ACR MRI Research Articles

Prostate diffusion-weighted imaging (DWI) in MR-guided radiotherapy: Reproducibility assessment on 1.5 T MR-Linac and 1.5 T MR-simulator

PurposeDiffusion-weighted imaging (DWI) holds promise for image-guided radiotherapy (MRgRT) in prostate cancer. However, challenges persist due to image distortion, artifacts, and apparent diffusion coefficient (ADC) reproducibility issues. This study aimed to assess DWI image quality and ADC reproducibility on both a 1.5 T MR-simulator and a 1.5 T MR-Linac, employing measurements from both an ACR MRI phantom and prostate cancer patients undergoing MRgRT. MethodsDW-MRI scans were conducted on 19 patients (mean age = 69 ± 8 years, with 23 MR-visible intra-prostatic lesions) and an ACR MRI phantom using a 1.5 T MR-simulator (b-values = 0, 800, 1400s/mm2) and a 1.5 T MR-Linac (b-values = 50, 500, 800 s/mm2). ADC homogeneity in the phantom was evaluated via 1D profile flatness (FL) in three directions. Image quality was assessed through qualitative 5-point Likert scale ratings and quantitative ADC and signal-to-noise ratio (SNR) measurements. Intra-observer reproducibility of image quality scores was evaluated using ICC(1, 2). Geometric distortion was measured by comparing landmark sizes on the ACR phantom against the ground truth. Mean ADC and reproducibility were assessed using Bland-Altman plots. ResultsBoth MR-simulator and MR-Linac demonstrated high ADC homogeneity (FL > 87.5% - MR-simulator: 97.23 ± 0.62%, MR-Linac: 94.75 ± 0.62%, p < 0.05) in the phantom. Image quality scores revealed acceptable ratings (≥3) for capsule demarcation, image artifacts, and geometric distortion in patients. However, intra-prostatic lesions were barely discernible in b800 images for both MR-simulator (average score = 2.37 ± 1.33) and MR-Linac (average score = 2.16 ± 1.28). While MR-Linac DWI scans exhibited significantly more severe geometric distortion than MR-simulator scans (p < 0.01), most phantom measurements fell within the image in-plane resolution of 3 mm. Significant differences were noted in MR-simulator ADC (CTV: 1.20 ± 0.14 × 10−3 mm2/s (MR-simulator) vs 1.06 ± 0.10 × 10–3 mm2/s (MR-Linac); GTV: 1.05 ± 0.21 × 10−3 mm2/s vs 0.91 ± 0.16 × 10 mm2/s, all p < 0.05), with a small non-zero bias observed in the Bland-Altman analysis (CTV: 12.3%; GTV: 14.5%). ConclusionThe significantly larger MR-simulator ADC and the small non-zero bias hint at potential systematic differences in ADC values acquired from an MR-simulator and an MR-Linac, both at 1.5 T. Although acceptable ADC homogeneity was noted, caution is warranted in interpreting MR-Linac DWI images due to occasional severe artifacts. Further studies are essential to validate DWI and ADC as reliable imaging markers in prostate cancer MRgRT.

