Uniform Phantom Research Articles

Non-local means filter denoising for DEXA images.

Dual high and low energy images of Dual Energy X-ray Absorptiometry (DEXA) suffer from noises due to the use of weak amount of X-rays. Denoising these DEXA images could be a key process to enhance and improve a Bone Mineral Density (BMD) map which is derived from a pair of high and low energy images. This could further improve the accuracy of diagnosis of bone fractures, osteoporosis, and etc. In this paper, we present a denoising technique for dual high and low energy images of DEXA via non-local means filter (NLMF). The noise of dual DEXA images is modeled based on both source and detector noises of a DEXA system. Then, the parameters of the proposed NLMF are optimized for denoising utilizing the experimental data from uniform phantoms. The optimized NLMF is tested and verified with the DEXA images of the uniform phantoms and real human spine. The quantitative evaluation shows the improvement of Signal-to-Noise Ratio (SNR) for the high and low phantom images on the order of 30.36% and 27.02% and for the high and low real spine images on the order of 22.28% and 33.43%, respectively. Our work suggests that denoising via NLMF could be a key preprocessing process for clinical DEXA imaging.

Quantification and monitoring of PET/CT data in multicentre trials: The Swiss SAKK 56/07 trial experience

AimTo outline the importance of continuous monitoring of quantitative positron emission tomography (PET) data in multicentre trials to minimize quantitative bias in longitudinal intra-patient PET studies in light of the multicentre SAKK 56/07 experience in quantification and monitoring 18F-FDG PET/CT data. Patients and methodsWe collected 64 uniform phantom 18F-FDG PET acquisitions periodically at the enrolling centres (12 European institutions). A core-laboratory analysed them for standard uptake value (SUV) accuracy (desired 1.00±10%) and acceptable image noise was defined by a coefficient of variation (COV) less than 15%. In total, 151 patients 18F-FDG PET acquisitions (baseline and follow-up) were also collected and analysed to verify longitudinal coherence of main acquisition/reconstruction parameters (DICOM tags verification) and patient preparation, in particular the uptake time (desired uptake time [UT]=60±10min). ResultsUniform phantom PET acquisition satisfied the inclusion criteria in 58/64 (89%) examinations. All PET scanner exhibited comparable SUV quantification, but we found large dispersion in terms of noise, with COV ranging 3–15%. Only 1 phantom PET acquisition was out of range with COV=21.5%. Patient data exhibited important variation in uptake time with UT=65±10min (mean±SD), with only 111/151 (74%) patients’ examinations satisfying inclusion criteria while 26% were out of range. ConclusionsRegular monitoring of PET data in multicentre trials is capital to ensure longitudinal intra-patient PET data consistence and minimize quantitative bias while it helps to spread the culture of quality in participating centre. Recent EARL (EANM Research Ltd) standardization and unification of procedures is a welcome step in this direction.

Fan-beam scanning laser optical computed tomography for large volume dosimetry

A prototype scanning-laser fan beam optical CT scanner is reported which is capable of high resolution, large volume dosimetry with reasonable scan time. An acylindrical, asymmetric aquarium design is presented which serves to 1) generate parallel-beam scan geometry, 2) focus light towards a small acceptance angle detector, and 3) avoid interference fringe-related artifacts. Preliminary experiments with uniform solution phantoms (11 and 15 cm diameter) and finger phantoms (13.5 mm diameter FEP tubing) demonstrate that the design allows accurate optical CT imaging, with optical CT measurements agreeing within 3% of independent Beer-Lambert law calculations.

Model-Based Normalization of a Fractional-Crystal Collimator for Small-Animal PET Imaging.

