bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐C‐141‐04: Robustness of 4DCT and 4DCBCT Object Volume Measurement with a Motion‐Capable Lung Phantom That Mimics Realistic Patient Tumor Trajectories
Authors: Nyflot MJ , Bowen SR , Do J , Kinahan PE , Sandison GA
Published: July 2013

Purpose: Accurate volume estimation for time‐resolved fan‐beam CT (4DCT) and cone‐beam CT (4DCBCT) is critical to planning and verification of many motion‐sensitive radiotherapy applications, including stereotactic lung radiotherapy. We used a 4D torso phantom to acquire realistic respiratory images with 4DCT and 4DCBCT, and compared object size estimation of the two modalities. Methods: A torso phantom consisting of a water‐filled sphere surrounded by foam pellets was driven by a motion device capable of reproducing patient respiratory traces. Ten typical respiratory traces were imaged along with static and sinusoidal cases with clinically‐relevant 4DCT and 4DCBCT techniques. 4DCT images were reconstructed in ten phases at 512×512×104 voxels and 0.977×0.977×2.50 mm3/voxel (GE Advantage). 4DCBCT images were reconstructed in ten phases at 128×205×205 voxels and 2.00×2.00×2.00 mm3/voxel (Elekta XVI). Objects were contoured in MIM 5.6.3 using threshold segmentation and volumes compared between image phases. Results: Reference object size was 7.03 mL and 7.01 mL for the static CT and CBCT acquisitions, respectively. When averaged over all phases, 4DCT volume was 6.78+/−0.72 mL; however, variation between phases was large and significant in Kruskal‐Wallis rank‐sum tests (2.68‐‐10.96 mL, p<0.001). 4DCBCT showed reduced accuracy of object volume estimation relative to the static case and 4DCT in paired sign‐rank tests (μ =9.08+/−0.07 mL, p<0.001); however, 4DCBCT greatly improved consistency of estimation, as no significant differences were detected between phases (8.47‐‐9.10 mL, p=0.4). Conclusion: Variation in object volume between respiratory phases was dramatically inferior for 4DCT versus 4DCBCT, possibly due to fan‐beam CT interplay effects or superiority of diaphragm sorting versus a linear surrogate. Consequently, radiotherapy planning or gating on individual phases of 4DCT datasets has potential to cause significant error. 4DCBCT did overestimate object size relative to 4DCT due to partial volume effects. As such, higher‐resolution 4DCBCT presets should be investigated for patient verification imaging.
SU‐C‐134‐02: Radiation Dose Reduction for CT Lung Cancer Screening Using Advanced Image Reconstruction Techniques
Authors: Mathieu K , Ai H , Godoy M , Munden R , de Groot P , Chandler A , Pan T
Published: July 2013

Purpose: To reduce radiation dose to patients undergoing computed tomography (CT) for lung cancer screening while maintaining overall diagnostic image quality and definition of ground‐glass opacities (GGOs). Methods: A Catphan phantom, a Kyoto Kagaku lung screening phantom, and a Kyoto Kagaku multipurpose chest phantom were scanned on a GE Discovery CT750 HD scanner to quantitatively assess the performance of two image reconstruction algorithms (adaptive statistical iterative reconstruction [ASIR] and model‐based iterative reconstruction [MBIR]) used in conjunction with reduced tube currents relative to a standard clinical lung cancer screening protocol (51 mAs and filtered back projection [FBP] reconstruction; CTDIvol = 3.9 mGy). To further assess the algorithms performances, qualitative image analysis was conducted (in the form of a reader study) using the multipurpose chest phantom, which was implanted with eight GGOs of two densities. Results: Our quantitative image analysis indicated that tube current, and thus radiation dose, could be reduced by at least 60% from MBIR while maintaining similar noise and spatial resolution (as determined from the CT images) compared with conventional FBP. The reader study indicated that dose could be reduced by 40% (to 30 mAs or 2.3 mGy) or 60% (to 20 mAs or 1.5 mGy) from using ASIR or MBIR, respectively, while maintaining GGO definition. Additionally, the readers ratings for overall image quality were equal or better (for a given dose) when using ASIR or MBIR compared with FBP. Conclusion: Combining ASIR or MBIR with reduced tube current may allow for lower doses while maintaining overall diagnostic image quality, as well as GGO definition during CT lung cancer screening. Dr. Adam Chandler is an employee of GE Healthcare. Dr. Tinsu Pan is the owner of Texas Medical Imaging Consultants.
SU‐C‐134‐03: Selecting a Cardiac‐Specific CT System Architecture
Authors: FitzGerald P , Bennett J , Carr J , Edic P , Entrikin D , Gao H , Iatrou M , Jin Y , Liu B , Wang G , Wang J , Yin Z , Yu H , Zeng K , De Man B
Published: July 2013

