Measuring femoral lesions despite CT metal artefacts: a cadaveric study.

OBJECTIVE: Computed tomography is the modality of choice for measuring osteolysis but suffers from metal-induced artefacts obscuring periprosthetic tissues. Previous papers on metal artefact reduction (MAR) show qualitative improvements, but their algorithms have not found acceptance for clinical applications. We investigated to what extent metal artefacts interfere with the segmentation of lesions adjacent to a metal femoral implant and whether metal artefact reduction improves the manual segmentation of such lesions. MATERIALS AND METHODS: We manually created 27 periprosthetic lesions in 10 human cadaver femora. We filled the lesions with a fibrotic interface tissue substitute. Each femur was fitted with a polished tapered cobalt-chrome prosthesis and imaged twice--once with the metal, and once with a substitute resin prosthesis inserted. Metal-affected CTs were processed using standard back-projection as well as projection interpolation (PI) MAR. Two experienced users segmented all lesions and compared segmentation accuracy. RESULTS: We achieved accurate delineation of periprosthetic lesions in the metal-free images. The presence of a metal implant led us to underestimate lesion volume and introduced geometrical errors in segmentation boundaries. Although PI MAR reduced streak artefacts, it led to greater underestimation of lesion volume and greater geometrical errors than without its application. CONCLUSION: CT metal artefacts impair image segmentation. PI MAR can improve subjective image appearance but causes loss of detail and lower image contrast adjacent to prostheses. Our experiments showed that PI MAR is counterproductive for manual segmentation of periprosthetic lesions and should be used with care.

Articulated planar reformation for change visualization in small animal imaging.

The analysis of multi-timepoint whole-body small animal CT data is greatly complicated by the varying posture of the subject at different timepoints. Due to these variations, correctly relating and comparing corresponding regions of interest is challenging.In addition, occlusion may prevent effective visualization of these regions of interest. To address these problems, we have developed a method that fully automatically maps the data to a standardized layout of sub-volumes, based on an articulated atlas registration. We have dubbed this process articulated planar reformation, or APR. A sub-volume can be interactively selected for closer inspection and can be compared with the corresponding sub-volume at the other timepoints, employing a number of different comparative visualization approaches. We provide an additional tool that highlights possibly interesting areas based on the change of bone density between timepoints. Furthermore we allow visualization of the local registration error, to give an indication of the accuracy of the registration. We have evaluated our approach on a case that exhibits cancer-induced bone resorption.

Smooth graphs for visual exploration of higher-order state transitions.

In this paper, we present a new visual way of exploring state sequences in large observational time-series. A key advantage of our method is that it can directly visualize higher-order state transitions. A standard first order state transition is a sequence of two states that are linked by a transition. A higher-order state transition is a sequence of three or more states where the sequence of participating states are linked together by consecutive first order state transitions. Our method extends the current state-graph exploration methods by employing a two dimensional graph, in which higher-order state transitions are visualized as curved lines. All transitions are bundled into thick splines, so that the thickness of an edge represents the frequency of instances. The bundling between two states takes into account the state transitions before and after the transition. This is done in such a way that it forms a continuous representation in which any subsequence of the time series is represented by a continuous smooth line. The edge bundles in these graphs can be explored interactively through our incremental selection algorithm.We demonstrate our method with an application in exploring labeled time-series data from a biological survey, where a clustering has assigned a single label to the data at each time-point. In these sequences, a large number of cyclic patterns occur, which in turn are linked to specific activities. We demonstrate how our method helps to find these cycles, and how the interactive selection process helps to find and investigate activities.

Extensions of parallel coordinates for interactive exploration of large multi-timepoint data sets.

Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight into multi-variate data. These plots help to spot correlations between variables. PCPs have been successfully applied to unstructured datasets up to a few millions of points. In this paper, we present techniques to enhance the usability of PCPs for the exploration of large, multi-timepoint volumetric data sets, containing tens of millions of points per timestep. The main difficulties that arise when applying PCPs to large numbers of data points are visual clutter and slow performance, making interactive exploration infeasible. Moreover, the spatial context of the volumetric data is usually lost. We describe techniques for preprocessing using data quantization and compression, and for fast GPU-based rendering of PCPs using joint density distributions for each pair of consecutive variables, resulting in a smooth, continuous visualization. Also, fast brushing techniques are proposed for interactive data selection in multiple linked views, including a 3D spatial volume view. These techniques have been successfully applied to three large data sets: Hurricane Isabel (Vis'04 contest), the ionization front instability data set (Vis'08 design contest), and data from a large-eddy simulation of cumulus clouds. With these data, we show how PCPs can be extended to successfully visualize and interactively explore multi-timepoint volumetric datasets with an order of magnitude more data points.