Previously, we proposed to use a coincidence collimator to achieve fractional-crystal resolution in PET imaging. We have designed and fabricated a collimator prototype for a small-animal PET scanner, A-PET. To compensate for imperfections in the fabricated collimator prototype, collimator normalization, as well as scanner normalization, is required to reconstruct quantitative and artifact-free images. In this study, we develop a normalization method for the collimator prototype based on the A-PET normalization using a uniform cylinder phantom. We performed data acquisition without the collimator for scanner normalization first, and then with the collimator from eight different rotation views for collimator normalization. After a reconstruction without correction, we extracted the cylinder parameters from which we generated expected emission sinograms. Single scatter simulation was used to generate the scattered sinograms. We used the least-squares method to generate the normalization coefficient for each LOR based on measured, expected and scattered sinograms. The scanner and collimator normalization coefficients were factorized by performing two normalizations separately. The normalization methods were also verified using experimental data acquired from A-PET with and without the collimator. In summary, we developed a model-base collimator normalization that can significantly reduce variance and produce collimator normalization with adequate statistical quality within feasible scan time.

Qualification of National Cancer Institute-Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials.

The National Cancer Institute developed the Centers for Quantitative Imaging Excellence (CQIE) initiative in 2010 to prequalify imaging facilities at all of the National Cancer Institute-designated comprehensive and clinical cancer centers for oncology trials using advanced imaging techniques, including PET. Here we review the CQIE PET/CT scanner qualification process and results in detail. Methods: Over a period of approximately 5 y, sites were requested to submit a variety of phantoms, including uniform and American College of Radiology-approved phantoms, PET/CT images, and examples of clinical images. Submissions were divided into 3 distinct time periods: initial submission (T0) and 2 requalification submissions (T1 and T2). Images were analyzed using standardized procedures, and scanners received a pass or fail designation. Sites had the opportunity to submit new data for scanners that failed. Quantitative results were compared across scanners within a given time period and across time periods for a given scanner. Results: Data from 65 unique PET/CT scanners across 56 sites were submitted for CQIE T0 qualification; 64 scanners passed the qualification. Data from 44 (68%) of those 65 scanners were submitted for T2. From T0 to T2, the percentage of scanners passing the CQIE qualification on the first attempt rose from 38% for T1 to 67% for T2. The most common reasons for failure were SUV outside specifications, incomplete submission, and uniformity issues. Uniform phantom and American College of Radiology-approved phantom results between scanner manufacturers were similar. Conclusion: The results of the CQIE process showed that periodic requalification may decrease the frequency of deficient data submissions. The CQIE project also highlighted the concern within imaging facilities about the burden of maintaining different qualifications and accreditations. Finally, for quantitative imaging-based trials, further evaluation of the relationships between the level of the qualification (e.g., bias or precision) and the quality of the image data, accrual rates, and study power is needed.

The Effect of Administered Activity on Patient Radiation dose and Image Quality in SPECT at Korle-Bu Teaching Hospital

The study discussed two parameters these include; administered activity (patients dose) and image quality. The aim is to determine the relationship between administered activity with resultant patient radiation dose and the quality of images produced. This will help make appropriate recommendation to the technologist and the nuclear medicine physician to produce images that would answer clinical question and at the same time maintain a balance with patient's radiation dose and its prognostic consequences. The study include both quadrant bar phantom study and patient image study in the form of static and dynamic studies. To determine image quality both the quadrant bar phantom and the patients images were assess by using SNR. The quadrant bar phantom was imaged by placing it on flood field uniform phantom which contained the radionuclide. The flood field uniformity phantom was filled with water and then an injected activity, which varied between 5 to 45 mCi of Tc-99 m were added and mixed thoroughly by several shaking for about 5 minutes. Images of the quadrant bar phantom together with real patients’ images with varied injected activities were analyzed. The study shows that as the administered activity increases from 5 to 45mCi the image quality increases significantly, which is based on the increase in SNR. Where the image quality increases from 17.06 to 22.29 in LEAP collimator and 13.56 to 21.51 in LEHR collimator using patients’ static images. In addition, the image quality also increases from 18.26 to 20.44 in LEAP and 13.51 to 21.47 in LEHR collimator using quadrant bar phantom studies. Furthermore, in the of dynamic patients images, the SNR had minimal variation from 5.40 to 29.86 in LEAP and 7.11 to 21.99 in LEHR. Furthermore the reduction in administered activity increases the acquisition time from 7 to 20mins for LEAP collimator and 8 to 22 mins for LEHR collimator. In addition, with the phantom study, the acquisition time increases from 12 to 19 mins for LEAP and 13 to 15 mins for LEHR collimator. Dynamic studies varies slightly in acquisition time just approximately a min increase with increase in administered activity.