Abstract P3-03-06: Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response

Abstract Background: Triple negative breast cancer (TNBC) has a poor prognosis. In particular, TNBC patients who have significant residual disease at the time of surgery following completion of neoadjuvant systemic therapy (NST) have an especially poor prognosis. In an effort to identify patients who are unlikely to achieve pathologic complete response (pCR), we investigated if pre-treatment breast MRI morphological characteristics and imaging response patterns during NST can predict pCR in TNBC patients. Materials and Methods: As part of a prospective IRB-approved clinical trial (ARTEMIS, NCT02276443), 199 patients with biopsy-proven stage I-III TNBC received NST and were classified as pCR or non-pCR based on histopathology at surgery. Patients underwent breast MRI at baseline (BL), after 2 cycles (C2), and 4 cycles (C4) of Adriamycin-based chemotherapy (AC). Subsequently, patients received either taxane-based NST or targeted therapy guided by mid-treatment imaging response. MRI studies were reviewed by two fellowship-trained breast radiologists who were blinded to the pathology results. ACR MRI BIRADS lexicon (5th Ed) was used to describe BL tumor morphology. Imaging response pattern at C2 and C4 MRI was classified as follows: type 0 (complete), type 1 (concentric shrinkage), type 2 (crumble), type 3 (diffuse enhancement), type 4 (stable), or type 5 (progression). Morphological baseline features and response patterns were summarized and compared to the pCR status on surgical pathology using Fisher’s exact test. P values less than 0.05 were considered statistically significant. Results: Median age was 53 years, range 24-79. Of 199 patients, 95 (48%) had pCR and 104 (52%) had non-pCR. At BL MRI, an irregularly-shaped mass and homogenous or clumped non-mass enhancement were associated with pCR (p=0.026 and p=0.013, respectively). Multifocality, peritumoral edema, and intratumoral necrosis were independent of pCR. Following NST, the most common MRI response pattern was type 1, seen with equal frequency in pCR and non-pCR at C2 (58% and 42%, respectively) and C4 (47% and 53%, respectively). The following response pattern associations were found: type 0 was associated with pCR at both C2 and C4 timepoints (p&amp;lt;0.001), while types 4 and 5 were associated with non-pCR at C2, (p&amp;lt;0.001). The four patterns: types 2, 3, 4, 5, were associated with non-pCR at C4 (p&amp;lt;0.001). Conclusion: Baseline MRI tumor morphological characteristics and MRI imaging response patterns during NST may be valuable markers for pCR prediction in TNBC. Qualitative breast MRI assessment may act as an accessible tool to identify TNBC patients who are unlikely to achieve pCR and may benefit from targeted therapies. Citation Format: Mary S Guirguis, Beatriz E Adrada, Rosalind P Candelaria, Jia Sun, Gary J Whitman, Wei T Yang, Medine Boge, Rania M Mohamed, Nabil A Elshafeey, Deanna L Lane, Huong Le-Petross, Jessica WT Leung, Lumarie Santiago, Marion E Scoggins, David A Spak, Miral Patel, Frances Perez, Peng Wei, Debu Tripathy, Jason White, Elizabeth Ravenberg, Lei Huo, Jennifer Litton, Banu Arun, Vincente Valero, Alastair Thompson, Stacy Moulder, Clinton Yam, Gaiane M Rauch. Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-06.

Longitudinal acquisition repeatability of MRI radiomics features: An ACR MRI phantom study on two MRI scanners using a 3D T1W TSE sequence

The purpose of this study was to quantitatively assess the longitudinal acquisition repeatability of MRI radiomics features in a three-dimensional (3D) T1-weighted (T1W) TSE sequence via a well-controlled prospective phantom study. Thirty consecutive daily datasets of an ACR-MRI phantom were acquired on two 1.5T MRI simulators using a 3D T1W TSE sequence. Images were blindly segmented by two observers. Post-acquisition processing was minimized but an intensity discretization (fixed bin size of 25). One hundred and one radiomics features (shape n=12; first order n=16; texture n=73) were extracted. Longitudinal repeatability of each feature was evaluated by Pearson correlation and coefficient of variance (CV68% ). Interobserver feature value agreement was also quantified using intraclass correlation coefficient (ICC) and Bland-Altman analysis. A most repeatable radiomics feature set on both scanners was determined by feature coefficient of variance (CV68% <5%), ICC (>0.75), and the ratio of the interobserver difference to the interobserver mean δ<5%. No trend of radiomics feature value changed with time. Longitudinal feature repeatability CV68% ranged 0.01-38.60% (mean/median: 12.5%/9.9%), and 0.01-40.47%, (8.49%/7.34%) on the scanners A and B. Shape features exhibited significantly better repeatability than first-order and texture features (all P<0.01). Significant longitudinal repeatability difference was observed in texture features (P<0.001) between the two scanners, but not in shape and first-order features (P>0.30). First-order and texture features had smaller interobserver-dependent variation than acquisition-dependent variation. They also showed good interobserver agreement on both scanners (A:ICC=0.80±0.23; B:ICC=0.80±0.22), independent of acquisition repeatability. The repeatable radiomics features in common on both scanners, including 12 shape features, 0 first-order features, and 3 texture features, were determined as the most repeatable MRI radiomics feature set. Radiomics features exhibited heterogeneous longitudinal repeatability, while the shape features were the most repeatable, in this phantom study with a 3D T1W TSE acquisition. The most repeatable radiomics feature set derived in this study should be helpful for the selection of reliable radiomics features in the future clinical use.