Integrated support for medical image analysis methods: from development to clinical application.

Computer-aided image analysis is becoming increasingly important to efficiently and safely handle large amounts of high-resolution images generated by advanced medical imaging devices. The development of medical image analysis (MIA) software with the required properties for clinical application, however, is difficult and labor-intensive. Such development should be supported by systems providing scalable computational capacity and storage space, as well as information management facilities. This paper describes the properties of distributed systems to support and facilitate the development, evaluation, and clinical application of MIA methods. First, the main characteristics of existing systems are presented. Then, the phases in a method's lifecycle are analyzed (development, parameter optimization, evaluation, clinical routine), identifying the types of users, tasks, and related computational issues. A scenario is described where all tasks are performed with the aid of computational tools integrated into an ideal supporting environment. The requirements for this environment are described, proposing a grid-oriented paradigm that emphasizes virtual collaboration among users, pieces of software, and devices distributed among geographically dispersed healthcare, research, and development enterprises. Finally, the characteristics of the existing systems are analyzed according to these requirements. The proposed requirements offer a useful framework to evaluate, compare, and improve the existing systems that support MIA development.

Lines of curvature for polyp detection in virtual colonoscopy.

Computer-aided diagnosis (CAD) is a helpful addition to laborious visual inspection for preselection of suspected colonic polyps in virtual colonoscopy. Most of the previous work on automatic polyp detection makes use of indicators based on the scalar curvature of the colon wall and can result in many false-positive detections. Our work tries to reduce the number of false-positive detections in the preselection of polyp candidates. Polyp surface shape can be characterized and visualized using lines of curvature. In this paper, we describe techniques for generating and rendering lines of curvature on surfaces and we show that these lines can be used as part of a polyp detection approach. We have adapted existing approaches on explicit triangular surface meshes, and developed a new algorithm on implicit surfaces embedded in 3D volume data. The visualization of shaded colonic surfaces can be enhanced by rendering the derived lines of curvature on these surfaces. Features strongly correlated with true-positive detections were calculated on lines of curvature and used for the polyp candidate selection. We studied the performance of these features on 5 data sets that included 331 pre-detected candidates, of which 50 sites were true polyps. The winding angle had a significant discriminating power for true-positive detections, which was demonstrated by a Wilcoxon rank sum test with p < 0.001. The median winding angle and inter-quartile range (IQR) for true polyps were 7.817 and 6.770 - 9.288 compared to 2.954 and 1.995 - 3.749 for false-positive detections.

Visualization of Sliding and Deformation of Orbital Fat During Eye Rotation.

PURPOSE: Little is known about the way orbital fat slides and/or deforms during eye movements. We compared two deformation algorithms from a sequence of MRI volumes to visualize this complex behavior. METHODS: Time-dependent deformation data were derived from motion-MRI volumes using Lucas and Kanade Optical Flow (LK3D) and nonrigid registration (B-splines) deformation algorithms. We compared how these two algorithms performed regarding sliding and deformation in three critical areas: the sclera-fat interface, how the optic nerve moves through the fat, and how the fat is squeezed out under the tendon of a relaxing rectus muscle. The efficacy was validated using identified tissue markers such as the lens and blood vessels in the fat. RESULTS: Fat immediately behind the eye followed eye rotation by approximately one-half. This was best visualized using the B-splines technique as it showed less ripping of tissue and less distortion. Orbital fat flowed around the optic nerve during eye rotation. In this case, LK3D provided better visualization as it allowed orbital fat tissue to split. The resolution was insufficient to visualize fat being squeezed out between tendon and sclera. CONCLUSION: B-splines performs better in tracking structures such as the lens, while LK3D allows fat tissue to split as should happen as the optic nerve slides through the fat. Orbital fat follows eye rotation by one-half and flows around the optic nerve during eye rotation. TRANSLATIONAL RELEVANCE: Visualizing orbital fat deformation and sliding offers the opportunity to accurately locate a region of cicatrization and permit an individualized surgical plan.

A fluoroscopy-based planning and guidance software tool for minimally invasive hip refixation by cement injection.

