ACR Phantom Research Articles

SU-E-I-54: Evaluation of High Contrast Resolution for Model Based Iterative Reconstruction of Sinus Examinations.

To evaluate high contrast resolution of Model Based Iterative Reconstruction used with typical sinus examination acquisition parameters. MBIR has recently become available as a recon option on a clinical scanner (Discovery HD750, GE Healthcare). In this work, we evaluate high contrast resolution for scan and reconstruction options that are available for sinus examinations. For this study we used our adult sinus CT protocol reconstructed with filtered back projection, and two alternative scans reconstructed with IR. Our conventional adult sinus CT protocol utilizes a high resolution scan mode which is not compatible with the scanner's IR recon option. The two additional scans are with high resolution option off, one with the head SFOV, and one with the body SFOV. Using IR and the head SFOV, reconstructed images have a 1024 × 1024 pixel matrix. Using IR and the body SFOV, reconstructed images have a 512 × 512 pixel matrix. Three evaluations of high contrast resolution are made for these images. A wire phantom is scanned for assessment of image modulation transfer function. The bar patterns of the ACR phantom are visually assessed for quality in both axial and coronal reformats. MTF curves show 50% values of 6.8, 7.5, and 7.7 lp/cm for Body IR 512 × 512, Head IR 1024 × 1024, and filtered back projection with HD Bone kernel. The 10% MFT curves for these reconstructions are 11.2, 11.9, and 12.1 lp/cm. Visual evaluation of the ACR phantom at 15 cm display field of view demonstrates resolution of the 10 lp/cm bar patterns for all reconstructions with better visualization of the axial versus coronal recons. MBIR reconstruction demonstrates high contrast resolution that is comparable with our conventional sinus examination.

SU‐C‐217BCD‐02: Evaluating the Impact of Iterative Reconstruction for Three Major CT Vendors

Purpose: Various vendors have promoted iterative reconstruction as an effective way to reduce CT radiation dose while maintaining image quality. The purpose of our exhibit is to demonstrate the effectiveness of various vendor reconstruction approaches on image quality based on a multi‐ institutional study utilizing the ACR phantom as a source of quantitative analysis. Methods: CT scans of the ACR CT QA phantom were acquired using three CT scanners (A: GE Discovery CT750 HD, B: Philips iCT, and C: Siemens FLASH). Images acquired at seven dose levels ranging from 1 to 20 mGy were reconstructed using both FBP and IR. The data acquisition was randomized and duplicated five times to reduce the effect of systematic variations. The images were reconstructed utilizing the kernel of reconstruction recommended by each manufacturer for abdominal CT studies utilizing both filtered back projection and the vendor's iterative reconstruction techniques. The phantom images were quantitatively evaluated for a number of parameters that determined spatial and contrast resolution as well as signal to noise levels. The data were entered into a spreadsheet and subsequently into a statistical package for analysis. Results: The success of iterative reconstruction varied substantially among the three vendors for the low dose CT protocols but did have a positive impact on image quality. The positive impact of iterative reconstruction was greatest for the lowest dose studies. The specific differences will be discussed in detail. Conclusions: In addition to subjective evaluation of image quality which can be affected by many parameters, it is also important to determine the impact of the newly developed CT iterative reconstruction algorithms in a quantitative manner utilizing phantoms. Our study suggests that the quantitative improvements in spatial resolution are modest. However, improvements in contrast to noise ratio are in the neighborhood of 35 to 58% depending on the exact implementation. Funding and Technical Support from National Institute of Standards and Technology is gratefully acknowledged. Technical support from each CT scanner manufacturer is also acknowledged.

SU-E-I-60: Validation of An Optically Stimulated Luminescent (OSL) Dosimeter for Use in Output Exposure Control Verification of Mammography Imaging Systems.