Evaluation of cine imaging during multileaf collimator and gantry motion for real-time magnetic resonance guided radiation therapy.

PurposeReal‐time magnetic resonance guided radiation therapy (MRgRT) uses 2D cine imaging for target tracking. This work evaluates the percent image uniformity (PIU) and spatial integrity of cine images in the presence of multileaf collimator (MLC) and gantry motion in order to simulate sliding window and volumetric modulated arc therapy (VMAT) conditions.MethodsPercent image uniformity and spatial integrity of cine images were measured (1) during MLC motion, (2) as a function of static gantry position, and (3) during gantry rotation. PIU was calculated according to the ACR MRI Quality Control Manual. Spatial integrity was evaluated by measuring the geometric distortion of 16 measured marker positions (10 cm or 15.225 cm from isocenter).ResultsThe PIU of cine images did not vary by more than 1% from static linac conditions during MLC motion and did not vary by more than 3% during gantry rotation. Banding artifacts were present during gantry rotation. The geometric distortion in the cine images was less than 0.88 mm for all points measured throughout MLC motion. For all static gantry positions, the geometric distortion was less than 0.88 mm at 10 cm from isocenter and less than 1.4 mm at 15.225 cm from isocenter. During gantry rotation, the geometric distortion remained less than 0.92 mm at 10 cm from isocenter and less than 1.60 mm at 15.225 cm from isocenter.ConclusionDuring MLC motion, cine images maintained adequate PIU, and the geometric distortion of points within 15.225 cm from isocenter was less than the 1 mm threshold necessary for real‐time target tracking and gating. During gantry rotation, PIU was negatively affected by banding artifacts, and spatial integrity was only maintained within 10 cm from isocenter. Future work should investigate the effects imaging artifacts have on real‐time target tracking during MRgRT.

PO-1782: Compressed sense accelerated MRI simulation: image quality assessment using an ACR MRI phantom

PO-1782: Compressed sense accelerated MRI simulation: image quality assessment using an ACR MRI phantom

Inclusion of Pediatric-Specific Indications and Procedures in the New ACR MRI Accreditation Program

MRI equipment with its complex instrumentation and adaptable software applications is vulnerable to technical and image quality problems, and maintaining quality assurance is essential. Accreditation of MRI centers by the ACR has become a routine practice for radiology departments and imaging centers across the country. In its prior format, the ACR MRI Accreditation Program had examination anatomic modules designed primarily to measure quality and validate MR performance primarily in adult imaging practices. In an effort to more closely meet the specific imaging requirements of pediatric patients, an ad hoc MR accreditation committee was created under the ACR Commission on Pediatric Imaging. The committee, consisting of ACR members from five children’s hospitals, was tasked with creating suggested revisions to the anatomic modules and helping develop pediatric-specific studies that could be adopted into the ACR MRI Accreditation Program. Updated ACR MRI accreditation anatomic modules incorporating the ad hoc committee’s recommendations were released by ACR in May 2017. This article highlights the recommendations made by the ad hoc committee. The revised modules should allow pediatric imaging centers to achieve ACR MRI accreditation for all anatomic modules and will underscore best imaging practices for patients of all ages.