Purpose: To identify the most promising system architecture(s) for a cardiac CT‐specific scanner of the future by performing a broad search and comparative evaluation of candidate architectures. Methods: We first performed a literature survey and consulted with cardiologists in order to identify the critical requirements for a cardiac CT scanner. Based on these requirements, we considered a broad range of potential architectures. We developed a scoring system to rate these candidates with respect to performance, development simplicity, and production cost (value). We applied our scoring system to identify the most promising candidate architectures. We then performed a more detailed analysis of six high‐scoring candidates; we evaluated the detailed results using a Six Sigma Priority Matrix. Results: We identified the following key requirements for a cardiac‐specific CT scanner: 300 mm transaxial field of view (FOV); 160 mm longitudinal coverage; 50 ms temporal resolution; 20 lp/mm spatial resolution; 10 Hounsfield Units (HU) noise; and <1 mSv radiation dose. Facilitated using TRIZ methods, we identified thirty potential architectures that could be applied for a cardiac‐specific CT scanner. These architectures were selected from classes including single‐and multiple‐source/detector third‐generation designs; designs with multiple focal spots in one and two dimensions; a variety of fully‐and semi‐stationary designs; and two rather novel concepts. Of these, we ultimately identified two architectures that best satisfy the key requirements and are most likely to provide a solution as a high performance CT scanner of the future: a triple‐source system and an arc‐source system. Conclusion: This work indicates that there is an opportunity to develop a CT system specifically for cardiac imaging that can substantially exceed the performance of contemporary general‐purpose CT scanners, and provide very high temporal resolution, diagnostic quality images of the entire heart, at very low radiation dose. This work was supported by NIH/NIBIB grant EB011785.
SU‐C‐134‐05: CT Contrast Media: Impact of Scanner Parameters On Enhancement and Detectability
Authors: Labby ZE , Sensakovic WF , Labby KJ , Turian J
Published: July 2013

Purpose: Uptake of iodine‐based CT contrast media (CM) results in an increase in Hounsfield Unit (HU) value, allowing for improved detectability in CT. Further, because the increase in HU is proportional to CM concentration, quantitative measurement of HU enhancement can aid diagnosis and can determine hemodynamic properties of tissues (i.e., perfusion CT). Imaging protocol parameters (e.g., reconstruction kernel) can alter the HU‐CM relationship, potentially confounding quantitation of contrast uptake. This phantom study measures the HU‐CM relationship and determines the impact of imaging protocol parameters. Methods: A solid water phantom was imaged with a Philips Big Bore CT Scanner. Eighteen custom cylinders with CM concentrations ranging from 0–50 mg of iodine/mL were placed in the phantom. Tube voltages of 90, 120, and 140kVp, current‐time products of 100 and 400mAs, and reconstruction kernels of UB (smooth) and D (hi‐res bone enhancing) were studied. A linear fit to the HU‐CM data was calculated to evaluate HU enhancement. Contrast‐to‐noise ratio (CNR) was calculated to evaluate detectability. Results: A linear relationship existed between HU and CM for all acquisitions (R‐squared > 0.99). HU‐CM linear slope ranged from 16 to 34 HU/mg‐I/mL. A tube voltage of 140kVp increased the slope by 81% when compared to 90kVp, whereas 120kVp increased the slope by 20%. Kernel D produced a 10‐15% increase in slope. For a 400mAs acquisition, CNR was optimized using 120kVp and the UB kernel, but CNR was optimized for 100mAs using 90kVp with the UB kernel. Conclusion: HU enhancement is linear with concentration; however, the slope is strongly impacted by reconstruction kernel and tube voltage. Knowledge of CT scanning parameter impact on contrast media signal enhancement and detectability can guide optimization of CT protocols and improve interpretation of quantitative CT data.
SU‐C‐134‐06: Guidance for CT Departments Desiring to Optimize Protocols for: Multiple Scanner Architectures
Authors: Szczykutowicz T , Ranallo F
Published: July 2013

Purpose: Clinical protocol development must consider a CT scanners architecture both in hardware and software. Differences in tube output, beam collimation, availability of iterative reconstruction, etc., may only allow some protocols to be properly performed on higher end scanners due to clinical constraints like breath hold duration and contrast dynamics. This study presents an overview of techniques for translating and optimizing a protocol from one scanner to another. Cases in which protocols are not compatible with a given scanner architecture are also discussed. Methods: At our institution, intensive protocol optimization is performed for each protocol using a single scanner architecture. Once a protocol is optimized in both technical and clinical parameters, the protocol can be translated to other scanner architectures (both older and newer). Essential restraints on the translation process include the maximum clinically allowable scan time and the maximum tube output of the scanner. Successful translation can be done if scan parameters can be modified within these essential constraints. If this is not possible then compromises have to be made that can affect clinical performance. Mathematical relationships related to tube output and clinical considerations will be discussed that guide the transformation and any needed compromises. Results: Several test cases are presented providing details of translating optimized protocols to an older and newer CT scanner architecture. Cases in which older scanners cannot provide the required performance are common for angiography exams that require high spatial resolution, thin reconstructed slice thickness, low noise, and fast scan times due to breath hold and contrast dynamic constraints. Conclusion: Understanding the limitations of older generation CT scanners and the benefits of newer CT architectures is critical for maintaining a uniquely optimized set of CT protocols across a wide range of CT architectures. Equipment grant from GE healthcare.
SU‐C‐116‐03: Comparisons and Limitations of Physics Instrumentation in Mammography
Authors: Brateman L , Heintz P
Published: July 2013

