Alternative mouse models for carcinogenicity assessment: industry use and issues with pathology interpretation

The Carcinogenicity Alternative Mouse Models (CAMM) Working Group of the Society of Toxicologic Pathology (STP) surveyed the membership to define current practices and opinions in industry regarding the use of alternative mouse models for carcinogenicity testing. The results of the survey indicated that CAMM are used most often to fulfill a regulatory requirement (e.g., to replace the two-year mouse bioassay) and are being accepted by regulatory agencies. Alternative models are also sometimes used for internal decision making or to address a mechanistic question. The CAMM most commonly used are the p53+/- and rasH2. The rasH2 appears to be the currently accepted model for general carcinogenicity testing. Problems with study interpretation included lack of historic background data, unexpected tumor finding, and tumor identification/characterization of early lesions. Problems with implementation or conduct of the study included extent of the pathology evaluation, numbers of animals, survival, and study duration. Recommendations were developed for, frequency and type of positive control testing, extent of histopathologic examination of test article-treated and positive control animals, current use and future development of diagnostic criteria; increased availability and use of historic data, and use of other genetically modified mice in carcinogenicity testing.

Surgeon-controlled visualization techniques for virtual reality-guided cardiac surgery

Surgeon-to-computer interaction difficulties in using virtual reality (VR)-guided surgical environments arise from disorientation, insufficient depth information, and delegation of view control. This study focuses on optimizing information delivery for VR-guided beating heart surgery. Initial human factors evaluation and participatory design has provided insight for developing an effective surgeon-controlled interface for VR-guided cardiac interventions. We discuss the motivation for and development of three interface prototypes as well as the methodology used to measure the effect of these novel techniques on user performance and workload.

Subject-specific models for image-guided cardiac surgery

Three-dimensional visualization for planning and guidance is still not routinely available for minimally invasive cardiac surgery (MICS). This can be addressed by providing the surgeon with subject-specific geometric models derived from 3D preoperative images for planning of port locations or to rehearse the procedure. For guidance purposes, these models can also be registered to the subject using intraoperative images. In this paper, we present a method for extracting subject-specific heart geometry from preoperative MR images. The main obstacle we face is the low quality of clinical data in terms of resolution, signal-to-noise ratio, and presence of artefacts. Instead of using these images directly, we approach the problem in three steps: (1) generate a high quality template model, (2) register the template with the preoperative data, and (3) animate the result over the cardiac cycle. Validation of this approach showed that dynamic subject-specific models can be generated with a mean error of 3.6+/-1.1 mm from low resolution target images (6 mm slices). Thus, the models are sufficiently accurate for MICS training and procedure planning. In terms of guidance, we also demonstrate how the resulting models may be adapted to the operating room using intraoperative ultrasound imaging.

Establishing non-inferiority in treatment trials in psychiatry: guidelines from an Expert Consensus Meeting

Comparing the efficacy of different treatments in psychiatry is difficult for many reasons, even when they are investigated in "head-to-head" studies. A consensus meeting was, therefore, held to produce best practice guidelines for such studies. This article presents the conclusions of this consensus and illustrates it using published data in the field of antidepressant treatment of generalized anxiety disorder.

FEM-based evaluation of deformable image registration for radiation therapy

This paper presents a new concept to automatically detect the neighborhood in an image where deformable registration is mis-performing. Specifically, the displacement vector field (DVF) from a deformable image registration is substituted into a finite-element-based elastic framework to calculate unbalanced energy in each element. The value of the derived energy indicates the quality of the DVF in its neighborhood. The new voxel-based evaluation approach is compared with three other validation criteria: landmark measurement, a finite element approach and visual comparison, for deformable registrations performed with the optical-flow-based 'demons' algorithm as well as thin-plate spline interpolation. This analysis was performed on three pairs of prostate CT images. The results of the analysis show that the four criteria give mutually comparable quantitative assessments on the six registration instances. As an objective concept, the unbalanced energy presents no requirement on boundary constraints in its calculation, different from traditional mechanical modeling. This method is automatic, and at voxel level suitable to evaluate deformable registration in a clinical setting.