Measuring image sharpness using modulation transfer function in magnetic resonance imaging

Background/Objectives: The purpose of this study was to propose a method to maintain the objectivity and validity of measuring image sharpness by changes of ETL using MTF in MRI quantitatively and provide fundamental data for future evaluation and management of magnetic resource imaging quality.Methods/Statistical analysis: We conducted phantom test using ACR MRI phantom. ImageJ and OriginPro programs were used for MTF measurement. For MTF measurement using edge method, after achieving ESF by using ImageJ, LSF was calculated by differentiation in OriginPro. Finally, MTF value was obtained through conversion. Image sharpness was defined based on 50% of MTF value.Findings: Results of sharpness measurement by ETL increase revealed that MTF 50% was decreased when ETL was increased. Sharpness comparison between 1ch head coil and 8ch brain coil at 1.5T showed that it was higher for 1ch head coil, although the difference between the two was not statistically significant. However, sharpness of 1ch head coil at 3.0T MRI was found to be significantly higher than that of 8ch brain coil at 3.0T MRI.Improvements/Applications: This study confirms the theoretical concept that MTF measured by ACR standard phantom can be used as a quantitative evaluation method for spatial resolution in the magnetic resonance medical image quality management. It can be considered a meaningful objective evaluation method.

EP-1722: Inter-observer agreement of ACR MRI phantom Test on a 1.5T MR-simulator with Flexible Coil setting

EP-1722: Inter-observer agreement of ACR MRI phantom Test on a 1.5T MR-simulator with Flexible Coil setting

SU‐F‐J‐143: Initial Assessment of Image Quality of An Integrated MR‐Linac System with ACR Phantom

Purpose/Objective(s):To assess the image quality of an integrated MR‐Linac system and compare with other MRI systems that are primarily used for diagnostic purposes.Materials/Methods:An ACR MRI quality control (QC) phantom was used to evaluate the image quality of a fully integrated 1.5T MRI‐Linac system recently installed at our institution. This system has a new split magnet design which gives the magnetic field strength of 1.5T. All images were acquired with a set of phased‐array surface coils which are designed to have minimal attention of radiation beam. The anterior coil rests on a coil holder which keeps the anterior coil's position consistent for QA purposes. The posterior coil is imbedded in the patient couch. Multiple sets of T1, T2/PD images were acquired using the protocols as prescribed by the ACR on three different dates, ranging 3 months apart.Results:The geometric distortion are within 0.5 mm in the axial scans and within 1mm in the saggital (z‐direction) scans. Slice thickness accuracy, image uniformity, ghosting ratio, high contrast detectability are comparable to other 1.5T diagnostic MRI scanners. The low‐contrast object detectability are lower comparatively, which is a result of using the body array coil. Additionally, the beam's‐eye‐view images (oblique coronal and saggital images) have minimal geometric distortion at all linac gantry angles tested. No observable changes or drift in image quality is found from images acquired 3 month apart.Conclusion:Despite the use of a body array surface coil, the image quality is comparable to that of an 1.5T MRI scanner and is of sufficient quality to pass the ACR MRI accreditation program. The geometric distortion of the MRI system of the integrated MR‐Linac is within 1mm for an object size similar to the ACR phantom, sufficient for radiation therapy treatment purpose.The authors received corporate sponsored research grants from Elekta which is the vendor for the MR‐Linac evaluated in this study.

SU‐G‐IeP1‐02: Automated SNR Analysis of MR Images Using Model‐Based Noise Determination

Purpose:To develop a robust automated method of signal‐to‐noise (SNR) analysis from MR images using a single image acquisition approach and model‐based noise determination.Methods:Three consecutive MRI phantom scans were performed according to the SNR test procedures in the 2015 ACR MRI Quality Control Manual. This was repeated for several different RF coils and on MRI scanners from two different vendors. The three images from each RF coil were analyzed by the single‐image (SNR‐ACR1) and two‐image (SNR‐ACR2) SNR analysis methods also described in the ACR QC Manual. In addition the images were analyzed by the automated method (SNR‐AUTO). The SNR‐AUTO method utilizes an ImageJ macro file that was developed to 1) segment the phantom from the background region by means of a simple histogram‐based thresholding algorithm, 2) measure the signal from a ROI encompassing 80% of the phantom area, and 3) determine noise by fitting the histogram of the background region (devoid of the phase encode direction) to a noise distribution model established in the literature.Results:The accuracy of the SNR‐AUTO analysis method is demonstrated by it yielding SNR results that on average were −0.8% ± 6.7% of the SNR‐ACR1 method and 7.5% ± 8.6% of the SNR‐ACR2 method. The SNR‐AUTO method demonstrated a higher level of reproducibility (average COV = 0.32%) than that of the other two methods (average COV = 1.01% and 1.69% for SNR‐ACR1 and SNRACR2 respectively) both of which require manual placement of ROIs. An additional finding is that the model‐based noise determination is relatively insensitive to the presence of minor artifacts in the background region.Conclusion:The SNR‐AUTO method proved to be an accurate, highly reproducible, time‐efficient method for analysis of SNR in MR images and is insensitive to minor artifacts in the noise‐measuring region.