To develop and validate an Optically Stimulated Luminescent (OSL) dosimeter for exposure control verification of x-ray projection mammography imaging systems. The active detection element of the dosimeter is a strip of OSL material 3.0 mm wide, 0.13 mm thick and 30.0 mm long with an overlying aluminum step wedge with thicknesses of 0, 0.2, 0.4 and 0.6 mm Al, encapsulated in a light-tight plastic enclosure with outer dimensions of 10.0 mm wide, 5.4 mm thick, and 54.0 mm long. The dosimeter is used in conjunction with a breast phantom for the purpose of estimating the half-value layer (HVL), entrance surface exposure (ESE), and average glandular dose (AGD) in conventional projection mammography. ESE and HVL were computed based on analysis of exposure profiles obtained from exposed strip dosimeters. The AGD was estimated by multiplying the ESE by the appropriate exposure to dose conversion factor for the thickness and % glandular tissue fraction represented by the phantom and target-filter combination employed. The accuracy and reproducibility of the ESE, HVL and AGD estimates obtained using the dosimeter positioned on the surface of the ACR phantom at the chest wall edge, was evaluated using mammography systems utilizing different imaging receptor technology, i.e. screen-film (SF), computed radiography (CR) and direct radiography (DR) and compared against results obtained using a calibrated ion chamber fitted with a mammography probe. ESE, AGD and HVL results obtained using the OSL mammography QA dosimeter agreed with results obtained using an ion chamber to within 5-10%, depending on the target-filter combination used. Repeat readings were highly consistent with a coefficient of variation = 5%. The OSL mammography QA dosimeter has been shown to effectively estimate ESE, HVL and AGD, demonstrating its usefulness for secondary monitoring of output exposure of mammography imaging systems.

WE‐C‐110‐05: The Influence of Beam Filtration and Collimation on CT Number Accuracy in the ACR CT Accreditation Process

Purpose: The ACR accreditation process requires the submission of images of the 200 mm ACR phantom to evaluate CT number accuracy using the institutionˈs adult abdomen protocol. Difficulties in obtaining CT numbers that fall within the allowed limits may be due to the use of a protocol designed for a body significantly larger than the phantom. We show that adjusting the sFOV to a size appropriate for the phantom significantly shifts the CT numbers toward the expected values. We also show that consistent with the hypothesis that an over‐correction for scatter results in the increased CT numbers, a reduced collimation, where less scatter correction is required for reconstruction, also shifts the CT numbers in the right direction. Methods: The ACR Gammex phantom was scanned on a 64‐slice GE LightSpeed‐VCT scanner with various bowtie filters, beam collimation and sFOV using our institution`s routine adult abdomen protocol. Results: Our results show that the CT numbers for water and polyethylene fall well outside the required range if we rigidly adhere to scanning the ACR phantom with the standard protocol. The observed inaccuracy in reported CT numbers is believed to originate from over‐corrections due to scatter contributions and beam hardening effects as the phantom is significantly smaller than a typical adult abdomen. CT number accuracy was improved when a small bowtie filter was used instead of the large one. The CT number dropped to 4.02 HU for water and to −87.32 for polyethylene. CT number accuracy further improved when scanning the phantom with a 20 mm beam collimation instead of 40 mm. Conclusions: In performing the ACR image quality assessment task, the employment of a bowtie filter consistent with the size of the phantom resulted in a significant improvement in achieving the CT number accuracy requirements of the ACR.

SU‐E‐I‐91: Use of the ACR CT Accreditation Phantom for Routine Quality Assurance of CBCT Imaging Systems in a Radiotherapy Environment

Purpose: Image guided radiation therapy using cone‐beam computed tomography (CBCT) is becoming routine practice in modern radiation therapy. The purpose of this work was to develop an imaging QA program for CT and CBCT units in our department based on the ACR CT accreditation phantom (model 464, Gammex‐RMI). It has four testing modules permitting one to test CT number accuracy, slice width, low contrast resolution, image uniformity, in plane distance accuracy, and high contrast resolution reproducibly with suggested window/levels for image analysis. Methods: Baseline values were obtained from images acquired on a Phillips Brilliance Big Bore CT simulator and CBCT images acquired on three Varian OBIs. DICOM images were exported and analyzed with software (Automated CT Software, Gammex‐RMI) or manually (OsiriX). Baseline values will be used to ensure that image quality stays consistent quarterly. Results: Initial CT simulator images showed that image quality was within ACR guidelines for all tested scanning protocols. Due to image noise and reconstruction artifacts, manual analysis should be used for future analysis of CBCT images. Image analysis from two OBIs showed that the HU calibration had drifted or was not properly calibrated, while the third OBI showed reasonable agreement with accepted values. All three OBIs were unable to distinguish the low contrast resolution plugs, had the same high contrast resolution, were within 0.7 mm of the accepted in plane resolution, and were within 0.5 mm of the nominal slice width. Conclusions: Preliminary analysis shows that the ACR phantom could be modified to be more useful in evaluating the low contrast resolution of CBCT systems. Suggestions will be made as to how ACR guidelines for image analysis could be modified to better suit CBCT systems, such as for image uniformity. It is expected to eventually incorporate all departmental CT imaging systems in into this imaging QA program.

