Showing papers by "Heinz-Otto Peitgen published in 2012"

Visualization support for the planning of hepatic needle placement.

Abstract: Percutaneous image-guided interventions, such as radiofrequency ablation or biopsy, are using needle-shaped instruments which have to be inserted into a target area without penetrating any vital structure. The established planning workflow is based on viewing 2D slices of a pre-interventional CT or MR scan. However, access paths not parallel to the axial plane are often necessary. For such complicated cases, the planning process is challenging and time consuming if solely based on 2D slices. To overcome these limitations while keeping the well-established workflow, we propose a visualization method that highlights less suited paths directly in the 2D visualizations with which the radiologist is familiar. Based on a user defined target point and segmentation masks of relevant risk structures, a risk structure map is computed using GPU accelerated volume rendering and projected onto the 2D slices. This visualization supports the user in defining safe linear access paths by selecting a second point directly in the 2D image slices. In an evaluation for 20 liver radiofrequency ablation cases, 3 experienced radiologists stated for 55% of the cases that the visualization supported the access path choice. The visualization support was rated with an average mark of 2.2. For 2 of the 3 radiologists, a significant reduction of the planning duration by 54 and 50% was observed. The proposed visualization approach can both accelerate the access path planning for radiofrequency ablation in the liver and facilitate the differentiation between safer and less safe paths.

Precise Local Resection for Hepatocellular Carcinoma Based on Tumor-Surrounding Vascular Anatomy Revealed by 3D Analysis

Abstract: Purposes: Local resection for hepatocellular carcinoma (HCC) has been traditionally performed non-anatomically. The purpose of this study is to evaluate the feasibility of precise l

Mixture-Model-Based segmentation of myocardial delayed enhancement MRI

Abstract: Myocardial viability assessment is an important task in the diagnosis of coronary heart disease. The measurement of the delayed enhancement effect, the accumulation of contrast agent in defective tissue, has become the gold standard for detecting necrotic tissue with MRI. The purpose of the presented work was to provide a segmentation and quantification method for delayed enhancement MRI. To this end, a suitable mixture model for the myocardial intensity distribution is determined based on expectation maximization and the comparison of the fit accuracy. The subsequent watershed-based segmentation uses the intensity threshold information derived from this model. Preliminary results are derived from an analysis of datasets provided by the STACOM challenge organizers. The segmentation provided reasonable results in all datasets, but the method strongly depends on the underlying myocardium segmentation.

Automatic alignment of pre- and post-interventional liver CT images for assessment of radiofrequency ablation

Abstract: Image-guided radiofrequency ablation (RFA) is becoming a standard procedure for minimally invasive tumor treatment in clinical practice. To verify the treatment success of the therapy, reliable post-interventional assessment of the ablation zone (coagulation) is essential. Typically, pre- and post-interventional CT images have to be aligned to compare the shape, size, and position of tumor and coagulation zone. In this work, we present an automatic workflow for masking liver tissue, enabling a rigid registration algorithm to perform at least as accurate as experienced medical experts. To minimize the effect of global liver deformations, the registration is computed in a local region of interest around the pre-interventional lesion and post-interventional coagulation necrosis. A registration mask excluding lesions and neighboring organs is calculated to prevent the registration algorithm from matching both lesion shapes instead of the surrounding liver anatomy. As an initial registration step, the centers of gravity from both lesions are aligned automatically. The subsequent rigid registration method is based on the Local Cross Correlation (LCC) similarity measure and Newton-type optimization. To assess the accuracy of our method, 41 RFA cases are registered and compared with the manually aligned cases from four medical experts. Furthermore, the registration results are compared with ground truth transformations based on averaged anatomical landmark pairs. In the evaluation, we show that our method allows to automatic alignment of the data sets with equal accuracy as medical experts, but requiring significancy less time consumption and variability.

Workflow-centred evaluation of an automatic lesion tracking software for chemotherapy monitoring by CT.

