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Stability Test for MRI Quality Assurance in Radiation Therapy

B McClain

B McClain*, A Curcuru , O Green , S Mutic , H Gach , Washington University School of Medicine, St. Louis, MO


MO-RPM-GePD-IT-1 (Monday, July 31, 2017) 3:45 PM - 4:15 PM Room: Imaging ePoster Theater

Purpose: The use of repetitive, long image acquisitions for tumor tracking and gating in MRI-guided Radiation Therapy (MRIgRT) stresses the components of the MRI. Typically, daily and monthly QA procedures use conventional MRI sequences to measure system performance but fail to evaluate the ability of the MRI to handle the stress of high-duty cycle structural or functional imaging. Stability tests can detect changes that identify incipient system failure or noise problems in the MRI environment. We implemented stability test procedures for our 0.35 T MRIgRT (ViewRay) and 1.5 T MRI simulator (Philips Ingenia) to monitor and troubleshoot the systems.

Methods: The stability test is currently performed monthly in conjunction with ACR QA tests and uses the ACR phantom. We acquire 2D TrueFISP cine acquisitions, nominally used in MRIgRT, at 0.35 T and EPI acquisitions, used for perfusion MRI, at 1.5 T. We collected simultaneous acquisitions of an ACR phantom and extracted an ROI from a single homogenous slice for every acquisition. A MatLab program was used to extract the mean pixel intensity values from inside of the ROI on each slice and calculate a normalized mean for each image over all series acquisitions. For comparison purposes, noise images were acquired and analyzed using the same method. Histogram and normalized mean plots along with the standard deviation were used to qualitatively access the stability performance of each scanner.

Results: The stability histograms provide a clear picture of image instabilities, taking into account the effects of noise on the image stability.

Conclusion: Quantitative analysis of stability plots provide a useful method to indicate whether or not a MRI system is operating properly. Ideally, stability tests should be run daily to identify system performance issues prior to the clinical scanning. However, clinical workflows make it challenging to add additional QA tests.

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