SU‐E‐J‐75: Clinical Commissioning and Quality Assurance Procedures for a Wide Bore MRI Unit Configured for Radiation Therapy Planning

Purpose: To develop a comprehensive protocol for the acceptance testing and clinical commissioning a wide bore (70cm) MRI‐Simulator for radiotherapy localization and planning.Methods: A GE 1.5T Optima 450W MR scanner was installed in our department in 2010. Standards derived from the ACR MRI Accreditation Program were used as reference for acceptance testing and commissioning. Commercially available phantoms were used to characterize magnetic field homogeneity, image intensity uniformity, high contrast spatial resolution, slice thickness, position accuracy and geometric accuracy. For 2D SE, GRE and 3D CUBE imaging sequences, in plane and through plane distortion and distortion correction accuracy with and without the GradWarp distortion algorithm provided the software was assessed. The test was performed using multi ROI at different locations off center with multiple slices using the Magphan® phantom. Couch position, couch load and laser system accuracy were also assessed. Daily QA procedures were developed for SNR, RF, isocenter position and the gradient linearity. Parameters derived from commissioning were utilized as baseline reference values for a comprehensive QA program. Results: For clinical commissioning, the MR scanner met the criteria established by the ACR MRI Accreditation Program .The results from ACR phantom showed that image quality specifications were met. The highest spatial frequencies were 9 lp/cm; visualized. The results from the monthly QA demonstrate that variations are within 1% of the commissioning data illustrating good self consistency as regards MRI simulator performance. In‐plane distortion measurements show that the distortion correction algorithm reduced the error to within acceptable (< 1mm at 30mm sup/inf to isocentre and within 2 mm at 120 mm off center) Conclusions: Analysis of the test results indicates consistent and reproducible operation of the wide bore MRI‐SIM unit. A comprehensive commissioning and QA protocol has been developed for use in the radiation oncology setting.

Variability in PET quantitation within a multicenter consortium

The purpose of this study was to evaluate the variability in quantitation of positron emission tomography (PET) data acquired within the context of a multicenter consortium. PET quantitation phantoms designed by American Association of Physicists in Medicine/ Society of Nuclear Medicine Task Group 145 were sent to the ten member sites of the Pediatric Brain Tumor Consortium (PBTC), a NIH-funded research consortium investigating the biology and therapies for brain tumors in children. The phantoms were water-filled cylinders (18.6 cm inside height and 20.4 cm inside diameter) based on the standard ACR phantom with four small, "hot" cylinders of varying diameters (8, 12, 16, 25 mm, all with 38 mm height), consisting of an equilibrium mixture of 68Ge/68Ga in an epoxy matrix. At each site, the operator added the appropriate amount of 18F to the water in the background in order to attain a feature-to-background ratio of roughly 4:1. The phantom was imaged and reconstructed as if it were a brain PET scan for the PBTC. An approximately 12 mm circular region of interest (ROI) was placed over each feature and in a central area in the background. The mean and maximum pixel values for each ROI were requested from local sites in units of activity concentration (Bq/ml) and the standard uptake value (SUV) (g/mL) based on bodyweight. The activity concentration was normalized by the decay-corrected known activity concentration for the features, and reported as the absolute recovery coefficient (RC). In addition, central analyses were performed by two observers The ten sites successfully imaged the phantom within 5 months and submitted the quantitative results and the phantom image data to the PBTC Operations and Biostatistics Center. The local site-based and central analyses yielded similar mean values for RC. Local site-based SUV measurements of the hot cylindrical features yielded greater variability than central analysis (COV range of 29.9%-42.8% compared to 7.7%-23.2%). Correcting for miscalculations in the local site reported SUVs substantially reduced the variation to levels similar to the central analysis (COV range of 8.8%-18.4%) and also led to the local sites providing a similar mean of the SUV values to those from the central analysis. In the central analysis, the use of mean SUV in place of maximum SUV for an ROI of fixed size substantially reduced the variation in the SUV values (COV ranges of 7.7%-11.3% vs. 9.3%-23.2%). Based on this investigation, a SUV variability in the range of 10%-25% due solely to instrument and analysis factors can be expected in the context of a multicenter consortium if a central reading is used and quality assurance and quality control procedures are followed. The overall SUV variability can be expected to be larger than this due to biological and protocol factors.

