B (JGB) have been studied by means of cyclic voltammetry in combination with in situ Scanning Tunneling Microscopy using HOPG (Highly Oriented Pyrolytic Graphite) and single crystalline Cu(1 0 0) as model substrates, both revealing different widths of the accessible potential windows. JGB and SAF serve as prototypical heterocyclic suppressor/leveler additives that are used for the metallization of 3D-TSVs (3D Through Silicon Vias) following a classical "leveling" concept. SAF can be considered as the reductive decomposition product of JGB that is formed at the copper/electrolyte interface upon electroplating. Both additives reveal a pronounced pH-dependent redox-chemistry with redox-transitions lying close to or even beyond the anodic limit of the copper potential window. Affected by these redox-processes are in particular the aromatic cores of those heterocycles that can be (quasi)reversibly reduced by a two electron transfer process within the potential window of copper. Therefore we identify the reduced form of those dyes as the active components for the suppressing/leveling effect in copper plating. STM data clearly shows a dye surface phase behavior that is crucially determined by its potential-dependent redox-chemistry. This will be exemplarily discussed for the SAF dye. On chloride-modified Cu(1 0 0) mono-reduced SAF forms a structurally well-defined monolayer of cationic stacking polymers. However, this coupled anion/cation layer reveals only minor suppressing capabilities with respect to the copper dissolution and deposition processes. Complete reduction of the aromatic heterocycle finally leads to the 3D precipitation of hydrophobic reaction products. 3D clusters of this SAF precipitate are discussed as the active structural motif for the suppressing effect of these dyes. (C) 2011 Elsevier Ltd. All rights reserved.

Underneath the cerclage: an ex vivo study on the cerclage-bone interface mechanics

Cerclages regain interest due to a rising number of periprosthetic fractures. The contact distribution at the circumferential cerclage-bone interface is still unknown. Local interface pressure depends on the amount of contact area. Cortical damage at the interface would provoke cerclage loosening. Therefore, the contact area, the bone pressure along the interface and the cortical resistance underneath loaded cerclages were determined in an ex vivo model.

Diagnostic microchip to assay 3D colony-growth potential of captured circulating tumor cells

Microfluidic technology has been successfully applied to isolate very rare tumor-derived epithelial cells (circulating tumor cells, CTCs) from blood with relatively high yield and purity, opening up exciting prospects for early detection of cancer. However, a major limitation of state-of-the-art CTC-chips is their inability to characterize the behavior and function of captured CTCs, for example to obtain information on proliferative and invasive properties or, ultimately, tumor re-initiating potential. Although CTCs can be efficiently immunostained with markers reporting phenotype or fate (e.g. apoptosis, proliferation), it has not yet been possible to reliably grow captured CTCs over long periods of time and at single cell level. It is challenging to remove CTCs from a microchip after capture, therefore such analyses should ideally be performed directly on-chip. To address this challenge, we merged CTC capture with three-dimensional (3D) tumor cell culture on the same microfluidic platform. PC3 prostate cancer cells were isolated from spiked blood on a transparent PDMS CTC-chip, encapsulated on-chip in a biomimetic hydrogel matrix (QGel™) that was formed in situ, and their clonal 3D spheroid growth potential was assessed by microscopy over one week in culture. The possibility to clonally expand a subset of captured CTCs in a near-physiological in vitro model adds an important element to the expanding CTC-chip toolbox that ultimately should improve prediction of treatment responses and disease progression.