Purpose: To evaluate discrepancies in measurements for two major vendors of mammography equipment with a few models of physics instruments, and to make known potential errors in best use of these instruments for ACR and MQSA/FDA documentation. We show variability in responses under different beam conditions and report problems encountered. A separate study shows effects on calculated mean glandular dose. Methods: Recent mammography equipment evaluations for new installations show discrepancies in measurements of kVp and HVL with different instrumentation. This study tested well‐behaved GE Essential and Hologic Dimensions units (6 target‐filter combinations) with 3 vendors and 4 instruments (3 with solid‐state detectors, SStDs) using recommended techniques, which sometime conflict. HVLs were measured two ways: (a) single‐point measurements for the SStDs, and for some instruments, (b) with standardized mammography‐grade aluminum filtration. Particular attention was paid to HVLs near values required for mammography phantom mean glandular dose calculations (28–30 kVp). Ionization chamber measurements with Al filtration, according to ACR recommendations, were used as reference HVLs for 28, 29 and 30 kVp. Results: Measurements of kVp with SStD instruments were most consistent with Mo/Mo, with a 0.18 kV average discrepancy for all instruments (discrepancy range (−0.3,+0.4). For Mo/Mo, one vendor was consistently high and 2 low, but this trend was inconsistent among other combinations. The range of discrepancies was within 1 kV for all except Mo/Rh for one instrument and W/Ag for another. Unlike kVp, HVL measurements showed large variations. Over 28‐30 kVp, discrepancies of single‐point HVLs ranged from approximately zero to nearly 15% from reference values. It was impossible to follow manufacturers or ACR HVL measurement recommendations with aluminum for 2 of the 3 SStDs. Conclusion: : All instruments appear to function well, but data show biases which affect accuracy. Users must be careful how they interpret their data, particularly for HVL.
SU‐E‐I‐09: Measurements of KV XVI CBCT Dose Profiles in Phantom Using Gafchromic XRQA2 Film
Authors: Giaddui T , Cui Y , Galvin J , Yu Y , Xiao Y
Published: July 2013

Purpose: To measure CBCT dose profiles inside phantom using Gafchromic XRQA2 film. Methods: Gafchromic XRQA2 film (International Specialty Products, Wayne, NJ) whole sheets were placed between slabs of the IMRT head and torso free point phantom, model 002H9K (Computerized Imaging Reference Systems, Inc, Norfolk, Virginia). Doses were acquired during chest and head imaging protocols of the Volume Imager (XVI) mounted on the Elekta linar accelerator (Elekta, Crawley, UK). Scanned films were analyzed using ImageJ (National Institute of Health, Bethesda, MD). Results: For the Chest protocol (full trajectory), dose ranged between 1.25 and 2.11 cGy, with average dose of 1.78 cGy. Here, the dose increased over the first 3 cm from the right surface of the phantom, it then leveled off, with average fluctuation of around 5% (within uncertainty level, with the exception of few points where a fluctuation of 24% was observed). Dose eventually started to drop in the left side of the phantom till it reached its lowest value. For the head and neck protocol (trajectory is 200°), dose ranged between 0.02 and 0.13 cGy, with average value of 0.09 cGy. The dose was more or less uniform from the right surface of the phantom till its center (it fluctuated within uncertainty level of 20 to 40% and even higher at some low dose points) and then started to increase from almost the center of the phantom until it reached its highest value near the left surface. Conclusion: Full trajectory protocol led to uniform dose distribution in the middle part of the phantom and doses were less near surfaces. However, for a protocol with a trajectory of 200° degree, the dose was uniform in one part of the phantom and showed increase in the other part, consistent with the start/stop angle of the gantry. Measured dose fluctuated mostly within uncertainty levels. This project is funded, in part, under a grant with the Pennsylvania Department of Health. The Department specifically declaims responsibility for any analyses, interpretations or conclusions
SU‐E‐I‐11: A Simple Approach to Account and Report Organ Dose From KV Image Guidance Procedures
Authors: Nelson A , Ding G
Published: July 2013

Purpose: To explore a simple approach to report and account for dose resulting from kV imaging procedures. Methods: Patient dose distributions resulting from Varian kV‐CBCT scans with different imaging scan protocols were calculated by using Monte‐Carlo methods. A total of 29 representative patients were studied including the Standard Head(15), Low‐Dose Thorax(9), and Pelvis(5) scan protocols. Dose dependence on isocenter location was explored by simulating the same patient scanned with three different isocenters each 5cm apart in the anterior‐posterior direction. Additionally, two pediatric head scans were simulated to demonstrate size dependence for the Standard Head protocol. The patient organ doses were analyzed using in‐house software that performs DVH analysis. Conclusion: The mean organ dose ranges across patients for Standard Head scans: Eye, Brain, Brainstem, Skin, and Bone: 0.03‐0.32cGy, 0.22‐0.31cGy, 0.19‐0.29cGy, 0.26‐0.38cGy, and 0.70‐1.02cGy, respectively. The wide range in eye dose was due to isocenter dependence for the posterior 200° Standard Head scan, where the scan angle does not spare eye dose for highly anterior isocenters. For Thorax and Pelvis scans, the dose to soft tissues showed small variation: 0.32‐0.61cGy and 1.20‐2.20cGy for Thorax and Pelvis, respectively. Conclusion: The results show that both soft tissue organ doses and bone dose show small variation between the patients studied. Although a large variation was observed for eye dose from head scans due to the asymmetric scan rotation and isocenter position differences, the doses are much lower and can therefore be reasonably estimated with an upper limit. This study indicates that it may be acceptable to estimate and account for organ dose by using simple tabulated values based on scan procedure without using patient‐specific data. While this approach is not as accurate as patient‐specific calculations, the simplicity of this method can enable reporting and accounting for imaging dose in patient treatment planning feasible.
SU‐E‐I‐12: Assessment of Absorbed Dose and Image Quality Using Cone Beam CT On An X‐Ray Angiography System
Authors: Supanich M , Vanderhoek M
Published: July 2013