SU‐F‐J‐153: ACR MRI Phantom Test On a 1.5T MR‐Simulator with Flexible Coils Setting and Performance Comparison to Volumetric Head Coil Setting

Purpose:To accommodate head‐and‐neck (HN) RT simulation scan with immobilization, sub‐optimized flexible radiofrequency coils have to be used on an MR‐sim rather than a volumetric head coil for diagnostic radiological (DR) applications. In this study, we present and compare ACR MRI phantom test with flexible coils setting (RT‐setting) and volumetric head coil setting (DR‐setting).Methods:Two 8‐channel array coils were wrapped close to an ACR MRI phantom placed on a flat couch‐top in RT‐setting for acquisition. ACR MRI phantom tests were conducted 10 times for each setting on a 1.5T MR‐sim. Sagittal localizer (TE/TR=20/200ms), axial T1 (TE/TR=20/500ms) and T2 scans (2TEs/TR=20,80/2000ms) were acquired (NEX=1). Acqusition and image analysis were conducted following ACR guidelines. Extra 10 RT‐setting acquisitions were obtained by enabling prescan normalization.Results:For RT‐setting without prescan normalization, all tests passed the ACR recommended criteria but image intensity uniformity. Geometric accuracy was 147.8±0.3mm and 191.0±0.4mm. Spatial resolution was 0.9mm. Slice thickness was 5.2mm±0.1mm (T1) and 5.1±0.1mm (T2). Slice position accuracy was 1.4±0.6mm, −2.2±0.3mm (T1), and 1.5±0.2mm, −2.2±0.2mm (T2). Image uniformity was 80.6%±2.6% (T1) and 80.2%±3.1% (T2) (criteria: ≥87.5% for 1.5T). Ghosting ratio was 0.0006±0.0004. Low contrast detectability was 30.7±1.7 (T1) and 22.6±3.0 (T2). Image uniformity (91.4%±4.2% and 91.8%±4.3%) and low contrast detectability (36.5±1.4 and 31.6±2.2) of DR‐setting were better than RT‐setting. Prescan normalization substantially improved image uniformity to 93.4%±0.2% and 93.4%±0.3%, but slightly compromised ghosting (0.0033±0.0004) and spatial resolution (0.9mm or 1.0mm) for RT‐setting.Conclusion:Flexible coils setting for HN‐RT simulation scan could successfully pass ACR criteria (prescan normalization enabled) and generally achieve comparable performance to volumetric coil setting, although compromise on low contrast detectability was observed probably due to the lower signal‐to‐noise ratio of the flexible coils. Our results could also serve as a reference baseline of high‐field MR‐sim QA performance under ACR guideline.