Image Noise Analysis of a Large Ring PET Scanner

Image noise analysis of a large ring PET scanner “macro PET” performed using two different phantoms, namely a Jaszczak SPECT phantom and a uniform cylindrical phantom. In the present work, simple 2D filtered back projection was used to reconstruct all the images, and in almost all the cases a Hamming filter of cutoff frequency 0.4 and a 256 by 256 matrix with zoom factors from 1 to 4 were used in order to investigate the imaging capabilities of the new scanner and the influence of filter and cut-off frequency on the filtered back projected images. Results indicate that 11.1 mm cold rod in the Jaszczak phantom images can consistently be seen. The Coefficient of variation (CV) results for Hann and Hamming filters are very similar and increase approximately in linear fashion with higher cutoff frequency. The value of CV for the Parsen filter is lower than the value for Hann and Hamming filters. It concludes that all filters with low cut off-frequency (0.6) would suppress image noise but decrease contrast.

A Novel Two-Compartment Model for Calculating Bone Volume Fractions and Bone Mineral Densities From Computed Tomography Images.

Osteoporosis is a disease characterized by a degradation of bone structures. Various methods have been developed to diagnose osteoporosis by measuring bone mineral density (BMD) of patients. However, BMDs from these methods were not equivalent and were incomparable. In addition, partial volume effect introduces errors in estimating bone volume from computed tomography (CT) images using image segmentation. In this study, a two-compartment model (TCM) was proposed to calculate bone volume fraction (BV/TV) and BMD from CT images. The TCM considers bones to be composed of two sub-materials. Various equivalent BV/TV and BMD can be calculated by applying corresponding sub-material pairs in the TCM. In contrast to image segmentation, the TCM prevented the influence of the partial volume effect by calculating the volume percentage of sub-material in each image voxel. Validations of the TCM were performed using bone-equivalent uniform phantoms, a 3D-printed trabecular-structural phantom, a temporal bone flap, and abdominal CT images. By using the TCM, the calculated BV/TVs of the uniform phantoms were within percent errors of ±2%; the percent errors of the structural volumes with various CT slice thickness were below 9%; the volume of the temporal bone flap was close to that from micro-CT images with a percent error of 4.1%. No significant difference (p >0.01) was found between the areal BMD of lumbar vertebrae calculated using the TCM and measured using dual-energy X-ray absorptiometry. In conclusion, the proposed TCM could be applied to diagnose osteoporosis, while providing a basis for comparing various measurement methods.

Activity concentration measurements using a conjugate gradient (Siemens xSPECT) reconstruction algorithm in SPECT/CT.

The interest in quantitative single photon emission computer tomography (SPECT) shows potential in a number of clinical applications and now several vendors are providing software and hardware solutions to allow 'SUV-SPECT' to mirror metrics used in PET imaging. This brief technical report assesses the accuracy of activity concentration measurements using a new algorithm 'xSPECT' from Siemens Healthcare. SPECT/CT data were acquired from a uniform cylinder with 5, 10, 15 and 20 s/projection and NEMA image quality phantom with 25 s/projection. The NEMA phantom had hot spheres filled with an 8 : 1 activity concentration relative to the background compartment. Reconstructions were performed using parameters defined by manufacturer presets available with the algorithm. The accuracy of activity concentration measurements was assessed. A dose calibrator-camera cross-calibration factor (CCF) was derived from the uniform phantom data. In uniform phantom images, a positive bias was observed, ranging from ∼6% in the lower count images to ∼4% in the higher-count images. On the basis of the higher-count data, a CCF of 0.96 was derived. As expected, considerable negative bias was measured in the NEMA spheres using region mean values whereas positive bias was measured in the four largest NEMA spheres. Nonmonotonically increasing recovery curves for the hot spheres suggested the presence of Gibbs edge enhancement from resolution modelling. Sufficiently accurate activity concentration measurements can easily be measured on images reconstructed with the xSPECT algorithm without a CCF. However, the use of a CCF is likely to improve accuracy further. A manual conversion of voxel values into SUV should be possible, provided that the patient weight, injected activity and time between injection and imaging are all known accurately.