Purpose: Cone beam CT (CBCT) acquisitions using interventional X‐ray Angiography (XA) systems are becoming more prevalent. Patient dose should be considered when performing these studies. This work assesses absorbed radiation dose and image quality from CBCT acquisitions on an XA system. Methods: CBCT acquisitions of a CIRS tissue equivalent abdomen phantom and the Gammex ACR CT phantom were performed at 3 detector dose settings using a 90 kVp, 210 degree, 420 view, 8 second acquisition on a Siemens Artis Zee system. Radiation dose was measured using a Radcal 0.6cc ionization chamber positioned at central and peripheral locations in the abdomen phantom. Patient absorbed dose was estimated via a weighted average of the peripheral (2/3) and central (1/3) doses. Image quality was assessed via the standard deviation of the reconstructed image pixel values in a homogeneous region of the ACR CT phantom and contrast to noise ratio (CNR) measurements of the polyethylene rod to the background. For comparison, absorbed dose was measured with the same setup on a standard CT system using a clinical abdomen and pelvis protocol. Results: Estimates of patient absorbed dose for the CBCT acquisitions were 38, 26, and 15 mGy at detector dose settings of 540, 360 (default) and 200 nGy per view. The image noise at different dose settings was consistent with a 0.5 power law relationship. The absolute value of the CNR was determined to be 6.1 (540 nGy), 5.5 (360 nGy) and 3.7(200 nGy). The absorbed dose estimate for the abdomen and pelvis standard CT was 9 mGy. Conclusion: Absorbed dose from cone beam CT acquisitions on an interventional XA system is greater than that of a standard CT. The necessary image quality for a given CBCT imaging task and the potential for dose reduction should be assessed in accordance with ALARA principles. Research Grant: Siemens AG
SU‐E‐I‐17: Micro CT Analysis of Results of Protein Deficiency On Rat Offspring
Authors: Rosenbaum S , Harten T , Pope L , Swartz D , Koenigsknecht C , Rudin S , Ionita C
Published: July 2013

Purpose: To evaluate the use of image based metrics in the study of renal vascular development in offspring from low protein fed pregnant rats. Methods: Using a custom, self made micro CT imaging system, we imaged two groups of rat kidneys. The control group consisted of eight one year old Wistar rat offspring exposed to normal maternal rat diet during pregnancy. The second group, of the same breed and age, were eight offspring of a low protein maternal diet during pregnancy. Both groups were euthanized and a warm barium sulfate gelatin suspension was pressure infused into the arterial circulation, creating radio opacity for identification of the arterial vasculature. Approximately one hour after administration, the kidneys were harvested, placed in formalin, then stored at 4°C. Each kidney was imaged using our micro CT machine set from 47 to 55 kVp and 40 to 60 Watts. Results: Clearly the renal vasculature development differed greatly between the two groups. In particular, the protein deficient group developed segmental renal arteries with larger diameters. There was also a minimal difference in the percentage of arteries to tissue volume for the two groups. After examining the 3D reconstructions, we set gray level threshold values for vasculature and for tissue. We then determined the corresponding volumes and volume ratio using LabView. Utilizing the projection images, we also measured the diameter of three vessels near the hilum of the kidney, segmental arteries. On average, the control group and protein deficient artery diameters were 375.71±49.10 516.33±52.58 μm, respectively. A comparison of histograms of the vessel diameters demonstrated a minimally overlapping classification of the two groups of animals. Conclusion: Using our custom made Micro CT scanner images, we were able to quantify the physiological effect of a maternal protein deficient diet on the developmental morphology of the offspring kidney vasculature. Support: NIH Grant 2R01EB002873
SU‐E‐I‐19: Dual‐Energy CT‐Based Material Decomposition for Stoichiometric Calibration of DCE CT
Authors: Coolens C , Landry G , Varon C , Verhaegen F
Published: July 2013