SU‐GG‐J‐34: Comprehensive Clinical Commissioning and Quality Assurance Procedures of a Big Bore CT Simulator in a Radiation Oncology Department

Purpose: To perform acceptance testing and clinical commissioning of a 16‐slice big bore CT‐simulator (85 cm) and comprehensive quality assurance (QA) procedures for radiation treatment planning using several phantoms. Method and Materials: This study focused on the performance evaluation of this CT simulator in a radiation oncology environment through the acceptance testing and commissioning for clinical use. Parameters derived from commissioning were used as reference values for a comprehensive QA program. Several phantoms were used in this project to evaluate the CT simulator image quality, like ACR phantom, Vendor (Philips) provided phantom and CATPHAN 504. CTDI phantom was used to evaluate the radiation dose to patients during scans. RMI phantom was used to evaluate the CT number linearity for use in the treatment planning system for density correction. Results: For clinical commissioning, the radiation dose reported in this study is lower compared to published data based on CTDI measurements. The results from ACR phantom showed that image quality specifications were met. The highest spatial frequency for two parts of the ACR phantom; abdomen and chest, there were 8 and 9 lp/cm; respectively visualized. The manufacture specification is 5 lp/cm. CT number linearity and low contrast resolution tests were also within acceptance requirements. Image quality evaluation parameters from different phantoms were compared. These showed good self consistency using this CT simulator. Conclusion: A comprehensive analysis of the test results indicates consistent and reproducible operation of the big bore CT‐simulator. This big bore CT simulator is well suited for use in a radiation oncology setting.

SU-GG-I-16: A Monte Carlo Simulation of the Imaging of Low MV Cone Beam Computed Tomography

Purpose: Megavoltage (MV) cone beam computed tomography (CBCT) using softer spectrum by either lowering the accelerating potential or using low-Z targets has been considered for image-guided radiotherapy (IGRT). In this study, projection images for 250 kVp, 1 MV and 6 MV photons were simulated and the image qualities of reconstructed CBCT were compared. Method and Materials: The Monte Carlo code EGSnrc/DOSXYZnrc was used to simulate the projection images for CBCT reconstruction using 250 kVp, 1 MV and 6 MV photons. The voxel phantom used for calculation was created from the CT images of an ACR accredit phantom with four (air, adipose, muscle, and bone) cylindrical inserts of 25 mm in diameter. For each energy, 51 projection images were simulated every 4° for 200° gantry rotation. Volumetric CBCT images were reconstructed from the calculated projection images using the Feldkamp algorithm. The image qualities of the 2D projections and 3D volumetric images were compared. Results: For 2D projection images, only the concave produced by the insert of air in the ACR phantom was observed. For 3D reconstructed CBCT images, the inserts of air and bone were quite distinguishable for all three energies. However, the inserts of adipose and muscle were only discriminated for the 250 kVp and 1 MV photons, but were barely identified for the 6MV photons. The contrast-to-noise ratios (CNR) of the 250 kVp and 1 MV images were comparable and significantly better than the 6 MV images. The imaging dose of the 1 MV and 6MV photons were respectively 5 and 18 times of the 250 kVp photons. Conclusion: The 1 MV photons could be a good option for IGRT with an image quality comparable to the 250 kVp photons and an acceptable imaging dose.