Reliable measurements for an image-derived sample volume in an open-configuration MR system

Open-configuration magnetic resonance (MR) systems are becoming desirable for volume measurements of off-center samples due to their non-claustrophobic system configuration, excellent soft-tissue contrast, high efficiency, and low-cost. However, geometric distortion is produced by the unwanted background magnetic field and hinders volume measurements. The present study describes the characteristics of geometric distortion in off-center samples such as the thigh muscle and adipose tissue measurements using an open-type MR system. The American Association of Physicists in Medicine uniformity and linearity phantom was used for the detection and the evaluation of the geometric distortion. The geometric distortion decreased near the isocenter and increased toward the off-center. A cylindrical phantom image was acquired at the isocenter and was used as the distortion-free, reference image. Two cylindrical phantoms were scanned off-center at a position analogous to that of the human thigh. The differences between the two cylindrical phantom volumes and the reference volume were 1.62 % ± 0.16 and 5.18 % ± 0.14. Off-center-related MR imaging requires careful consideration for image interpretation and volumetric assessment of tissue.

Comparison of Bolus Materials to Highly Absorbent Polypropylene and Rayon Cloth

This study assesses the utility of a highly absorbent polypropylene and rayon cloth (HAPRC) as a bolus material in radiation therapy. A comparison of various bolus materials used clinically at our center to the test bolus material, water-saturated HAPRC, was conducted. The reproducibility of the physical density was assessed by computerized tomography (CT) scanning the water-saturated HAPRC on a uniform density block phantom on multiple occasions, allowing the cloth to dry fully between subsequent CT scans. The cloth was found to have a consistent physical density between 0.8 and 1.0 g/cm3. To evaluate the dosimetric impact of the various bolus materials, metal oxide semiconductor field effect transistor dosimetry measurements were performed for a 6 MV treatment beam on the anterior surface of an anthropomorphic thorax phantom. The ability of the bolus material to conform to an irregular surface was assessed by CT scanning the various bolus materials overlaying the nose of an anthropomorphic head phantom and another irregularly shaped test object. The HAPRC conforms well to irregular contours and is relatively inexpensive compared to Superflab and thermoplastic sheets. Before implementing the material into the clinical setting, an appropriate process for laundering the material should be determined, for hygienic reasons.

Automatic exposure control calibration and optimisation for abdomen, pelvis and lumbar spine imaging with an Agfa computed radiography system

The use of three physical image quality metrics, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQm) have recently been examined by our group for their appropriateness in the calibration of an automatic exposure control (AEC) device for chest radiography with an Agfa computed radiography (CR) imaging system. This study uses the same methodology but investigates AEC calibration for abdomen, pelvis and spine CR imaging. AEC calibration curves were derived using a simple uniform phantom (equivalent to 20 cm water) to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated abdomen, pelvis and spine images (created from real patient CT datasets) with appropriate detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated images contained clinically realistic projected anatomy and were scored by experienced image evaluators. Constant DDI and CNR curves did not provide optimized performance but constant eNEQm and SNR did, with the latter being the preferred calibration metric given that it is easier to measure in practice. This result was consistent with the previous investigation for chest imaging with AEC devices. Medical physicists may therefore use a simple and easily accessible uniform water equivalent phantom to measure the SNR image quality metric described here when calibrating AEC devices for abdomen, pelvis and spine imaging with Agfa CR systems, in the confidence that clinical image quality will be sufficient for the required clinical task. However, to ensure appropriate levels of detector air kerma the advice of expert image evaluators must be sought.

Phantom criteria for qualification of brain FDG and amyloid PET across different cameras.