Purpose: To improve the sensitivity and accuracy of contrast‐enhanced CT measurements by using atomic number extraction of Iodine‐based contrast agent concentration from dual energy CT (DECT) material decomposition. Methods: Dual energy scans of different levels of CT contrast agent concentrations (range 0– 67.5 mgI/mL) were acquired in a body phantom on a 320‐slice single‐source CT scanner (Toshiba, Aquilion 1) at 80 and 135kVp using 300mAs to minimize noise. The X‐ray spectrum was modeled with SpekCalc by adjusting nominal tube filtration to match measured half value layers at all available energies. From the CT images, the effective atomic number Zeff of the different contrast materials was calculated using DECT material decomposition written in Matlab™ and electron density values relative to water ρe/w were obtained. A stoichiometric calibration for DCE CT was done two‐fold: (a) using ρe/w per conventional single‐energy CT; and (b) employing also Zeff from DECT. Resulting accuracy of contrast concentration values were compared against known elemental compositions and the sensitivity and CNR of methods assessed. Results: Using only ρe/w resulted in poor differentiation of contrast concentration levels, with an increase in ρe/w of only 0.5% per mgI/mL. Performing the material decomposition from DECT resulted in a much wider dynamic range of Zeff per mgI/mL through its power of three dependency. DECT estimates of Zeff and ρe/w were within (9.4 ± 6.4%) and (2.1 ± 9.5%) from theoretical calculations based on dilutions of Visipaque™320 in water, with the largest deviations starting to appear above 30mgI/mL. Similar results were found from DECT analysis based on (80–120kV) scans (within 4.5%). Conclusion: DECT material decomposition is showing promise to increase the dynamic range and signal to noise ratio of contrast‐enhanced CT imaging. Future work will explore dynamic DECT of contrast enhancement.
SU‐E‐I‐21: Metal Artifact Redcution in CT for Surgical Screws: Comparison Between Two Commercially Available Software Packages
Authors: Al‐Senan R , Yester M
Published: July 2013

Purpose: To compare the performance between two available metal artifact reduction software (MAR) packages from different CT vendors to determine applicability for surgical screws, even though such use is not supported. Methods: Two vertebral screws (Al and stainless steel) were placed in the center of a water phantom (20 cm × 15 cm), with long axis perpendicular to the scan direction. Scans were performed using a GE Discovery HD750 with Dual Energy (DE) and MARS software, and Philips iCT with iDose4 and OMAR software. Reconstruction was performed with and without MAR. Assessment was performed qualitatively and quantitatively by measuring the SD in areas surrounding the screws. For the GE scanner, mono‐energy reconstructions were performed for 70, 127, and 140 keV in addition to the MARS routine. Thickness of the screws was also measured and compared to the expected size. Results: DE reduced streak artifacts and MARS further reduced artifacts for both screws. However, a portion of the middle was distorted. SD of region next to the screw tips was reduced up to 97%; whereas SD in the region under the long axis increased in some MARS images by more than 50%. O‐MAR reduced streak artifacts but less effectively than MARS but with no loss of the middle section. With OMAR, in general most images showed reduced SD in both regions by 2% to 54%. Additionally, width was significantly reduced (20% to 50%) by MARS. This effect was not noted with O‐MAR. Conclusion: Performance of MARS and O‐MAR differed considerably. MARS effectively reduced streaks along the long axis but introduced distortions in regions near the center of the screw. With O‐MAR, streaks were reduced by a lesser degree than MARS along the screws axis, but by higher degree above and below the screws with no distortion at the center.
SU‐E‐I‐24: How Does C‐Arm Rotation Affect Peak Skin Dose in Interventional Cardiology?
Authors: Pasciak A , Jones A
Published: July 2013

Purpose: Rotating the C‐arm during an interventional cardiology (IC) procedure is believed to spread radiation dose on the skin. Previous studies have shown that this practice often increases peak skin dose (PSD) in interventional radiology (IR) procedures. We sought to determine whether C‐arm rotation reduces the PSD in IC procedures and, if so, under what circumstances. Methods: Simulations were performed using a numerical ray‐tracing algorithm to analyze the effect of C‐arm rotation on PSD across a range of patient sizes, C‐arm configurations, and procedure types. Specific data on modern fluoroscopes and patient dimensions were used as inputs to the simulations. Conclusion: In many cases, modest angles completely eliminated overlap between x‐ray field sites on the skin. C‐arm rotation was most effective for large patients and small x‐ray field sizes. In cases in which overlap remained, PSD increases were generally small, and the 95% area load was reduced. One exception was craniocaudal rotation, which tended to increase PSD, substantially in some cases. The use of a prophylactic approach in which the C‐arm was rotated between small opposing left and right anterior oblique angles was effective in dividing the skin dose between two distinct skin sites. Conclusions: Rotating the C‐arm reduces PSD in IC procedures when used as either a procedural modification or a prophylactic dose reduction strategy. Tight collimation increases the benefit of C‐arm rotation. Conflict of Interest: A. S. Pasciak and A. K. Jones are founders of Fluoroscopic Safety, LLC. Fluoroscopic Safety, LLC provides educational instruction on the safe use of fluoroscopy to physicians.
SU‐E‐I‐27: Evaluation of Dose Reduction by the Clinical Implementation of a Noise Reducing Image Processing Algorithm for Neurointerventional Procedures
Authors: Omar A , Marteinsdottir M , Palmgren C , Mauti M , Soderman M , Boon S
Published: July 2013