PURPOSE: In orthopaedics, minimally invasive injection of bone cement is an established technique. We present HipRFX, a software tool for planning and guiding a cement injection procedure for stabilizing a loosening hip prosthesis. HipRFX works by analysing a pre-operative CT and intraoperative C-arm fluoroscopic images. METHODS: HipRFX simulates the intraoperative fluoroscopic views that a surgeon would see on a display panel. Structures are rendered by modelling their X-ray attenuation. These are then compared to actual fluoroscopic images which allow cement volumes to be estimated. Five human cadaver legs were used to validate the software in conjunction with real percutaneous cement injection into artificially created periprothetic lesions. RESULTS: Based on intraoperatively obtained fluoroscopic images, our software was able to estimate the cement volume that reached the pre-operatively planned targets. The actual median target lesion volume was 3.58 ml (range 3.17-4.64 ml). The median error in computed cement filling, as a percentage of target volume, was 5.3% (range 2.2-14.8%). Cement filling was between 17.6 and 55.4% (median 51.8%). CONCLUSIONS: As a proof of concept, HipRFX was capable of simulating intraoperative fluoroscopic C-arm images. Furthermore, it provided estimates of the fraction of injected cement deposited at its intended target location, as opposed to cement that leaked away. This level of knowledge is usually unavailable to the surgeon viewing a fluoroscopic image and may aid in evaluating the success of a percutaneous cement injection intervention.

Interactive local super-resolution reconstruction of whole-body MRI mouse data: a pilot study with applications to bone and kidney metastases.

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy.

PURPOSE: Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-operative planning. METHODS: Individual voxels were classified based on a set of automatically extracted image features. Minimum-cost graph cuts were computed on the classification results. The graph-cut step enabled us to enforce geometrical containment constraints, such as cortical bone sheathing the femur's interior. The solution's novelty lies in the combination of voxel classification with multilabel graph cuts and in the way label costs were defined to enforce containment constraints. RESULTS: The segmentation pipeline was tested on a set of twelve manually segmented clinical CT volumes. The distribution of healthy tissue and bone cement was automatically determined with sensitivities greater than 82% and pathological fibrous interface tissue with a sensitivity exceeding 73%. Specificity exceeded 96% for all tissues. CONCLUSIONS: The addition of a graph-cut step improved segmentation compared to voxel classification alone. The pipeline described in this paper represents a practical approach to segmenting multitissue regions from CT.

Comparative exploration of whole-body MR through locally rigid transforms.

PURPOSE: Whole-body MRI is seeing increasing use in the study and diagnosis of disease progression. In this, a central task is the visual assessment of the progressive changes that occur between two whole-body MRI datasets, taken at baseline and follow-up. Current radiological workflow for this consists in manual search of each organ of interest on both scans, usually on multiple data channels, for further visual comparison. Large size of datasets, significant posture differences, and changes in patient anatomy turn manual matching in an extremely labor-intensive task that requires from radiologists high concentration for long period of time. This strongly limits the productivity and increases risk of underdiagnosis. MATERIALS AND METHODS: We present a novel approach to the comparative visual analysis of whole-body MRI follow-up data. Our method is based on interactive derivation of locally rigid transforms from a pre-computed whole-body deformable registration. Using this approach, baseline and follow-up slices can be interactively matched with a single mouse click in the anatomical region of interest. In addition to the synchronized side-by-side baseline and matched follow-up slices, we have integrated four techniques to further facilitate the visual comparison of the two datasets: the "deformation sphere", the color fusion view, the magic lens, and a set of uncertainty iso-contours around the current region of interest. RESULTS: We have applied our method to the study of cancerous bone lesions over time in patients with Kahler's disease. During these studies, the radiologist carefully visually examines a large number of anatomical sites for changes. Our interactive locally rigid matching approach was found helpful in localization of cancerous lesions and visual assessment of changes between different scans. Furthermore, each of the features integrated in our software was separately evaluated by the experts. CONCLUSION: We demonstrated how our method significantly facilitates examination of whole-body MR datasets in follow-up studies by enabling the rapid interactive matching of regions of interest and by the explicit visualization of change.

Exposure render: an interactive photo-realistic volume rendering framework.

The field of volume visualization has undergone rapid development during the past years, both due to advances in suitable computing hardware and due to the increasing availability of large volume datasets. Recent work has focused on increasing the visual realism in Direct Volume Rendering (DVR) by integrating a number of visually plausible but often effect-specific rendering techniques, for instance modeling of light occlusion and depth of field. Besides yielding more attractive renderings, especially the more realistic lighting has a positive effect on perceptual tasks. Although these new rendering techniques yield impressive results, they exhibit limitations in terms of their exibility and their performance. Monte Carlo ray tracing (MCRT), coupled with physically based light transport, is the de-facto standard for synthesizing highly realistic images in the graphics domain, although usually not from volumetric data. Due to the stochastic sampling of MCRT algorithms, numerous effects can be achieved in a relatively straight-forward fashion. For this reason, we have developed a practical framework that applies MCRT techniques also to direct volume rendering (DVR). With this work, we demonstrate that a host of realistic effects, including physically based lighting, can be simulated in a generic and flexible fashion, leading to interactive DVR with improved realism. In the hope that this improved approach to DVR will see more use in practice, we have made available our framework under a permissive open source license.