BackgroundWhile fluorodeoxyglucose (FDG) and amyloid PET is valuable for patient management, research, and clinical trial of therapeutics on Alzheimer’s disease, the specific details of the PET scanning method including the PET camera model type influence the image quality, which may further affect the interpretation of images and quantitative capabilities. To make multicenter PET data reliable and to establish PET scanning as a universal diagnostic technique and a verified biomarker, we have proposed phantom test procedures and criteria for optimizing image quality across different PET cameras.ResultsAs the method, four physical parameters (resolution, gray-white contrast, uniformity, and image noise) were selected as essential to image quality for brain FDG and amyloid PET and were measured with a Hoffman 3D brain phantom and a uniform cylindrical phantom on a total of 12 currently used PET models. The phantom radioactivity and acquisition time were determined based on the standard scanning protocol for each PET drug (FDG, 11C-PiB, 18F-florbetapir, and 18F-flutemetamol). Reconstruction parameters were either determined based on the methods adopted in ADNI, J-ADNI, and other research and clinical trials or optimized based on measured phantom image parameters under various reconstruction conditions.As the result, phantom test criteria were proposed as follows: (i) 8 mm FWHM or better resolution and (ii) gray/white %contrast ≥55 % with the Hoffman 3D brain phantom and (iii) SD of 51 small region of interests (ROIs) ≤0.0249 (equivalent to 5 % variation) for uniformity and (iv) image noise (SD/mean) ≤15 % for a large ROI with the uniform cylindrical phantom. These criteria provided image quality conforming to those multicenter clinical studies and were also achievable with most of the PET cameras that are currently used.ConclusionsThe proposed phantom test criteria facilitate standardization and qualification of brain FDG and amyloid PET images and deserve further evaluation by future multicenter clinical studies.

Assessing task performance in FFDM, DBT, and synthetic mammography using uniform and anthropomorphic physical phantoms.

The purpose of this study is to quantify the differences in detectability between full field digital mammography (FFDM), digital breast tomosynthesis (DBT), and synthetic mammography (SM) for challenging, low contrast signals, in the context of both a uniform and an anthropomorphic, textured phantom. Images of the phantoms were acquired using a Hologic Selenia Dimensions system. Images were taken at 50%, 100%, and 200% of the dose delivered under automatic exposure control (AEC). Low-contrast disks, created using an inkjet printer with iodine-doped ink, were inserted into the phantom. The disks varied in diameter from 210 to 630 μm, and in local contrast from 1.1% to 2.8% in regular increments. Human observers located the disks in a 4 alternative forced choice experiment. Proportion correct (PC) was computed as the number of correct localizations out of the total number of tries. Overall, scores from FFDM and DBT were consistently greater than scores from SM. At an exposure corresponding to the AEC setting, mean PC scores for the largest disks with the uniform phantom were 0.80 for FFDM, 0.83 for DBT, and 0.66 for SM, with the same rank ordering at other doses. Scores were similar but lower for the nonuniform background. At an exposure twice the AEC setting, however, the difference between uniform and nonuniform scores was most pronounced for DBT alone. Differences between scores for FFDM and SM were statistically significant, while those between FFDM and DBT were not. Scores were used to compute the minimum contrast level needed to reach 62.5% detection rate. The minimum contrast for SM was 36%-81% higher compared to FFDM or DBT, in either background. This study shows that an anthropomorphic phantom and lesions inserts may be used to conduct a reader study. Detectability was significantly lower for synthetic mammography than for FFDM or DBT, for all conditions. Additionally, observer performance was consistently lower for the anthropomorphic phantom, indicating the greater challenge due to anatomical background. Because of this, it may be important to use realistic phantoms in observer studies in order to draw conclusions that are more clinically relevant.

Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features.