SU-GG-I-88: Physics Performance Comparisons between 256-Slice, 64-Slice and 16-Slice CT Scanners in the Clinic

Purpose: It is a challenge for the practicing medical physicist to perform quality controltesting for these scanners in a short amount of time and make comparisons between various MDCT scanners.Methods and Materials: Three Philips‐Brilliance MDCT‐scanners (256‐, 64‐ and 16‐slice) in the same hospital system were tested under the same conditions for dosimetry and image quality performance. The ACR image quality phantom was used. CTDI was measured with the standard head and body phantoms and a CTDI pencil‐chamber. OSLCT dosimeters were used to measure CTDI. Measurements were converted to mGy/100mAs in order to perform comparisons between the scanners. Dose measurements were also performed for all the collimation settings that are available for each scanner.Results: The least variation in noise was observed for the 16‐slice scanner, although all units were within acceptable limits. Although high contrast linearity was met by all units, the high contrast resolution was satisfied mostly by the 64‐ and 16‐slice scanners, for the materials included in the ACR phantom. The CT dose decreases with beam width for all scanners, an effect more pronounced in the head phantom. For the clinically programmed brain and pelvis protocols, measured CTDIw for 64‐ and 16‐ slice scanners is 15% and 60% lower than for 256‐slice unit, respectively, and for similar beam widths. OSL dosimeter measurements confirmed the chamber measurements within 2–5% in most cases for CTDIw. The 256‐slice had sharper dose profiles. The periphery profiles were sharper than the central ones. Conclusions: It is important an institution to have a QC procedure for CTscanners that will allow detail comparisons between them, under similar clinical conditions. We recommend that the physicist investigates the dosimetric behavior of the MDCT scanners not only for the clinically used collimations but all available collimations and compare the CTDI results with published literature.

Phantom evaluation of a cardiac SPECT/VCT system that uses a common set of solid-state detectors for both emission and transmission scans

BackgroundWe developed a cardiac SPECT system (X-ACT) with low dose volume CT transmission-based attenuation correction (AC). Three solid-state detectors are configured to form a triple-head system for emission scans and reconfigured to form a 69-cm field-of-view detector arc for transmission scans. A near mono-energetic transmission line source is produced from the collimated fluorescence x-ray emitted from a lead target when the target is illuminated by a narrow polychromatic x-ray beam from an x-ray tube. Transmission scans can be completed in 1 min with insignificant patient dose (deep dose equivalent <5 μSv). MethodsWe used phantom studies to evaluate (1) the accuracy of the reconstructed attenuation maps, (2) the effect of AC on image uniformity, and (3) the effect of AC on defect contrast (DC). The phantoms we used included an ACR phantom, an anthropomorphic phantom with a uniform cardiac insert, and an anthropomorphic phantom with two defects in the cardiac insert. ResultsThe reconstructed attenuation coefficient of water at 140 keV was .150 ± .003/cm in the uniform region of the ACR phantom, .151 ± .003/cm and .151 ± .002/cm in the liver and cardiac regions of the anthropomorphic phantom. The ACR phantom images with AC showed correction of the bowing effect due to attenuation in the images without AC (NC). The 17-segment scores of the images of the uniform cardiac insert were 78.3 ± 6.5 before and 87.9 ± 3.3 after AC (average ± standard deviation). The inferior-to-anterior wall ratio and the septal-to-lateral wall ratio were .99 and 1.16 before and 1.02 and 1.00 after AC. The DC of the two defects was .528 and .156 before and .628 and .173 after AC. ConclusionThe X-ACT system generated accurate attenuation maps with 1-minute transmission scans. AC improved image quality and uniformity over NC.