Purpose: To quantify the change in registered patient and staff dose indicators, i.e., KAP and CAK, and to evaluate if any detrimental effects on the treatment response are introduced, by the clinical implementation of a noise reducing algorithm for neurointerventional procedures. Methods: An image processing algorithm, ClarityIQ, for the AlluraClarity (Product not yet available in the US) system has been developed by Philips (Philips Healthcare Best, The Netherlands) to achieve advanced real time noise reduction in fluoroscopy and digital subtraction angiography. With the implementation of the noise reducing algorithm, an equivalent image quality can be achieved with reduced exposure by optimizing the system settings, consequently modifying the emitted photon spectrum.A retrospective study was performed where exposure dose data with the new system settings (January–June 2012; 174 diagnostic and 138 interventional cases) was compared with data for the prior system settings (January–June 2010; 190 diagnostic and 112 interventional cases). The data was categorized according to type of diagnostic or interventional procedure. In order to evaluate the effect on the treatment response, the total number of acquisition images, duration of fluoroscopy, and total procedure time was collected. Results: The median of the total KAP and CAK (sum of frontal and lateral plane) for diagnostic and interventional procedures for the prior settings was 124 Gycm2 and 0.78 Gy, and 328 Gycm2 and 2.71 Gy, respectively. The median for diagnostic and interventional procedures with the new settings was 47 Gycm2 and 0.27 Gy, and 109 Gycm2 and 0.89 Gy, respectively. The difference in the total number of acquisition images, duration of fluoroscopy, and total procedure time was statistically negligible. Conclusion: The new system settings resulted in a significantly reduced KAP and CAK (approximately 60%), indicating reduction in both patient and staff doses, with no indication of change in treatment response.

Two of the athors are employed by Philips Healthcare, Best, The Netherlands (S. Boon and M. Mauti). The project was partly financed by Philips Healthcare.
SU‐E‐I‐38: How to CT a Horse Using a CT Scanner Built for Human Imaging
Authors: Polf J , Polf H , Rodebush C
Published: July 2013

Purpose: Veterinary medicine teaching hospitals within the United States include fully functioning radiography departments which contain a full host of modern medical imaging capabilities, including standard CT scanners, MR imagers, digital radiography, ultrasound, and nuclear imaging systems. These systems, initially designed for human use, are employed daily in both diagnostic and research imaging studies on non‐human patients. Imaging animals of different species and breeds often presents unique challenges not encountered in human imaging studies. In this work we present a case study of the clinical procedure used for performing an equine CT scan at the Boren Veterinary Teaching Hospital. Methods and Materials: For equine CT procedures, the animal is first anesthetized, loaded on a gurney and transported to prep room. In the prep room it is transferred onto a specially designed large‐animal CT table and positioned for imaging. Next, it is transported to the CT suite where the large‐animal table is docked with the scanners CT couch. The CT scanners couch is then used to drive the large‐animal table and move the animal as the helical CT scan is performed. For our case study, the head and neck of the horse was scanned as part of a study to image a large sinus carcinoma. Conclusion: The equine CT procedure took approximately 30 minutes to complete. Between eight to ten people are need to help stabilize, move, position, and lift the horse at different steps in the process. For this talk we will present a step‐by‐step description of the entire procedure, showcasing the unique challenges encountered when scanning large animals. Conclusion: The specialized needs and challenges of these imaging studies have led to many new procedural and engineering solutions, which are necessary to make scanning large animals on a CT scanner built for human imaging possible.
SU‐E‐I‐42: Size‐Specific Dose Estimates (SSDE) Modified for Lung Inhomogeneities: A Practical Approach
Authors: Mihailidis D , Tomara P , Kagadis G
Published: July 2013

Purpose: his work recommends a method of estimating the patient effective diameter (ED) parameter in the thoracic area in order to compute the Size‐Specific Dose Estimates (SSDE) for both adult and pediatric patients, taking into account the lung inhomogeneities. Methods: A well‐established method of estimating effective distance/depth (sometimes called radiological depth) in radiotherapy treatment planning for lung inhomogeneities, is recommended here. The method requires the use of an average relative electron density for the lung tissue of rho(Lung)=0.3 to be used so a corrected lateral (LAT) patient thickness and ED is determined. Based on the new ED the dose correction factor, as per TG‐204, can be selected. This method was compared with the current recommendation by TG‐204 and another correction method for lung inhomogeneities from the literature. Results: Improved estimation of patient ED that incorporates lung inhomogeneities was compared to that computed by a radiotherapy treatment planning system. The two methods agreed to within 5% for the cases studied. This difference is smaller than the 12–20% between the recommended method by TG‐204 and another published correction method. In addition, the results showed that the effective AP thickness is not necessary to be accounted for by this approach. Conclusions: A fast and easy method of computing patient effective LAT thickness and ED in order to estimate SSDE is based on the use of a relative electron density for the lung tissue. The more accurate LAT thickness and patient ED allow the selection of a dose correction factor out of the TG‐204 tables that would take into account in some way the tissue heterogeneities in the thoracic area. This method may potentially be used in cone‐beam CT image guided radiotherapy where estimation of patient imaging doses is required.
SU‐E‐I‐48: Organ Dose Measurement and Calculation for Dedicated CT Used In Radiotherapy
Authors: Cakmak E , Tuncel N , Sindir B , Yavuz M
Published: July 2013