Cardiac MRI visualization for ventricular tachycardia ablation.

OBJECTIVE: The integrated visualization of cardiac MRI during a ventricular tachycardia (VT) mapping and ablation procedure would provide improved catheter guidance and tissue assessment. We developed a system for and explored the added value of simultaneous visualization of intracardiac voltage measurements and MRI-derived myocardial scar information during VT ablation procedures. METHOD: We propose the use of a synchronized 3D and 2D view. In 3D, the catheter will be guided optimally by assessing 3D scar characteristics and its relation to the ventricular anatomy. In 2D, a detailed assessment of the tissue can be made. We developed several 3D visualization techniques, including volume rendering of the scar and myocardial surfaces colored according to the voltage measurements. We also visualized context structures in the heart. For the 2D view, we proposed showing three adjacent slices simultaneously. To link the 3D with the 2D view, we added a linking plane and linking contours; the slice level shown in the 2D view is indicated in the 3D view. RESULTS: We evaluated our method via a case study during which we simulated the visual environment of an ablation procedure. The MRI-based volume rendering of scar tissue and the linking between the 3D and 2D views were both positively received. However, the visualization of the voltage measurements was found to be hard to interpret, partly due to the perceptually suitable but non-standard colormap. CONCLUSIONS: Based on this study, we can conclude that our approach of displaying MRI data and integrating it with voltage measurements has potential to improve VT ablation procedures.

Combined surface and volume processing for fused joint segmentation.

PURPOSE: Segmentation of rheumatoid joints from CT images is a complicated task. The pathological state of the joint results in a non-uniform density of the bone tissue, with holes and irregularities complicating the segmentation process. For the specific case of the shoulder joint, existing segmentation techniques often fail and lead to poor results. This paper describes a novel method for the segmentation of these joints. METHODS: Given a rough surface model of the shoulder, a loop that encircles the joint is extracted by calculating the minimum curvature of the surface model. The intersection points of this loop with the separate CT-slices are connected by means of a path search algorithm. Inaccurate sections are corrected by iteratively applying a Hough transform to the segmentation result. RESULTS: As a qualitative measure we calculated the Dice coefficient and Hausdorff distances of the automatic segmentations and expert manual segmentations of CT-scans of ten severely deteriorated shoulder joints. For the humerus and scapula the median Dice coefficient was 98.9% with an interquartile range (IQR) of 95.8-99.4 and 98.5% (IQR 98.3-99.2%), respectively. The median Hausdorff distances were 3.06 mm (IQR 2.30-4.14) and 3.92 mm (IQR 1.96 -5.92 mm), respectively. CONCLUSION: The routine satisfies the criterion of our particular application to accurately segment the shoulder joint in under 2 min. We conclude that combining surface curvature, limited user interaction and iterative refinement via a Hough transform forms a satisfactory approach for the segmentation of severely damaged arthritic shoulder joints.

The anatomy of the thoracic spinal canal in different postures: a magnetic resonance imaging investigation.

BACKGROUND AND OBJECTIVES: The goal of this study was to investigate,with magnetic resonance imaging, the human anatomic positions of the spinal canal (eg, spinal cord, thecal tissue) in various postures and identify possible implications from different patient positioning for neuraxial anesthetic practice. METHOD: Nine volunteers underwent magnetic resonance imaging in supine, laterally recumbent, and sitting (head-down) positions. Axial and sagittal slices of the thoracic and lumbar spine were measured for the relative distances between anatomic structures, including dura mater and spinal cord. RESULTS: The posterior dura-spinal cord (midline) distance is on average greater than the anterior dura-spinal cord (midline) distance along the thoracic spinal column, irrespective of volunteer postures (P G 0.05).The separation of the dura mater and spinal cord is greatest posterior in the middle thoracic region compared with upper and lower thoracic levels for all postures of the volunteers (P G 0.05). By placing the patient in a head-down sitting posture (as commonly done in epidural and spinal anesthesia), the posterior separation of the dura mater and spinal cordis increased. CONCLUSIONS: The spinal cord follows the straightest line through the imposed geometry of the spinal canal. Accordingly, there is relatively more posterior separation of the cord and surrounding thecal tissue at midthoracic levels in the apex of the thoracic kyphosis. Placing a patient in a position that accentuates the thoracic curvature of the spine (ie,sitting head-down) increases the posterior separation of the spinal cord and dural sheath at thoracic levels.