A real time hyperelastic tissue model

Real-time soft tissue modeling has a potential application in medical training, procedure planning and image-guided therapy. This paper characterizes the mechanical properties of organ tissue using a hyperelastic material model, an approach which is then incorporated into a real-time finite element framework. While generalizable, in this paper we use the published mechanical properties of pig liver to characterize an example application. Specifically, we calibrate the parameters of an exponential model, with a least-squares method (LSM) using the assumption that the material is isotropic and incompressible in a uniaxial compression test. From the parameters obtained, the stress-strain curves generated from the LSM are compared to those from the corresponding computational model solved by ABAQUS and also to experimental data, resulting in mean errors of 1.9 and 4.8%, respectively, which are considerably better than those obtained when employing the Neo-Hookean model. We demonstrate our approach through the simulation of a biopsy procedure, employing a tetrahedral mesh representation of human liver generated from a CT image. Using the material properties along with the geometric model, we develop a nonlinear finite element framework to simulate the behaviour of liver during an interventional procedure with a real-time performance achieved through the use of an interpolation approach.

Dose reduction for cardiac CT using a registration-based approach

Two reasons for the recent rise in radiation exposure from CT are increases in its clinical applicability and the desire to maintain high SNR while acquiring smaller voxels. To address this emerging dose problem, several strategies for reducing patient exposure have already been proposed. One method employed in cardiac imaging is ECG-driven modulation of the tube current between 100% at one time point in the cardiac cycle and a reduced fraction at the remaining phases. In this paper, we describe how images obtained during such acquisition can be used to reconstruct 4D data of consistent high quality throughout the cardiac cycle. In our approach, we assume that the middiastole (MD) phase is imaged with full dose. The MD image is then independently registered to lower dose images (lower SNR) at other frames, resulting in a set of transformations. Finally, the transformations are used to warp the MD frame through the cardiac cycle to generate the full 4D image. In addition, the transformations may be interpolated to increase the temporal sampling or to generate images at arbitrary time points. Our approach was validated using various data obtained with simulated and scanner-implemented dose modulation. We determined that as little as 10% of the total dose was required to reproduce full quality images with a 1 mm spatial error and an error in intensity values on the order of the image noise. Thus, our technique offers considerable dose reductions compared to standard imaging protocols, with minimal effects on the quality of the final data.

Challenges in image-guided therapy system design

System development for image-guided therapy (IGT), or image-guided interventions (IGI), continues to be an area of active interest across academic and industry groups. This is an emerging field that is growing rapidly: major academic institutions and medical device manufacturers have produced IGT technologies that are in routine clinical use, dozens of high-impact publications are published in well regarded journals each year, and several small companies have successfully commercialized sophisticated IGT systems. In meetings between IGT investigators over the last two years, a consensus has emerged that several key areas must be addressed collaboratively by the community to reach the next level of impact and efficiency in IGT research and development to improve patient care. These meetings culminated in a two-day workshop that brought together several academic and industrial leaders in the field today. The goals of the workshop were to identify gaps in the engineering infrastructure available to IGT researchers, develop the role of research funding agencies and the recently established US-based National Center for Image Guided Therapy (NCIGT), and ultimately to facilitate the transfer of technology among research centers that are sponsored by the National Institutes of Health (NIH). Workshop discussions spanned many of the current challenges in the development and deployment of new IGT systems. Key challenges were identified in a number of areas, including: validation standards; workflows, use-cases, and application requirements; component reusability; and device interface standards. This report elaborates on these key points and proposes research challenges that are to be addressed by a joint effort between academic, industry, and NIH participants.