Purpose: To investigate the organ doses of patients undergoing to General Electric (GE) Light Speed RT computed tomography (CT) device by the measurement and calculation method. Methods: The head, thorax and pelvis regions of Rando phantom scanned with 120kV, 200 mA, and 2.5 mm thickness for helical and axial mode. TLD pairs were used for dose measurements in specified 10 organ locations. Each exam was repeated and the TL counts averaged for organs. TL count conversion to dose was done for each scanning parameters using CTDI dose measurement on CT phantom. On the other hand, for calculation of organ doses at the same scanning process IMPACT software was utilized by using CTDI‐air (100 mAs) that measured by ion chambers in small and large window widths. CTDI‐air (100 mAs) in small and large window widths was 26.43 mGy and 21.17 mGy respectively. The organ doses that obtained from software and those from TLD measurements were compared. Results: In each examination the organ doses were tailored as the in‐field and out‐field radiation. The in‐field organ dose differences between TLD measurements and Impact software calculation by entering CTDI‐air (100 mAs): In helical and axial head exam the dose differences for eye, brain and thyroid were 2.8, 1 and 13.3, and 8.2, −8.3 and 9.6 mGy respectively, in helical and axial chest exam the dose differences for heart, lung, liver and kidney 2.7, 15.3 1.1 and 7.3 and, 9.1, 6.5, 0.3 and 5.2 mGy respectively, in helical and axial pelvic exam the dose differences for bladder, prostate, uterus and testis −3.6, −5.1, 1.9 and −21.7, and −3, −3.2, 1.8 and −15.5 mGy respectively. Conclusion: The availability of this program for organ dose calculations by measuring the CTDI‐air value of the CT device that used in the radiotherapy would be considered valuable.
SU‐E‐I‐49: Influence of the Phantom Length in Computed Tomography Dose Profile Dosimetry
Authors: Takei Y , Suzuki S , Koshida K , Kataoka Y , Kobayashi M , Ootsuka T
Published: July 2013

Purpose: We measured the computed tomography (CT) dose profile with CT dose phantom for several X‐ray beam widths on 64‐slice, and 320‐slice multi detector‐row CT (MDCT) using micro ionization chamber, and assessed the association of the CTDI100 value with CT dose phantom length. Methods: The CT dose profile (CTDP) was measured as Dm using radiation monitor (Model 9015, Radcal, Monrovia, CA) with micro ionization chamber (10X5‐0.18, Radcal, Monrovia, CA) which have an active length of 19 mm and a 0.18 cm3 active area on 64‐slice MDCT (Aquilion CX, Toshiba Medical Systems, Tochigi, Japan), and 320‐slice MDCT (Aquilion One, Toshiba Medical Systems, Tochigi, Japan). The MDCT systems were used with a tube voltage of 120 kV, tube current of 100 mA, rotation time of 1 second, and nominal X‐ray beam widths of 4, 12, 32, and 160 mm (4*1 mm, 4*3 mm, 64*0.5 mm, and 320*0.5 mm axial slice acquisitions, respectively). A micro ionization chamber was placed in the center of the single CT dose phantom, and we acquired several axial scans as 5 mm increments of phantom length. Then two, and three coupled dose phantom were placed together to simulate a 300‐mm‐long, and 450‐mm‐long phantom. We acquired several axial scans in similar method. Results: The observed percent increase of the Dm with extended length from 150 mm to 300 mm of the CT dose phantom was 120 % at range from −60 to 60 mm. However, it was greatly increased toward peripheral area of the DP. With extended length from 300 mm to 450 mm of CT dose phantom, the observed percent increase of the Dm was slightly increased. There was no difference in the form of the CTDP between 300‐mm‐long phantom and 450‐mm‐long phantom. Conclusion: In upward of the 300‐mm‐long CT dose phantom, there is no difference in the form of the CTDP.
SU‐E‐I‐50: Assessment of Measured, Simulated and Displayed Values of CTDI Volume
Authors: Miller G , Hu Y , Ruan C
Published: July 2013

Purpose: Computed tomography dose index (CTDI) is the most commonly used dose descriptor for imaging protocol optimization and patient dose estimation. The purpose of this research was to examine the CTDI Volume (CTDIVOL) variability by comparing measured values of CTDIVOL against simulated and machine displayed values. Methods: A GE LightSpeed VCT scanner was used in this study. Measured values of CTDIVOL were determined using a 100 mm pencil ionization chamber in standard CT PMMA head and body phantoms. A Monte Carlo (MC) simulation of the CT scanner was developed using the MCNPX software package. The CT phantoms were modeled, and the resulting simulated dose was used to calculate CTDIVOL. The machine displayed values, which are based on patient scan protocols, were recorded directly from the CT scanner. The value presented by the scanner is actually the dose to air within a CT phantom which is about 12% higher than the dose to the phantom material. The machine displayed values have been corrected in order to make valid comparisons. Results: The machine displayed values of CTDIVOL and the results from the MC simulation were compared against the measured values. The displayed values of CTDIVOL matched the measured values within 56% for both the head and body CT phantoms. The values from the MC simulation of CTDIVOL were 7–% higher for the head phantom and 5–9% lower for the body phantom. Conclusion: This study demonstrated the variations among the measured, simulated and displayed values of CTDIVOL. The displayed values were recently included in patient dose reports, so they should be calibrated periodically to avoid under or over estimating patient specific dose. The discrepancies between the simulated and measured values of CTDIVOL indicate the CT simulation model should be machine specific so it can be used for reliable patient organ dose evaluation.
SU‐E‐I‐51: Metal Artifact Reduction in CT Using Deformable Tissue‐Class Modeling
Authors: Zhuge Y , Ning H , Cheng J , Arora B , Xie H , Miller R
Published: July 2013

