On replacing the manual measurement of ACR phantom images performed by MRI technologists with an automated measurement approach

Panych, Lawrence P.; Chiou, Jr‐Yuan George; Qin, Lei; Kimbrell, Vera L.; Bussolari, Lisa; Mulkern, Robert V.

doi:10.1002/jmri.25052

Cited by 14 publications

(14 citation statements)

References 12 publications

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“…There have been a number of publications of the ACR phantom test conducted on diagnostic MRI scanners (10)(11)(12)(13)(14) for diagnostic MRI QA/QC purpose, while the reports of ACR phantom test on dedicated MR-sim are still sparse (15). Our results showed that ACR phantom image acquired on a 1.5T dedicated MR-sim generally had sufficiently good image quality to pass all ACR recommended criteria, under a compromised flexible coil setting, thus fulfilled the basic requirements for clinical service.…”

Section: Discussionmentioning

confidence: 99%

Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test

Wong

Yuan

et al. 2017

Quant. Imaging Med. Surg.

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Background: A flexible RF coil setting has to be used on an MR-simulator (MR-sim) in the head and neck simulation scan for radiotherapy (RT) purpose, while the image quality might be compromised due to the sub-optimized flexible coil compared to the normal diagnostic radiological (DR) head coil. In this study, we assessed the image quality of an MR-sim by conducting the standard American College of Radiology (ACR)MRI phantom test on a 1.5T MR-sim under RT-setting and comparing it to DR-setting.Methods: A large ACR MRI phantom was carefully positioned, aligned and scanned 9 times for each under RT-and DR-setting on a 1.5T MR-sim, following the ACR scanning instruction. Images were analyzed following the ACR guidance. Measurement results under two coil settings were quantitatively compared.Inter-observer disagreements under RT-setting between two physicists were compared using Bland-Altman (BA) analysis and intra-class correlation coefficient (ICC). Results:The MR-sim with RT-setting obtained sufficiently good image quality to pass all ACR recommended criteria. No significant difference was found in phantom length accuracy, high-contrast spatial resolution, slice thickness accuracy, slice position accuracy, and percent-signal ghosting. RT-setting significantly under-performed in low-contrast object detectability, while better performed in image intensity uniformity. BA analysis showed that 95% limit of agreement and biases of phantom test measurement under RT-setting between two observers were very small. Excellent inter-observer agreement (ICC >0.75) was achieved in all measurements except for slice thickness accuracy (ICC =0.42, moderate agreement) under RT-setting.Conclusions: Very good and highly reproducible image quality could be achieved on a 1.5T MR-sim with a flexible coil setting as revealed by the standard ACR MRI phantom test. The flexible RT-setting compromised in image signal-to-noise ratio (SNR) compared to the normal DR-setting, and resulted in reduced low-contrast object detectability.

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Section: Discussionmentioning

confidence: 99%

Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test

Wong

Yuan

et al. 2017

Quant. Imaging Med. Surg.

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“…International bodies such as the American College of Radiology (ACR) [19] and American Association of Physicists in Medicine (AAPM) [20] have given reference guidance on acceptance testing, commissioning and regular QA routines for clinical MRI scanners. The MRI QA test guidance from the ACR with its associated custom-designed phantom has become an important reference for routine MRI QA after acceptance into the ACR accreditation program [21][22][23][24][25][26]. The ACR protocol evaluates geometric accuracy, high-contrast spatial resolution, low-contrast object detectability, ghosting, image intensity uniformity, slice thickness and slice position accuracy [19].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of different quality assurance methods for magnetic resonance imaging in radiotherapy

Adjeiwaah

Garpebring

Nyholm

2020

Physics and Imaging in Radiation Oncology

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Background and purpose: There are currently no standard quality assurance (QA) methods for magnetic resonance imaging (MRI) in radiotherapy (RT). This work was aimed at evaluating the ability of two QA protocols to detect common events that affect quality of MR images under RT settings. Materials and methods: The American College of Radiology (ACR) MRI QA phantom was repeatedly scanned using a flexible coil and action limits for key image quality parameters were derived. Using an exploratory survey, issues that reduce MR image quality were identified. The most commonly occurring events were introduced as provocations to produce MR images with degraded quality. From these images, detection sensitivities of the ACR MRI QA protocol and a commercial geometric accuracy phantom were determined. Results: Machine-specific action limits for key image quality parameters set at ± mean 3 were comparable with the ACR acceptable values. For the geometric accuracy phantom, provocations from uncorrected gradient nonlinearity effects and a piece of metal in the bore of the scanner resulted in worst distortions of 22.2 mm and 3.4 mm, respectively. The ACR phantom was sensitive to uncorrected signal variations, electric interference and a piece of metal in the bore of the scanner but could not adequately detect individual coil element failures. Conclusions: The ACR MRI QA phantom combined with the large field-of-view commercial geometric accuracy phantom were generally sensitive in identifying some common MR image quality issues. The two protocols when combined may provide a tool to monitor the performance of MRI systems in the radiotherapy environment.

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“…9,10 Multiple facilities have also reported automation of at least some of the ACR QC tests [11][12][13] but were either unable to automate the detection of the LC test patterns 13 or did not provide sufficient information to be able to reproduce their LC detection algorithms. 10,12,14 The work described by Fitzpatrick 9 did include a description of their algorithm and involved the detection of LC spokes by means of a two-step approach. This involved first segmenting the central LC pattern from the image using binarization of the central circular zone containing the LC spoke patterns followed by identification of the LC spoke patterns using cross-correlation of a set of disk templates along pre-determined radial lines within the segmented central zone containing the spoke patterns.…”

Section: Introductionmentioning

confidence: 99%

“…Aside from the suite of algorithms developed by Bao et al that have been in use at our institution since 2007, other fully automated QC computer algorithms have been described . Multiple facilities have also reported automation of at least some of the ACR QC tests but were either unable to automate the detection of the LC test patterns or did not provide sufficient information to be able to reproduce their LC detection algorithms . The work described by Fitzpatrick did include a description of their algorithm and involved the detection of LC spokes by means of a two‐step approach.…”

Section: Introductionmentioning

confidence: 99%

Automated low‐contrast pattern recognition algorithm for magnetic resonance image quality assessment

et al. 2017

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On replacing the manual measurement of ACR phantom images performed by MRI technologists with an automated measurement approach

Abstract: The technologists' geometry measurements may be able to be replaced by automated measurement without compromising the weekly QC program required by the ACR.

Cited by 14 publications

References 12 publications

Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test

Image quality assessment of a 1.5T dedicated magnetic resonance-simulator for radiotherapy with a flexible radio frequency coil setting using the standard American College of Radiology magnetic resonance imaging phantom test

Sensitivity analysis of different quality assurance methods for magnetic resonance imaging in radiotherapy

Automated low‐contrast pattern recognition algorithm for magnetic resonance image quality assessment

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