Reconstruction of 3D Elasticity Images from a Layered Element Chain

Elasticity imaging is a novel technique that can reveal intrinsic mechanical properties of soft tissue. This paper proposes a new finite element approach to reconstruct elasticity images. Based on the real time data capturing capability of ultrasound, we propose a layered element chain algorithm to compute the distribution of Young's moduli in a region of interest. This approach employs pre-calibrated moduli as its input instead of using boundary pressure conditions which are usually not easy to obtain.

Electrophysiology-guided deep brain neurosurgery

Since the discovery of X-rays, medical imaging has played a major role in the guidance of surgical procedures. Recent advances in computer technology have only accelerated the rapid development of this field. As interventions become significantly less invasive, the use of pre-operative and intra-operative images to guide surgery has assumed increasing importance. Image-guided techniques have been employed for many years to plan and guide neurosurgical procedures. Amongst the most challenging areas of neurosurgery is the accurate targeting of nuclei within the deep brain for the treatment of Parkinson's and other motor system diseases. Unfortunately, standard CT and MR imaging does not permit the anatomical delineation of the targets, and so additional information, for example atlases and electrophysiological data, must also be employed. Both these forms of data can be mapped, using non rigid image registration techniques, to a standard representation of a brain acquired from MRI. The electrophysiology database can also evolve over time with the incorporation of data acquired from multiple patients operated in the past. Information of this nature can then be incorporated within the patient image, and serve as an invaluable tool in predicting to the surgeon the likely area of the target. This approach can significantly reduce the trauma associated with the insertion of multiple unnecessary electrodes to refine the target location, and speed up the procedure.

Application of t1 and t2 maps for stereotactic deep-brain neurosurgery planning

This work presents the application of a quantitative magnetic resonance imaging (MRI) technique in stereotactic deep-brain neurosurgery planning procedures. The high spatial resolution T<inf>1</inf>and T<inf>2</inf>maps acquired using this imaging method have been normalized to the standard CJH-27 brain coordinate system and integrated into a neurosurgical visualization and navigation system to improve the accuracy of surgical target localization. The T<inf>1</inf>and T<inf>2</inf>maps, along with the standardized anatomical and functional information within this system, can be navigated, non-rigidly registered, and arbitrarily processed. Once applied to individual patients, these maps facilitate the delineation of surgical targets. Our preliminary studies compared the centroids of segmented deep-brain nuclei based on the T<inf>1</inf>and T<inf>2</inf>maps with those according to Schaltenbrand and Wahren atlas, and with the actual surgical targets of 15 patients who had undergone thalamotomy, pallidotomy, and subthalamic nucleus deep-brain stimulation. The average displacement was 3.21mm&#177;0.80mm, indicating the potential capability of this system to accurately initiate target identifications.

High Quality Appearance Models of Heart Sub-Components Based on MR Images

High quality images have many uses, such as the testing of image processing algorithms and serving as templates for registration in image guided surgery. This work describes the creation of four high quality images or "appearance models", for 1. Myocardium, 2. Right atrium and ventricle, 3. Left atrium and aorta, and 4. Epicardial surface. The appearance models are created by registering and averaging together a series of high-resolution MR images of the same volunteer. These are then corrected to represent the average shape as determined from MR data of ten other volunteers. Thus, we show how single volunteer imaging can be combined with image registration to generate average-shape appearance models with high resolution and signal-to-noise ratio. Our final data consist of four 3D average shape appearance models (each depicting one of the sub-heart components) with 1.5 x 1.5 x 1.5 mm³voxels and a signal-to-noise ratio increase of 6.6 versus raw data.

2D ultrasound augmented by virtual tools for guidance of interventional procedures

Many intracardiac procedures can currently be performed on the heart only after it has been arrested, and the patient has been placed on cardio-pulmonary bypass. We have developed a new method for operating on multiple targets inside the beating heart, and describe a procedure for accessing them under virtual-reality (VR)-assisted image guidance that combines real-time ultrasound with a virtual model of tools, and the surgical environment acquired from pre-operative images. This paper presents preliminary results aimed at assessing the operator's ability to accurately position and staple an artificial valve to a "valve orifice" within a cardiac phantom when guidance is performed via ultrasound alone, and with US augmented by the VR environment.

