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Session: Imaging General ePoster Viewing [Return to Session]

The ACR MRI QC Low-Contrast Detectability Test and the Rose Model

H Gach1*, (1) Washington University School of Medicine in St. Louis, St. Louis, MO

Presentations

PO-GePV-I-24 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: MRIs routinely follow American College of Radiology (ACR) MRI quality control (QC) guidelines. However, test results depend on the MRI hardware and setup, pulse sequence parameters, and manual or automated analysis. The purpose of this study was to understand the theory behind the low-contrast detectability (LCD) test and its dependency on receiver bandwidth.

Methods: The ACR LCD test was performed on a 1.5 T Philips Ingenia MRI using body coil RF transmission and a 15-channel receiver array head coil to image the large ACR MRI phantom. T₁-weighted (T1W) and T₂-weighted (T2W) MRIs were acquired per the ACR protocols but with two repetitions to permit signal-to-noise ratio (SNR) measurements using the difference method. Receiver bandwidths were varied to affect the SNR. A single observer determined the average number of detectable spokes from the two repetitions. Region of interest (ROI) analyses were performed to measure SNR and the contrast between the spoke and the background. The contrast-to-noise ratio (CNR) was calculated based on the Rose model.

Results: The total number of spokes for T1W MRI varied from 39 for bandwidth 68 Hz/pixel to 24 for bandwidth 872 Hz/pixel. ACR recommends ≥36 spokes (1.5 T T1W). The total number of spokes for T2W MRI varied from 38 (20 ms TE) and 37 (80 ms TE) for bandwidth 109 Hz/pixel to 33.5 (20 ms TE) and 26.5 (80 ms TE) for bandwidth 364 Hz/pixel. A CNR >2 for each spoke ensured its detection.

Conclusion: The outcome of the LCD test is highly dependent on the receiver bandwidth and the skills of the observer. Thus, the test is vulnerable to “cheating” by using a low bandwidth. A CNR threshold of 2 for spoke detection is lower than the nominal Rose criterion of threshold CNR of 3-5 and warrants further investigation.

Keywords

MRI, Quality Control, Quantitative Imaging

Taxonomy

IM- MRI : Quality Control and Image Quality Assessment

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