FREE BREATHING 3D CARDIAC MRI

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In cardiac MRI applications, the need to freeze or resolve both cardiac and respiratory motion poses a difficult challenge. We propose a novel approach to detect and correct for the complex respiration-induced motion of the heart, while capturing its beating motion. A respiration compensated, 3D cardiac imaging method will be developed and tested in its ability to evaluate myocardium motion, as compared to our current clinical wall-motion protocol. The specific aims are: 1. To develop and implement a very fast 3D imaging strategy. The algorithms for parallel imaging, for our UNFOLD method and for partial-Fourier imaging will be fused, and the resulting hybrid method will be implemented on a 3D steady-state free-precession (SSFP) imaging sequence. 2. To develop, implement and evaluate further additions to the fast imaging approach developed in Specific Aim 1. Novel strategies will be investigated to suppress fat signal, further suppress potential artifacts and improve spatial/temporal resolution. The resulting fast imaging method will be used to generate time series of 3D cardiac images with temporal resolution sufficient to resolve the respiratory cycle (one frame every 1 to 1.5 s). 3. To develop a method for detecting/correcting respiratory motion in a first step, and generating cardiac-phase images in a second step. The heart respiratory motion will be detected in two complementary ways: A conventional respiration monitoring stretchable belt will provide (non-quantitative) information with very high temporal resolution, while the 3D imaging scheme developed in Specific Aims 1 and 2 will provide a wealth of spatial/geometrical quantitative motionrelated information. Combining the knowledge from these two sources will allow the spatially/temporally complex respiratory-motion of the heart to be detected and correct for. In a second step, the respiration-corrected data will be converted from a time series to a cardiac-phase series of high quality 3D images. 4. To evaluate the method's performance in the task of capturing myocardium motion as compared to the protocol currently in use at our institution, a representative example of the current state-of-the-art. The goal is to verify the hypothesis that our method provides SNR, spatial resolution (which includes spatial blurring) and diagnostic value superior to those of the current protocol. Phantom experiments, simulations and imaging of volunteers and patients will be performed. The evaluation of these results will involve both objective criteria (quantitative measurements) as well as subjective criteria (clinicians' impressions on image quality).