Search

1- or 2-directional MRI blood flow mapping sequences are an integral part of standard MR protocols for diagnosis and therapy control in heart diseases. Recent progress in rapid MRI has made it possible to acquire volumetric, 3-directional cine images in reasonable scan time. In addition to flow and velocity measurements relative to arbitrarily oriented image planes, the analysis of 3-dimensional trajectories enables the visualization of flow patterns, local features of flow trajectories or possible paths into specific regions. The anatomical and functional information allows for advanced hemodynamic analysis in different application areas like stroke risk assessment, congenital and acquired heart disease, aneurysms or abdominal collaterals and cranial blood flow. The complexity of the 4D MRI flow datasets and the flow related image analysis tasks makes the development of fast comprehensive data exploration software for advanced flow analysis a challenging task. Most existing tools address only individual aspects of the analysis pipeline such as pre-processing, quantification or visualization, or are difficult to use for clinicians. The goal of the presented work is to provide a software solution that supports the whole image analysis pipeline and enables data exploration with fast intuitive interaction and visualization methods. The implemented methods facilitate the segmentation and inspection of different vascular systems. Arbitrary 2- or 3-dimensional regions for quantitative analysis and particle tracing can be defined interactively. Synchronized views of animated 3D path lines, 2D velocity or flow overlays and flow curves offer a detailed insight into local hemodynamics. The application of the analysis pipeline is shown for 6 cases from clinical practice, illustrating the usefulness for different clinical questions. Initial user tests show that the software is intuitive to learn and even inexperienced users achieve good results within reasonable processing times.

Radiofrequency (RF) ablation is an image-guided minimally invasive therapy which destroys a tumor by locally inducing electrical energy into the malignant tissue through a radiofrequency applicator. Treatment success is essentially dependent on the accurate placement of the RF applicator. In the case of CT-guided RF ablation of liver tumors, a central problem during monitoring is the reduced quality and information content in the peri-interventional images compared to the images used for planning. Therefore, the question of how to effectively transf er information from the planning scan into the peri-interventional scan in order to support the interventionalist is of high interest. Key to such an enhancement of peri-interventional scans is an adequate registration of the pre- and peri-interventional image, which also needs to be fast since intervention duration is still a challenge. We present an approach for the fast and automatic registration of a high quality CT volume scan of the liver to a spiral CT scan of lower quality. Our method combines an approximate pre-registration to compensate large displacem ents and a rigid registratio n of a liver subvolume fo r further refinement. The method focuses on the position of the tumor to be ablated and the corresponding access path . Thereby, it achieves both fast and precise results in the region of interest. A preliminary evaluation, on 37 data sets from 20 different patients, shows that the registration is performed within a maximum of 18 seconds, while obtaining high accuracy in the relevant region of the liver comprising tu mor and the planned access path. Keywords: Image-guided Therapy, In tervention, Registration, Radiofrequency Ablation, Targeting Support, Liver

The diagnosis support in the field of coronary artery disease (CAD) is very complex due to the numerous symptoms and performed studies leading to the final diagnosis. CTA and MRI are on their way to replace invasive catheter angiography. Thus, there is a need for sophisticated software tools that present the different analysis results, and correlate the anatomical and dynamic image information. We introduce a new software assistant for the combined result visualization of CTA and MR images, in which a dedicated concept for the structured presentation of original data, segmentation results, and individual findings is realized. Therefore, we define a comprehensive class hierarchy and assign suitable interaction functions. User guidance is coupled as closely as possible with available data, supporting a straightforward workflow design. The analysis results are extracted from two previously developed software assistants, providing coronary artery analysis and measurements, function analysis as well as late enhancement data investigation. As an extension we introduce a finding concept directly relating suspicious positions to the underlying data. An affine registration of CT and MR data in combination with the AHA 17-segment model enables the coupling of local findings to positions in all data sets. Furthermore, sophisticated visualization in 2D and 3D and interactive bull's eye plots facilitate a correlation of coronary stenoses and physiology. The software has been evaluated on 20 patient data sets.

The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.