Purpose:To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules.Methods:This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs. For the lung nodule cases, the reference condition was selected to be 100% of clinical dose with FBP reconstruction using the B45f kernel; feature values calculated from other conditions were compared to this reference condition. A measure was introduced, which the authors refer to as Q, to assess the stability of features across different conditions, which is defined as the ratio of reproducibility (across conditions) to repeatability (across repeat contours) of each feature.Results:The water phantom results demonstrated substantial variability among feature values calculated across conditions, with the exception of histogram mean. Features calculated from lung nodules demonstrated similar results with histogram mean as the most robust feature (Q ≤ 1), having a mean and standard deviation Q of 0.37 and 0.22, respectively. Surprisingly, histogram standard deviation and variance features were also quite robust. Some GLCM features were also quite robust across conditions, namely, diff. variance, sum variance, sum average, variance, and mean. Except for histogram mean, all features have a Q of larger than one in at least one of the 3% dose level conditions.Conclusions:As expected, the histogram mean is the most robust feature in their study. The effects of acquisition and reconstruction conditions on GLCM features vary widely, though trending toward features involving summation of product between intensities and probabilities being more robust, barring a few exceptions. Overall, care should be taken into account for variation in density and texture features if a variety of dose and reconstruction conditions are used for the quantification of lung nodules in CT, otherwise changes in quantification results may be more reflective of changes due to acquisition and reconstruction conditions than in the nodule itself.

Transmission imaging for integrated PET-MR systems

Attenuation correction for PET-MR systems continues to be a challenging problem, particularly for body regions outside the head. The simultaneous acquisition of transmission scan based μ-maps and MR images on integrated PET-MR systems may significantly increase the performance of and offer validation for new MR-based μ-map algorithms. For the Biograph mMR (Siemens Healthcare), however, use of conventional transmission schemes is not practical as the patient table and relatively small diameter scanner bore significantly restrict radioactive source motion and limit source placement. We propose a method for emission-free coincidence transmission imaging on the Biograph mMR. The intended application is not for routine subject imaging, but rather to improve and validate MR-based μ-map algorithms; particularly for patient implant and scanner hardware attenuation correction. In this study we optimized source geometry and assessed the method’s performance with Monte Carlo simulations and phantom scans. We utilized a Bayesian reconstruction algorithm, which directly generates μ-map estimates from multiple bed positions, combined with a robust scatter correction method. For simulations with a pelvis phantom a single torus produced peak noise equivalent count rates (34.8 kcps) dramatically larger than a full axial length ring (11.32 kcps) and conventional rotating source configurations. Bias in reconstructed μ-maps for head and pelvis simulations was ⩽4% for soft tissue and ⩽11% for bone ROIs. An implementation of the single torus source was filled with 18F-fluorodeoxyglucose and the proposed method quantified for several test cases alone or in comparison with CT-derived μ-maps. A volume average of 0.095 cm−1 was recorded for an experimental uniform cylinder phantom scan, while a bias of <2% was measured for the cortical bone equivalent insert of the multi-compartment phantom. Single torus μ-maps of a hip implant phantom showed significantly less artifacts and improved dynamic range, and differed greatly for highly attenuating materials in the case of the patient table, compared to CT results. Use of a fixed torus geometry, in combination with translation of the patient table to perform complete tomographic sampling, generated highly quantitative measured μ-maps and is expected to produce images with significantly higher SNR than competing fixed geometries at matched total acquisition time.

TH-AB-209-11: Breast Microcalcification Classification Using Spectral X-Ray Coherent Scatter Computed Tomography

Purpose: To investigate the ability of Coherent Scatter Computed Tomography (CSCT) to distinguish non-invasively between type I calcifications, consisting of calcium oxalate dihydrate (CO) compounds which are more often associated with benign lesions, and type II calcifications containing hydroxyapatite (HA) which are predominantly associated with malignant tumors. Methods: The coherent scatter cross sections of HA and CO were measured using an energy dispersive x-ray diffractometer. The measured cross sections were introduced into MC-GPU Monte Carlo simulation code for studying the applicability of CSCT to discriminate between the two types of microcalcifications within the whole breast. Simulations were performed on a virtual phantom with inserted HA and CO spots of different sizes and placed in regions of interest having different background compositions. We considered a polychromatic x-ray source and an energy resolving photon counting detector. We applied an algorithm that estimates scatter components in projection space in order to obtain material-specific images of the breast. As material components adipose, glandular, HA and CO were used. The relative contrast of HA and CO components were used for type I and type II microcalcification discrimination. Results: The reconstructed CSCT images showed material-specific component-contrast values, with the highest CO or HA component contrast corresponding generally to the actual CO or HA feature, respectively. The discrimination performance varies with the x-ray intensity, calcification size, and background composition. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to unity. Conclusion: The simulation results obtained for a uniform breast imaging phantom indicate that CSCT has potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications.

