MRI is a versatile tool for systematically assessing anatomical and functional changes in small animal models of human disease. Its noninvasive nature makes MRI an ideal candidate for longitudinal evaluation of disease progression in mice; however achieving the desired level of statistical power can be expensive in terms of imaging time. This is particularly true for cancer studies, where dynamic contrast-enhanced (DCE-) MRI, which involves the repeated acquisition of anatomical images before, during, and after the injection of a paramagnetic contrast agent, is used to monitor changes in tumor vasculature. A means of reducing the overall time required to scan multiple cohorts of animals in distinct experimental groups is therefore highly desirable. Multiple-mouse MRI, in which several animals are simultaneously scanned in a common MRI system, has been successfully used to improve study throughput. However, to best utilize the next generation of small-animal MRI systems that will be equipped with an increased number of receive channels, a paradigm shift from simultaneously scanning as many animals as possible to scanning a more manageable number, at a faster rate, must be considered. Given a small-animal MRI system with 16 available receive channels, the simulations described in this work explore the tradeoffs between the number of animals scanned at once and the number of array elements dedicated to each animal for maximizing throughput. An array system consisting of 15 receive and 5 transmit coils allows throughput-optimized acceleration of a DCE-MRI protocol by a combination of multi-animal and parallel imaging techniques. The array system was designed and fabricated for use on a 7.0-T / 30-cm MRI system, and tested for high-throughput imaging performance in phantoms. Results indicate that up to a nine-fold throughput improvement is possible without sacrificing image quality compared to standard single-animal imaging hardware. A DCE-MRI study throughput improvement of just over six times that achieved with conventional single-mouse imaging was realized. This system will lower the barriers for DCE-MRI in preclinical research and enable more thorough sampling of disease pathologies that progress rapidly over time. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/20659 |
| Date | 03 July 2013 |
| Creators | Ramirez, Marc Stephen |
| Source Sets | University of Texas |
| Language | en_US |
| Detected Language | English |
| Format | application/pdf |
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