Nationwide Price Variability for an Elective, Outpatient Imaging Procedure

PurposeOut-of pocket expenses for common medical tests and procedures will become increasingly relevant as high-deductible insurance plans gain widespread adoption. The purpose of this study was to determine the variability of pricing for an outpatient, noncontrast knee MRI, based on geographic location and population. MethodsWe randomly chose nonhospital outpatient radiology centers in each state’s highest-population locality, based on a list generated from the ACR MRI Accreditation Program database. The presence of ≥2 and a maximum of 3 centers within a given locality was required for inclusion. Using a standardized script, we contacted centers by phone to determine the lowest, out-of-pocket, bundled cost (technical fee plus professional fee). The median (interquartile range) costs were calculated within each locality and region, including Midwest, Northeast, South, and West regions. A generalized linear model and Spearman’s rank correlation were used to determine the association between cost and region, and cost and population, respectively. ResultsA total of 122 outpatient centers from 43 cities were analyzed. Costs ranged from $259 to $2,042 across all centers. For centers within a locality, the difference between the minimum and maximum costs among centers ranged from $1,592 to $0; median cost differences between localities ranged from $1,488 to $325. Median cost for the West, Northeast, Midwest, and South region was $690, $500, $550, and $550, respectively (P = .849). Median cost was inversely correlated with population density (ρ = –0.417 [correlation coefficient], P = .005). ConclusionsOut-of-pocket costs for an outpatient knee MRI vary substantially across imaging centers, both locally and nationally. Cost tends to decrease with increasing local population.

MO‐G‐18C‐06: MRI QC: Effects of Multi‐Channel Coil Element Failure On Image Quality

Purpose:To quantitatively evaluate changes in phantom quality control (QC) measurements resulting from malfunctioning channels in multichannel brain coils during routine MRI QC.Methods:The large ACR MRI phantom was scanned on a 1.5T GE HDXt scanner using an 8‐channel brain array and on a 1.5T Siemens Aera using a 20‐channel head‐neck array. For the 8‐channel array, images were acquired by sequentially turning off an increasing number of adjacent channels. For the 20‐channel array, images were acquired with various combinations of active coil elements. Percent integral uniformity (PIU), signal‐to‐noise ratio (SNR) and ghosting ratio were measured with and without uniformity correction (UC).Results:For the 8‐channel array, SNR and PIU decreased with the number of inactive coil elements (57% and 34%, respectively). UC increased PIU to &gt;82% and SNR to 80%, but also increased apparent ghosting due to background nonuniformity. For the 20‐channel array, the central pair of element groups (H3‐H4) closest to the phantom had the greatest impact on image quality. Without UC, PIU and SNR were similar when all groups or both H3‐H4 were active. Without UC, PIU decreased by 50% when either H3 or H4 was deactivated. Noise greatly decreased resulting in a ∼500% increase in SNR. Without UC, SNR decreased by 60% and PIU increased when both H3‐H4 were deactivated. PIU was most affected by UC (50%–160% increase). For both coils, ghosting ratio generally increased with UC but not above ACR limit (2.5%). With UC applied, PIU failed the ACR limit (87.5%) when 2 elements of the 8‐channel array or H3‐H4 were inactive.Conclusion:Channel failure for the two multichannel arrays tested was reflected in changes in SNR and PIU. For daily MR QC, setting coil‐specific SNR, PIU and ghosting QC limits to ensure the detection of malfunctioning elements is necessary due to coil design variations.

Practical Considerations for ACR MRI Accreditation

Since 2008, nonhospital providers of advanced imaging techniques have been required to obtain and maintain accreditation from eligible accreditation bodies to receive federal reimbursements [1]. Several private insurance payers are also adopting these accreditation requirements. MRI practice at our institution has been accredited by the ACR since 2001. On the basis of our experience, we present steps and practical considerations for the efficient and timely ACR MRI accreditation.

Features of Occult Invasion in Biopsy-Proven DCIS at Breast MRI

The purpose of this study is to determine if MRI BI-RADS criteria or radiologist perception correlate with presence of invasive cancer after initial core biopsy of ductal carcinoma in situ (DCIS). Retrospective search spanning 2000-2007 identified all core-biopsy diagnoses of pure DCIS that coincided with preoperative MRI. Two radiologists fellowship-trained in breast imaging categorized lesions according to ACR MRI BI-RADS lexicon and estimated likelihood of occult invasion. Semiquantitative signal enhancement ratio (SER) kinetic analysis was also performed. Results were compared with histopathology. 51 consecutive patients with primary core biopsy-proven DCIS and concurrent MRI were identified. Of these, 13 patients (25%) had invasion at excision. Invasion correlated significantly with presence of a mass for both readers (p = 0.012 and 0.001), rapid initial enhancement for Reader 1 (p = 0.001), and washout kinetics for Reader 2 (p = 0.012). Significant correlation between washout and invasion was confirmed by SER (p = 0.006) when threshold percent enhancement was sufficiently high (130%), corresponding to rapidly enhancing portions of the lesion. Radiologist perception of occult invasion was strongly correlated with true presence of invasion. These results provide evidence that certain BI-RADS MRI criteria, as well as radiologist perception, correlate with occult invasion after an initial core biopsy of DCIS.

