Cardiovascular disease is still the leading cause of death worldwide. In this project we focus on the heart and the aorta. Current clinical decision making is based on several biomedical measurements and imaging, yielding geometrical and functional parameters that are compared to large population statistics (evidence-based medicine). In our group, we strive to assist clinical decision making based on accurate, functional measurements, and patients-specific models of the diseased organ.
Ultrasound imaging is a widely used imaging technique, one of the workhorses in the clinic, that is frequently used for imaging of the cardiovascular system. Ultrasound (US) has several advantages, it is non-invasive, relatively cheap, can be used at the patient’s bedside, and most importantly: is known for its high temporal and spatial resolution. Unfortunately, US is also known for its drawbacks, which are a limited field-of-view and contrast. The latter is anisotropic, as well as the resolution. In this project, we aim to tackle these physical limitations by developing so-called multiperspective US imaging techniques.
The project has four objectives:
1) developing a novel imaging platform, including
2) new methods for functional measurements on organs;
3) create patient-specific models based on these new functional imaging techniques and
4) perform extensive experimental verification and in vivo validation of the methods proposed.
In multiperspective ultrasound imaging (MPUS), we use multiple transducers rather than a single one as is the case in conventional US imaging. Systems are developed that can perform MPUS in 2-D and 3D. Algorithms are developed that can fuse the image data obtained with both transducers and/or reconstruct high quality images (higher contrast, improved resolution), with a larger field-of-view. With these new systems it is crucial to know where the probes are, a problem that is tackled using both dedicated US acquisition and image analysis techniques.
Based on the improved MPUS images, new segmentation and elastography techniques have been developed. Thanks to the availability of MPUS data, segmentation and motion estimation have improved significantly or has become feasible at all (in case of the aorta). Moreover, the data can be used to improve patient-specific models of the aorta that are currently developed to assess the mechanical state of the vessel, parameters that cannot be assessed via measurements.
To translate these new methods from bench (design/development phase) to bedside (clinical pilots), simulations and setups were introduced to test and verify the performance of the imaging techniques proposed, and in vivo pilot studies were set up. A simulation framework that can produce realistic MPUS images with a known ground truth on geometry or motion was developed, as well as experimental setups that allow testing of the new MPUS systems under more realistic conditions (i.e. biological tissue). Finally, volunteer and patient pilot studies have been organized, that allow for in vivo validation.