SU‐FF‐I‐125: Assessment of Inter and Intra‐Scanner Variation in Diffusion Tensor Imaging Using the ACR Phantom

Purpose: Diffusion Tensor Imaging (DTI) has become a widely used MRI sequence to assess patient response to many forms of therapy. In order to track small changes in patient DTI parameters in a clinical setting, knowledge of inter‐scanner and intra‐scanner variations is necessary to insure that a perceived patient therapy response is statistically significant. Ideally, inter and intra‐scanner variations should be determined from a large sample of healthy patients so that scanner specific effects can be quantified. However, this type of analysis is not practical in most institutions. Because of the lack and availability of DTI phantoms which closely model typical pathology, we will assess the usefulness of the MRI ACR phantom for this application. Method and Materials: Clinical DTI acquisitions were performed using the ACR phantom on 8 GE scanners (two 3T and six 1.5T) using an 8‐channel head coil at M.D. Anderson Cancer Center to assess inter‐scanner variations. Repeated acquisitions were also performed at each scanner to assess intra‐scanner variations. DTI image sets were analyzed using several ROIs in homogeneous regions of the phantom. Axial profiles were obtained for each ROI in each scan for several DTI parameters. Results: We have compared several DTI parameters obtained from our scans of the ACR phantom to published patient measurements as well as patient data gathered from our own institution and found that the ACR phantom is quite viable for quantification of inter and intra‐scanner variations in DTI measurement. Conclusion: This work suggests that the widely available ACR phantom may be useful for assessing DTI variability between scanners. With this information, it may be possible for institutions to schedule consecutive DTI acquisitions for a single patient on scanners which behave similarly, limiting the effects of inter‐scanner variations on physicians' ability to assess therapy response.

SU-FF-I-72: Evaluation and Comparison of Image Quality Figures for Digital Mammography

Purpose: To survey the image quality of digital mammographic units in Taiwan using a mammographic contrast‐detail phantom and an ACR accreditation phantom, and to compare image quality figures from those two phantoms. Method and Materials: The scope of the survey covered most digital mammographic units in Taiwan. On‐site measurements included phantom image acquisitions and entrance surface doses (ESD).Image acquisitions of an ACR accreditation phantom (Victoreen N‐566 18‐220) and ESD measurements were following the protocols of the ACR MammographyQuality Control Manual. A mammographic contrast‐detail phantom (CDMAM type 3.4, Artinis) with 1‐cm PMMA‐equivalent thickness was placed on the PMMA of 3 cm. The CDMAM assembling was exposed using the same technical factors as the ACR accreditation phantom. Signal‐difference‐to‐noise Ratios (SDNR) of the largest mass inside the ACR phantom were calculated by the equation, SDNR = (Mean background − Mean mass )/ (SD background 2 + SD mass 2 ) . Inverse Image quality figures (IQFinv) were calculated according to the threshold diameter (D i,min) at each contrast‐column (Ci ), IQF inv = n/Σ(D i,min ⋅C i ) . Results: Fifty‐seven digital units were surveyed, including 44 DR units and 13 CR units. The tube voltage, tube current‐time product, and ESD range from 23 to 29 kV, 36 to 182 mAs, and 3.22 to 12.4 mGy for imaging the ACR phantom. The mean values and standard deviation of SDNR are 1.97±0.31 for GE 2000D, 1.50±0.91 for GE DS, and 1.76±0.20 for Hologic Lorad Selenia. The mean values and standard deviation of IQFinv are 127±10 for GE 2000D, 120±11 for GE DS, 135±28 for Hologic Lorad Selenia, and 101±0 for Siemens Novation DR. The correlation between SNDR and IQF are mild (R 2=0.414 for GE 2000D; 0.520, GE DS; 0.446, Hologic Lorad Selenia). Conclusion: The SNDR obtained from the ACR phantom mildly correlates with the IQFinv evaluated from the CDMAM phantom.

MO‐D‐213A‐02: Practical Aspects of Nuclear Medicine Accreditation

This lecture will present a review of the specific aspects and requirements of the nuclear medicine accreditation process. Particular emphasis will be placed on the process for SPECT cameras. The specifics of the phantoms, acquisition procedures, and the review of submitted data will be presented. Examples will be given for specific cameras. Upon completion of the course participants will be able to describe:1. The characteristics of the required ACR phantom for SPECT.2. The acquisition procedures used for accreditation in nuclear medicine.3. The image characteristics evaluated by the ACR phantom reviewers.