TU-A-103-01: MRI QA

MRI QAACR Annual Testing Requirements The ACR MRI accreditation program requires annual testing to be performed by a qualified medical physicist/MR scientist. Two of these tests are Magnetic Field Homogeneity and radio frequency Coil testing. Unfortunately, these tests are often not well understood by the medical physics community. They are often vendor specific, or require access to service protocols or passwords. In some cases they are cumbersome or impossible to perform on a particular unit. This session will give the medical physicist a better understanding of the value of these tests and guidance on how to perform them. Another portion of the annual testing is review of the technologist QA program. This is also subject to misunderstanding. Often the value of an individual test, or the proper procedures for their performance is not well understood. Guidance and recommendations for enhancing the review of the technologist QA program is also addressed in this session. Learning Objectives: 1. Identify and understand the B0 homogeneity test tools available on manufactured MRI equipment sold today. Interpret the homogeneity field test results to ensure the magnet is shimmed properly. 2. Understand the acquisition and reconstruction of phase maps. 3. Identify the pitfalls when analyzing and subtracting phase maps. 4. Understand shimming values and how they relate to the magnetic field homogeneity. 5. Use of the Bandwidth Difference Methodology to evaluate the magnetic field homogeneity. 6. Describe different approaches to performing RF coil quality control testing. 7. Discuss methods of measuring SNR and the influence of acquisition parameters on the results. 8. Recommend information to include in the coil QC record. 9. Understand the technologist's role in the quality control program. 10. Obtain tips about the technologist's quality control test. 11. Identify common image quality problems of MRI scanners. 12. Understand the importance of efficient communication to Radiologists and Physicist Understand additional QC tests (MRS, Perfusion, Diffusion, fMRI, ADNI, etc).

SU‐E‐I‐67: Effects of Normalization, Filtration, and Distortion Correction Options On MRI ACR Phantom Images

Purpose: Toptimization of clinical MR image quality through protocol design on modern scanners requires understanding a wide variety of image acquisition options. Using ACR phantom analysis results for comparison, we sought to understand the effect of these options on the resulting image quality measurements. Methods: Twenty‐six series were acquired with different combinations of normalization, filtration, distortion correction, radiofrequency mode, and gradient mode using a Siemens Aera (Erlangen, Germany) 1.5T scanner with 20‐channel head/neck phased‐array coil. The ACR T1‐weighted phantom protocol (transverse, TR=500 ms, TE=20 ms, 256×256 matrix, 5mm thickness and gap, 25 cm FOV) was used to scan a large ACR MRI phantom (J.M. Specialty Parts, San Diego, California). All images were acquired in the same session without repositioning the phantom. Automated ACR analysis was implemented in MATLAB (Mathworks, Natlick, Massachusetts) for most tests. The software results were compared to manual analysis for five series. High‐contrast resolution, slice thickness, and low‐contrast detectability (LCD) were evaluated manually for all scans following the recommendations in the ACR's Phantom Test Guidance manual (http://www.acr.org/~/media/∼/media/ACR /Documents/Accreditation/MRI/LargePhantomGuidance.pdf). Results: Scans without normalization failed ACR uniformity (1.5T) and slice thickness requirements and had lower LCD scores. Filtering with the Raw Filter degraded resolution to 1.1 mm and increased the ghosting ratio but resulted in decreased noise. On this scanner 2D (in‐plane) distortion correction can be applied prospectively or retrospectively. Results showed that prospective correction provided better geometric accuracy performance. Images acquired using whisper and fast gradient modes, as well as fast and low SAR options, resulted in poorer LCD scores compared to normal gradient and radiofrequency modes. Conclusion: MR protocol optimization requires compromise to achieve relative balance between signal, noise, uniformity, resolution, geometric accuracy and other image metrics. Phantom studies with quantitative metrics provide a robust method of determining how imaging options affect these image parameters.