Abstract: In chemotherapy monitoring, an estimation of the change in tumour size is an important criterion for the assessment of treatment success. This requires a comparison between corresponding lesions in the baseline and follow-up computed tomography (CT) examinations. We evaluate the clinical benefits of an automatic lesion tracking tool that identifies the target lesions in the follow-up CT study and pre-computes the lesion volumes. Four radiologists performed volumetric follow-up examinations for 52 patients with and without lesion tracking. In total, 139 lung nodules, liver metastases and lymph nodes were given as target lesions. We measured reading time, inter-reader variability in lesion identification and volume measurements, and the amount of manual adjustments of the segmentation results. With lesion tracking, target lesion assessment time decreased by 38 % or 22 s per lesion. Relative volume difference between readers was reduced from 0.171 to 0.1. Segmentation quality was comparable with and without lesion tracking. Our automatic lesion tracking tool can make interpretation of follow-up CT examinations quicker and provide results that are less reader-dependent. • Computed tomography is widely used to follow-up lesions in oncological patients. • Novel software automatically identifies and measures target lesions in oncological follow-up examinations. • This enables a reduction of target lesion assessment. • The automated measurements are less reader-dependent.

Computer-assisted surgical planning in adult-to-adult live donor liver transplantation: how much does it help? A single center experience.

Abstract: BACKGROUND Preoperative imaging and donor selection are cardinal components of adult-to-adult live donor liver transplantation (ALDLT) The purpose of this study was to evaluate our three-dimensional (3D) computed tomography image-derived computer-assisted surgical planning (3D CASP) in ALDLT METHODS Eighty-three consecutive ALDLTs (71 right and 12 left) were planned with 3D CASP Graft, remnant, and total liver volume compliance were calculated and compared with actual intraoperative values Computed risk analysis encompassing territorial liver mapping, functional (safely drained) volumes, and outflow congestion volumes in grafts and remnants allowed for the individualized management of the middle hepatic vein (MHV) RESULTS Graft volume compliance was 135%±44% Three small-for-size (SFS) grafts with lethal SFS syndrome (SFSS) had nonsignificant volume compliance with maximal graft volume-body weight ratios of less than 083 Seven SFS grafts with reversible or absent SFSS showed maximal graft volume-body weight ratios of 09 to 116 Significant differences were identified for (a) virtual graft and remnant congestion volumes of risky versus nonrisky MHV types (49%±6% and 34%±7% vs 29%±8% and 33%±12%, P<0001 and P<002, respectively) and (b) virtual mean functional versus surgical volumes of grafts (527±119 vs 963±176 mL, P<00001) and remnants (419±182 vs 640±213 mL, P<0001) CONCLUSIONS CASP allowed for (a) prevention of SFSS in extremely small grafts by predicting donor liver plasticity and (b) individualized MHV management for both donors and recipients based on functional graft/remnant volume analysis

Quadrature filter based motion analysis for 3d ultrasound sequences

Abstract: Analysis of echocardiograms is a valuable tool for assessing myocardial function and diseases. Processing of ultrasound data is challenging due to noise levels and depth-dependent quality of structure edges. We propose to adapt a method based on quadrature filters that is invariant to changes in intensity and has been successfully applied to MRI data earlier. Quadrature-filter-based registration derives the spatial deformation between two images from the local phase shift. Because the local phase is intensity-invariant and requires inhomogeneity, e.g., noise and intensity variations, to properly pick up phase shifts, it is well suited for ultrasound data. A multi-resolution and multi-scale scheme is used to cover different scales of deformations. The type and strength of regularization of the dense deformation field can be specified for each level, allowing for weighting of global and local motion. To speed up the registration, deformation fields are determined slice-wise for three orientations of the original data and subsequently combined into a true 3D deformation field. The method is evaluated with the data and ground truth provided by the Cardiac Motion Analysis Challenge at STACOM 2012.