Purpose: The purpose of this work is to present a novel approach to reduce metal artifacts in CT using deformable tissue‐class modeling. The tissue‐class model is generated by combining information from both original corrupted image slice (original slice) with metal artifacts, and its neighboring image slice (reference slice) in the same scan, but without metal artifacts. Missing or corrupted information in the original slice is estimated from the reference slice. Methods: The proposed method consists of four major steps. (1) Reference slice is deformed to the original slice using diffeomorphic demons registration algorithm. (2) Strong bright streak including metal objects, and dark streak artifacts are segmented respectively, by applying the basic connected threshold method on the difference image between the original and deformed reference image. (3) Pixel intensities of strong bright and dark streaks in original slice are replaced by those of corresponding pixels in deformed reference slice. The k‐means clustering algorithm is then utilized to segment the original slice into four tissue classes: air, soft tissue, normal tissue, and bone. This tissue‐class model is forward projected to produce a model sinogram. (4) Corrupted projection data in the sinogram of the original slice is substituted by corresponding segments in the model sinogram. The completed sinogram is then reconstructed with the filtered back‐projection to produce the corrected image. Results: The proposed method has been tested on clincal patient data with dental fillings, prostate fiducial markers. Both qualitative and quantitative analysis indicate that image quality has been improved considerably after correction, and the proposed method outperforms the standard linear‐interpolation based method, and the method using tissue‐class modelling on the original slice only. Conclusion: A novel method for metal artifact reduction in CT has been developed. The method is capable of reducing bright and dark streaks caused by metal objects in CT.
SU‐E‐I‐62: A New Metal Artifact Reduction Algorithm Using Edge Preserving Smoothing Filter
Authors: Kim J , Nam H , An S , Oh Y , Ji y , Lee R
Published: July 2013

Purpose: Metallic materials such as tooth supplement or surgical clip lead to metal artifacts on the X‐ray computed tomographic (CT) image. In this study, we have developed a new metal artifact reduction algorithm. To improve the image quality from metal artifacted data, our algorithm uses edge preserving interpolation method with BM3D smoothing algorithm. For evaluation, we used both real human dental data with metal artifacts and metal implemented phantom. Methods: Real metal artifacted data was obtained at Ewha womans university Mokdong hospital. Metal implemented phantom containing air, water, teflon, metalis made to evaluate the performance of the proposed algorithm. With obtained projection data, metal part is extracted from the back‐projection image. Once the metal location and size is obtained, all corrupted non‐metal part is recovered using edge preserving wavelet interpolation. With interpolated data, reconstruct image with filtered back‐projection. Apply BM3D to smooth the reconstructed image with edge preserving. BM3D is a state‐of‐art smoothing algorithm, which uses block information to get the similarity of the image. Replace the metal data from the smoothed image and continue doing this forward‐and backward projection iteratively. Our algorithm is based on the iterative reconstruction algorithm combined with the wavelet based interpolation with edge preserving smoothing filter. Results: We compared the proposed algorithm with Filtered back‐projection and iterative reconstruction algorithm with bilinear interpolation and Gaussian smoothing filter. For the evaluation, we used visual comparison, and quantitative comparison using student t‐test. For the real data, there is no exact solution. Thus only visual comparison can be applied. For the phantom data, we did the quantitative error comparison as well as visual comparison. The proposed algorithm outperformed results in both real and phantom data. Conclusion: We have developed a new CT reconstruction algorithm for metal artifact reduction and demonstrated its superiority compared with other algorithms.
SU‐E‐I‐66: Quality Assurance Program for Functional MRI
Authors: Damen N , Zhou XJ
Published: July 2013

Purpose: To develop and implement an automatic algorithm for quantitatively analyzing image quality parameters in functional MRI (fMRI) studies. The image quality parameters include signal stability over time, signal‐to‐noise ratio (SNR), and ghost levels. Methods: A set of images (9 slices, 512 images per slice over a time of 8′32′) in fMRI was acquired from a spherical quality assurance (QA) phantom using a gradient‐echo echo planar imaging (EPI) sequence at 3T. For a given slice, the center of phantom was determined automatically by calculating the center of the “mass”, followed by an automatic edge‐detection algorithm to outline the phantom edge. The signal intensity in the central region of the phantom was displayed as a function of time to assess the signal stability. After a mask for the phantom was determined, the mask was shifted by 1/2 of the FOV along the phase‐encoding direction, producing a mask for the EPI ghost. The ghost mask was sub‐divided into four equal quadrants, and the average and maximum ghost intensities were evaluated in each quadrant. Ghost levels within the four quadrants were compared to infer specific root causes of the ghosts. Finally, a background noise region was automatically determined. The standard deviation and mean intensity in the noise region were used to evaluate the SNR and ghost percentage according to the ACR recommendations. Results: The above algorithm was successfully implemented in an open‐course JAVA script. The signal stability and ghost level in fMRI QA scans were automatically visualized without user intervention. Further, ghost characteristics in the four quadrants provided valuable information to reveal the causes of the ghosts, including B0‐eddy currents, linear eddy currents, and cross‐term eddy currents. Conclusion: We have developed and implemented an automated algorithm for QA analysis in fMRI studies. This algorithm is open‐source, and can be downloaded through a website.