Is It Time for a Dedicated Pediatric MRI ACR Accreditation Program?

Participation in ACR accreditation programs has become an essential practice for adult and pediatric imaging centers across the country. The responsibility for these ACR programs is vested in the Commission on Quality and Safety, 1 of 7 operational commissions in the ACR. The MRI Accreditation Program evaluates the qualifications of personnel, quality control programs, MR safety policies, and image quality specific to MRI. Currently, the ACR MRI Accreditation Program is designed primarily to evaluate adult MRI practices, which are in many ways not applicable to pediatric applications and facilities. In this article, the authors describe the difficulties faced during the ACR MRI Accreditation Program at a dedicated children's hospital and offer suggested changes for the process.

TU‐A‐211‐01: ACR MRI Accreditation: Process and Pitfalls

ACR MRI accreditation was initiated in 1996. Over the years, the accreditation process and requirements have evolved in order to keep pace with the rapidly changing MRI technology. This presentation will briefly review changes that have been initiated in response to the changing technology along with the evolving changes in the responsibilities of the Medical Physicist for providing advice and support for system performance, quality assurance and safety. Specific differences in the accreditation process between conventional general‐purpose MRI systems and specialty (extremity) systems used for anatomical imaging and systems used for breast imaging will be discussed. Additional requirements that have resulted from the Medicare Improvements for Patients and Providers Act (MIPPA), common reasons for accreditation failure and the anticipated changes and updates to the 2004 ACR MRI Quality Control Manual will also be discussed.Learning Objectives:1. Review the responsibilities of the Medical Physicist in the accreditation process2. Discuss the CMS/MIPPA accreditation requirements as of January 1, 2012.3. Review differences in breast and specialty (extremity) system accreditation4. Discuss common reasons for accreditation failure5. Discuss anticipated changes and updates in the ACR MRI Quality Control Manual

WE-G-217A-09: Phase Imaging Measurement of Static Magnetic Field Homogeneity.

The ACR MRI accreditation program requires measurement of the magnetic field homogeneity (MFH) in the annual QA. Full implementation of vendor methods can be very time consuming and incorporates techniques not available to clinical physicists. Conversely, many of the less involved techniques proposed tend to be less inaccurate and/or precise. Here, we propose a robust approach to MFH analysis using a simple phase mapping acquisition which is a time efficient compromise. The root mean square (r.m.s.) for MFH measurement is commonly used over multiple slices (∼24). In regions with high SNR, the MR signal can be reasonably assumed Gaussian distributed. Therefore, the standard deviation of phase values in ROI is equivalent to the r.m.s. of those. The standard deviations of phases in x, y and z are assumed uncorrelated. Thus, only axial, sagittal and coronal planes need to be acquired to approximate the MFH as opposed to a full 3D acquisition. To investigate this concept, phase images were acquired on four 1.5T clinical scanners and one 3.0 clinical scanner (MAGNETOM Espree, Siemens Medical Systems, Signa Excite HD 1.5T, and 3.0T GE Healthcare Technologies). The manufacturer phantoms were scanned using two echo times (delta_TE=TE2-TE1<5ms) using a simple 2D gradient echo acquisition to produce phase images. After acquiring phase difference images in three orthogonal planes, the standard deviation was calculated in three circular ROIs (Diameter=10, 20 and 30cm) in each plane, respectively, to estimate the MFH for the effective DSV. The MFH values in five scanners using this method were within vendor specifications for the DSV. Additionally, the measured MFH values compared favorably with vendor planned maintenance records with <0.1 ppm discrepancy. This proposed method may be a reliable and practical for regular MFH measurement in QA programs and providing an independent check of the vendor measurement.