SU‐FF‐I‐151: Effects of Varying Slice Overlap On Image Noise and SNR in 3D PET Imaging

Objective: To investigate the effects of different number of slice overlaps (SO) on image noise and SNR in 3D PET data acquisition. Materials and Methods: Three phantoms were scanned to simulate different patient sizes: (1) an ACR phantom with three cold inserts, (2) a NEMA/IEC phantom, and (3) a NEMA/IEC phantom coupled to a second NEMA/IEC phantom to act as a scatter source. The background activity concentration in the phantoms ranged between 3.5–5 kBq/cc. All phantoms were scanned in 3D on a GE‐DRX PET/CT scanner using two bed positions (3min/bed) with three different number of SOs (3, 7&amp;11) between the two bed positions. This paradigm resulted in 91, 87 &amp; 83 PET image slices for SO 3, 7 &amp; 11 respectively. 3D‐IR (2 iterations, 21 subsets) was used for all image reconstructions. For each phantom and each SO, a 7×7 square ROI was drawn on all slices of the phantom background, and the average &amp; STD of the ROI were calculated to represent the phantom background AC and noise content. SNR was then determined as the ratio between AC and noise. Noise and SNR were plotted versus different image slices for all the phantoms and SOs. Results: Increasing the slice overlap decreased the noise and improved the SNR in the overlap region. The improvement in SNR between SO3 and SO11 was 46% on average over all phantoms; while the improvement between SO7 and SO11 was 19%. For the ACR and NEMA/IEC, the SO7 and SO11 images showed relatively similar noise and SNR, while for the NEMA/IEC+Scatter, the SO3 and SO7 had similar results. Conclusion: Increasing SO improves SNR in the overlap region. An SO of 7 is optimal for intermediate size objects and should be increased to 11 for larger cross section particularly with scatter from outside the FOV.

SU‐FF‐I‐74: The Use of a Simple Contrast to Noise Ratio (CNR) Metric to Predict Low Contrast Resolution Performance in CT

Purpose: To investigate the use of a simple contrast to noise metric and its ability to predict low contrast resolution in CT scans. Method and Materials: The ACR low contrast phantom was scanned with 120 kVp and various exposure levels ranging from 50 to 1600 effective mAs. Each scan was reconstructed with 5 mm thickness and 8 different reconstruction filters, ranging from very smooth (B10) through very sharp (B80). Each image was windowed and leveled to the same settings, anonymized to reduce reader bias and put in random order. The images were sent to 9 independent readers, experienced in evaluating the ACR phantom for low contrast resolution. Each reader scored the smallest size set of rods visible in each image. Separately, a simple contrast to noise ratio (CNR) was obtained for each image, calculated as (A‐B)/σ where A is the mean of an ROI placed over the 25mm rod, B is an ROI of samesize placed in the background next to the 25mm rod, and σ is the standard deviation of the background. Results: For many of the lower exposure and filter combinations, the largest 25mm rod was not visible and no measurement of CNR could be made. For those images in which it was visible, the CNR ranged from 0.15 for 300mAs and filter B70, to 6.4 for 1600mAs and filter B10. The measured CNR does correlate well with observer performance within a reconstruction filter setting, though there is wide variability in observer performance. However, CNR did not correlate well with observer performance across reconstruction filters. Conclusion: The correlation between CNR and observer performance suggests it may be possible to use this metric to predict low contrast performance for cases with a fixed reconstruction filter and might be useful if a limited range of filters are used.

MO‐D‐213A‐03: Practical Aspects of PET Accreditation

PET scanner accreditation is based on reviews of images acquired from the ACR PET phantom. The phantom is relatively easy to fill and set up for a PET study and can be used to measure tomographic uniformity, spatial resolution, and the detectability of “hot” lesions. The variety of resolution and “hot” components enables the reviewers to see relatively subtle differences in system performance.The accreditation phantom images are submitted to a review panel of qualified medical physicists for scoring. The Nuclear Medicine Accreditation Committee has defined acceptable standards for uniformity, spatial resolution and lesion detection.Uniformity and noise are evaluated qualitatively by inspection of reconstructed tomographic sections. Optimal density ranges should be comparable to those used for clinical images. Spatial resolution is judged by identifying the smallest “cold” rods in the phantom and lesion detectability is determined from the “hot” cylinders. The same protocol is also used for the “cold” cylinders that demonstrate the effectiveness of the attenuation and scatter corrections.Learning Objectives:1. Be aware of the ACR PET accreditation process and PET Physicist Qualifications.2. Understand the ACR PET Phantom and testing required for ACR accreditation.3. Understand how phantom images are reviewed by the ACR.4. Be able to activate the ACR Phantom.5. Understand phantom image acquisition and processing.6. Understand PET phantom image contrast, resolution, and uniformity.

