The mouse has become the preferred species for cardiovascular research into the genetic mechanisms that underpin cardiovascular disease. In addition, mice are increasingly being used to study the evolution of anatomic and physiological responses to disease and therapy. The availability of transgenic and """"""""knockout"""""""" mice, combined with conventional pharmacologic approaches, make the mouse a uniquely powerful species in which to study cardiovascular disease. One current method for non-invasive mouse imaging (MRI) has excellent image quality but its potential for widespread application is limited by its high cost, poor temporal resolution and low throughput. We propose an ultrasound method that provides accurate, low-cost, fast and non-invasive quantification of cardiac left ventricular (LV) volumes and function in small animals. Additionally, it is easy-to-use, requires minimal mouse preparation and minimal scanning time. The spatial resolution is sufficient to enable calculation of important anatomic and physiologic parameters (chamber volumes, ejection fraction, cardiac output, etc.) Furthermore, we take advantage of the superior temporal resolution to enable assessment of mouse LV perfusion using analysis of the time evolution of myocardial video intensity following bolus injection of microbubble contrast agents.
The Specific Aims of this project are to: 1) Develop a dedicated murine ultrasound transducer array / scanner pair capable of a spatial resolution of 200 microns laterally and 100 microns axially with a frame rate of 100+ frames per second. It is believed that this may be the first phased array transducer optimized specifically for mouse heart imaging. 2) Develop a volumetric (3D) ultrasound scanner, specially matched for murine heart imaging, based on the array in Aim 1. Using positional knowledge of the acquired 2D image frames, we will interpolate to form a 3D volumetric data set. 3) Expand the capability and utility of the murine heart scanner to include advanced image processing, novel approaches to automatic LV border detection and include quantitative analysis of contrast agent-based perfusion images. 4) Perform a validation study in vitro using an ultrasound phantom and in vivo in infarcted mouse hearts using Magnetic Resonance Imaging (MRI) as a standard.
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