A novel workflow-centric breast MRI reading prototype utilizing multitouch gestures

Abstract: We propose a novel paradigm for clinical diagnostic software using a mobile multi-touch device for user interaction and dedicated monitors for image display. We show a demonstrator implementing a workflow-based breast MRI reading system tailored to multi-touch interaction. The demonstrator explores the feasibility of touch interaction for diagnostic reading of MRI patient cases. We show a patient-centric, workflow-oriented concept that is arranged around a multi-touch capable hybrid input-output device. In this contribution we introduce clinically useful concepts of the demonstrator. Firstly, a mechanism that we dubbed location awareness takes care of security issues. Reading is supported by (1) a patient browser with graphical patient history and cancer risk factors; (2) a workflow concept using hanging protocols; (3) dedicated ROI definition, annotation, and measurement tools using multi-touch gestures. Gesture concepts and interaction paradigms are introduced for intuitive user experiences while maintaining accuracy.

Improving interaction in navigated surgery by combining a pan-tilt mounted laser and a pointer with triggering

Abstract: User interaction during navigated surgery is often a critical issue in the overall procedure, as several complex aspects must be considered, such as sterility, workflow, field of view, and cognitive load. This work introduces a new approach for intraoperative interaction that seamlessly fits the high surgical requirements. A navigation system, typically consisting of a tracking system and a monitor for 3D virtual models, is augmented with a tracked pointer with triggering functionality and a pan-tilt mounted laser. The pointer, which is sterile and can be applied for landmark-based organ registration, is used for wireless interaction with the monitor scene. The laser system enables the calibration of the monitor, which is out of the tracking system's range. Moreover, the laser beam can focus on any organ point defined on the virtual model, which improves targeting or visual feedback during intervention. The calibration of the laser system, monitor, and triggered pointer is achieved by an effective procedure, which can be easily repeated in operating room. The mathematical background of the calibration is based on the Levenberg-Marquardt and Umeyama's algorithms.

Modeling, Simulation and Optimization of Radio Frequency Ablation

Abstract: The treatment of hepatic lesions with radio-frequency (RF) ablation has become a promising minimally invasive alternative to surgical resection during the last decade. In order to achieve treatment qualities similar to surgical R0 resections, patient specific mathematical modeling and simulation of the biophysical processes during RF ablation are valuable tools. They allow for an a priori estimation of the success of the therapy as well as an optimization of the therapy parameters. In this report we discuss our recent efforts in this area: a model of partial differential equations (PDEs) for the patient specific numerical simulation of RF ablation, the optimization of the probe placement under the constraining PDE system and the identification of material parameters from temperature measurements. A particular focus lies on the uncertainties in the patient specific tissue properties. We discuss a stochastic PDE model, allowing for a sensitivity analysis of the optimal probe location under variations in the material properties. Moreover, we optimize the probe location under uncertainty, by considering an objective function, which is based on the expectation of the stochastic distribution of the temperature distribution. The application of our models and algorithms to data from real patient’s CT scans underline their applicability.

Efficient Breast Deformation Simulation

Abstract: Breast surgery might benefit from image guidance, if position and extend of the disease could be visualized in the same breast deformation as the surgery is performed. Such visualizations, however, are challenging to obtain, since the positioning for image acquisition in MRI is prone, while the patient lies supine for surgical procedures, causing a considerable deformation of the breasts between the two states. In our contribution, we outline a set of novel algorithms and methods to improve an efficient simulation of breast deformation between the prone image and the supine surgery positioning. In particular, we propose several extensions to a highly efficient dynamic corotated finite element method (FEM), namely non-linear material properties, the sliding of the breast tissue on the chest wall, and a fine-tuning step to align the breast model to a measured surface. All extensions are carefully designed to keep the efficiency and stability of the approach, and thus to allow their application in clinical routine. We explore all novel techniques using synthetic and volunteer prone and supine breast MRI data and assess their feasibility towards accurate, yet efficient simulation of large breast deformations.