Experimental validation of a three‐dimensional linear system model for breast tomosynthesis

A three-dimensional (3D) linear model for digital breast tomosynthesis (DBT) was developed to investigate the effects of different imaging system parameters on the reconstructed image quality. In the present work, experimental validation of the model was performed on a prototype DBT system equipped with an amorphous selenium (a-Se) digital mammography detector and filtered back-projection (FBP) reconstruction methods. The detector can be operated in either full resolution with 85 microm pixel size or 2 x 1 pixel binning mode to reduce acquisition time. Twenty-five projection images were acquired with a nominal angular range of +/- 20 degrees. The images were reconstructed using a slice thickness of 1 mm with 0.085 x 0.085 mm in-plane pixel dimension. The imaging performance was characterized by spatial frequency-dependent parameters including a 3D noise power spectrum (NPS) and in-plane modulation transfer function (MTF). Scatter-free uniform x-ray images were acquired at four different exposure levels for noise analysis. An aluminum (Al) edge phantom with 0.2 mm thickness was imaged to measure the in-plane presampling MTF. The measured in-plane MTF and 3D NPS were both in good agreement with the model. The dependence of DBT image quality on reconstruction filters was investigated. It was found that the slice thickness (ST) filter, a Hanning window to limit the high-frequency components in the slice thickness direction, reduces noise aliasing and improves 3D DQE. An ACR phantom was imaged to investigate the effects of angular range and detector operational modes on reconstructed image quality. It was found that increasing the angular range improves the MTF at low frequencies, resulting in better detection of large-area, low-contrast mass lesions in the phantom. There is a trade-off between noise and resolution for pixel binning and full resolution modes, and the choice of detector mode will depend on radiation dose and the targeted lesion.

MO-D-352-02: Practical Aspects of Nuclear Medicine Accreditation

This lecture will present a review of the specific aspects and requirements of the nuclear medicine accreditation process. Particular emphasis will be placed on the process for SPECTcameras. The specifics of the phantoms, acquisition procedures, and the review of submitted data will be presented. Examples will be given for specific cameras. Upon completion of the course participants will be able to describe: 1. The characteristics of the required ACR phantom for SPECT. 2. The acquisition procedures used for accreditation in nuclear medicine. 3. The image characteristics evaluated by the ACR phantom reviewers.

MO-D-352-03: Practical Aspects of PET Accreditation

PET scanner accreditation is based on reviews of images acquired from the ACR PET phantom. The phantom is relatively easy to fill and set up for a PET study and can be used to measure tomographic uniformity, spatial resolution, and the detectability of “hot” lesions. The variety of resolution and “hot” components enables the reviewers to see relatively subtle differences in system performance. The accreditation phantom images are submitted to a review panel of qualified medical physicists for scoring. The Nuclear Medicine Accreditation Committee has defined acceptable standards for uniformity, spatial resolution and lesion detection. Uniformity and noise are evaluated qualitatively by inspection of reconstructed tomographic sections. Optimal density ranges should be comparable to those used for clinical images.Spatial resolution is judged by identifying the smallest “cold” rods in the phantom and lesion detectability is determined from the “hot” cylinders. The same protocol is also used for the “cold” cylinders that demonstrate the effectiveness of the attenuation and scatter corrections. Learning Objectives: 1. Be aware of the ACR PET accreditation process and PETPhysicist Qualifications. 2. Understand the ACR PET Phantom and testing required for ACR accreditation. 3. Understand how phantom images are reviewed by the ACR. 4. Be able to activate the ACR Phantom. 5. Understand phantom image acquisition and processing. 6. Understand PET phantom imagecontrast, resolution, and uniformity.