SU‐F‐I‐43: A Software‐Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

Purpose:The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor‐specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions.Methods:MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student's t‐distribution to compute the LCD as the minimal Hounsfield Unit's that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue‐mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam‐hardening filters and phantom lengths.Results:As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image.Conclusion:The proposed metric and its associated software tools are vendor‐independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.

SU‐C‐207A‐06: On‐Line Beam Range Verification with Multiple Scanning Particle Beams: Initial Feasibility Study with Simulations

Purpose:To investigate the feasibility and requirement for intra‐fraction on‐line multiple scanning particle beam range verifications (BRVs) with in‐situ PET imaging, which is beyond the current single‐beam BRV with extra factors that will affect the BR measurement accuracy, such as beam diameter, separation between beams, and different image counts at different BRV positions.Methods:We simulated a 110‐MeV proton beam with 5‐mm diameter irradiating a uniform PMMA phantom by GATE simulation, which generated nuclear interaction‐induced positrons. In this preliminary study, we simply duplicated these positrons and placed them next to the initial protons to approximately mimic the two spatially separated positron distributions produced by two beams parallel to each other but with different beam ranges. These positrons were then imaged by a PET (∼2‐mm resolution, 10% sensitivity, 320×320×128 mm^3 FOV) with different acquisition times. We calculated the positron activity ranges (ARs) from reconstructed PET images and compared them with the corresponding ARs of original positron distributions.Results:Without further image data processing and correction, the preliminary study show the errors between the measured and original ARs varied from 0.2 mm to 2.3 mm as center‐to‐center separations and range differences were in the range of 8–12 mm and 2–8 mm respectively, indicating the accuracy of AR measurement strongly depends on the beam separations and range differences. In addition, it is feasible to achieve ≤ 1.0‐mm accuracy for both beams with 1‐min PET acquisition and 12 mm beam separation.Conclusion:This study shows that the overlap between the positron distributions from multiple scanning beams can significantly impact the accuracy of BRVs of distributed particle beams and need to be further addressed beyond the established method of single‐beam BRV, but it also indicates the feasibility to achieve accurate on‐line multi‐beam BRV with further improved method.

SU‐G‐IeP4‐01: A Simple Doppler Flow Phantom Design for Evaluation of Doppler Ultrasound Systems

Purpose:There are a number of commercially available flow phantoms for evaluating Doppler ultrasound systems. However, it may be hard to justify purchasing these phantoms if a hospital has a small number of ultrasound units to evaluate. In this study, we developed a simple flow phantom with parts available in a hospital to evaluate Doppler ultrasound systems.Methods:To create a flow reserve, one end of an IV line was connected to a 100 ml saline bag and the line was filled with saline. 20 ml of glycerin was injected into the saline bag to simulate blood like flow characteristics. The other end of the IV line was also connected to the saline bag to create a loop. The IV line was fed into an infusion pump (programmable up to 999 ml/hr) and was also placed between a uniform ultrasound phantom and a standoff gel pad. To minimize impedance differences, acoustic gel was used between the phantom and the gel pad. Doppler measurements were performed on two Philips iU22 ultrasound units using the L12‐5 probes.Results:The pulsatile flow of the solution in the IV line could be seen in the Doppler mode when the infusion pump was running. The color Doppler also indicated the direction of the flow via overlaid red or blue color on the grayscale B‐mode ultrasound image of the IV line. The directionality of the flow could be confirmed by reversing the direction of the probe. The peak flow rates (cm/s) observed on the waveforms were reproducible within %10 when the measurements were repeated.Conclusion:A simple flow phantom can be developed from materials available in a hospital for routine evaluation of Doppler ultrasound systems.