2D-3D registration of coronary angiograms for cardiac procedure planning and guidance

We present a completely automated 2D-3D registration technique that accurately maps a patient-specific heart model, created from preoperative images, to the patient's orientation in the operating room. This mapping is based on the registration of preoperatively acquired 3D vascular data with intraoperatively acquired angiograms. Registration using both single and dual-plane angiograms is explored using simulated but realistic datasets that were created from clinical images. Heart deformations and cardiac phase mismatches are taken into account in our validation using a digital 4D human heart model. In an ideal situation where the pre- and intraoperative images were acquired at identical time points within the cardiac cycle, the single-plane and the dual-plane registrations resulted in 3D root-mean-square (rms) errors of 1.60 +/- 0.21 and 0.53 +/- 0.08 mm, respectively. When a 10% timing offset was added between the pre- and the intraoperative acquisitions, the single-plane registration approach resulted in inaccurate registrations in the out-of-plane axis, whereas the dual-plane registration exhibited a 98% success rate with a 3D rms error of 1.33 +/- 0.28 mm. When all potential sources of error were included, namely, the anatomical background, timing offset, and typical errors in the vascular tree reconstruction, the dual-plane registration performed at 94% with an accuracy of 2.19 +/- 0.77 mm.

Recurrent venous thromboembolism in patients with and without anticoagulation after inferior vena caval filter placement

AIM

The aim of this study was to compare the rate of recurrent venothromboembolic (VTE) events and factors contributing to VTE events in patients with inferior vena caval (IVC) filters on chronic anticoagulation to those in whom anticoagulation was discontinued.

METHODS

Retrospective cohort study of 353 patients who received IVC filters between 1986 and 2002.

RESULTS

Anticoagulation status was available for 304 patients (132 on coumadin anticoagulation therapy and 172 who did not receive any anticoagulation therapy) whose IVC filters were placed within 30 days of their qualifying thromboembolic event. Two-year event-free survival for the anticoagulated group was 80.6% (95% confidence interval--CI--76.9, 84.3] and was 67.8% (95% CI 63.2, 72.3) for the non-anticoagulated group. Patients who had Greenfield filter had a higher, but not statistically significant different, rate of recurrence compared to those with other types of filters (hazard ratio 1.4; 95% CI 0.9, 2). The rate of recurrent VTE events was independent of age, gender, smoking status, or underlying medical condition.

CONCLUSIONS

Among those with IVC filters, long-term anticoagulation therapy prolonged event-free survival for up to 2 years but did not prevent recurrent VTE events.

Image-guided laser projection for port placement in minimally invasive surgery

We present an application of an augmented reality laser projection system in which procedure-specific optimal incision sites, computed from pre-operative image acquisition, are superimposed on a patient to guide port placement in minimally invasive surgery. Tests were conducted to evaluate the fidelity of computed and measured port configurations, and to validate the accuracy with which a surgical tool-tip can be placed at an identified virtual target. A high resolution volumetric image of a thorax phantom was acquired using helical computed tomography imaging. Oriented within the thorax, a phantom organ with marked targets was visualized in a virtual environment. A graphical interface enabled marking the locations of target anatomy, and calculation of a grid of potential port locations along the intercostal rib lines. Optimal configurations of port positions and tool orientations were determined by an objective measure reflecting image-based indices of surgical dexterity, hand-eye alignment, and collision detection. Intra-operative registration of the computed virtual model and the phantom anatomy was performed using an optical tracking system. Initial trials demonstrated that computed and projected port placement provided direct access to target anatomy with an accuracy of 2 mm.