Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method
Open Access
- 24 March 2018
- journal article
- research article
- Published by Wiley in Journal of Applied Clinical Medical Physics
- Vol. 19 (3), 326-335
- https://doi.org/10.1002/acm2.12311
Abstract
Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight‐channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built‐in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1‐weighted and T2‐weighted images was well‐controlled in the isocenter and 10 cm off‐center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA.Keywords
Funding Information
- National Natural Science Foundation of China (11605291, 11275270)
- Beijing Hope Run Special Fund of Cancer Foundation of China (LC2015B06)
- National Key R&D Program of China (2016YFC0904600, 2017YFC0107501)
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