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At least 253 records · Page 14

SU-F-T-463: Light-Field Based Dynalog Verification

Purpose: To independently verify leaf positions in so-called dynalog files for a Varian iX linac with a Millennium 120 MLC. This verification provides a measure of confidence that the files can be used directly as part of a more extensive intensity modulated radiation therapy / volumetric modulated arc therapy QA program. Methods: Initial testing used white paper placed at the collimator plane and a standard hand-held digital camera to image the light and shadow of a static MLC field through the paper. Known markings on the paper allow for image calibration. Noise reduction was attempted with removal of ‘inherent noise’ from an open-field light image through the paper, but the method was found to be inconsequential. This is likely because the environment could not be controlled to the precision required for the sort of reproducible characterization of the quantum noise needed in order to meaningfully characterize and account for it. A multi-scale iterative edge detection algorithm was used for localizing the leaf ends. These were compared with the planned locations from the treatment console. Results: With a very basic setup, the image of the central bank A leaves 15–45, which are arguably the most important for beam modulation, differed from the planned location by [0.38±0.28] mm. Similarly, for bank B leaves 15–45 had a difference of [0.42±0.28] mm Conclusion: It should be possible to determine leaf position accurately with not much more than a modern hand-held camera and some software. This means we can have a periodic and independent verification of the dynalog file information. This is indicated by the precision already achieved using a basic setup and analysis methodology. Currently, work is being done to reduce imaging and setup errors, which will bring the leaf position error down further, and allow meaningful analysis over the full range of leaves.

60 APPLIED LIFE SCIENCES↗

Electrical Impedance Tomography Technology: 2013 Center Innovation Fund Final Report

Electrical impedance tomography is a medical noninvasive imaging technology which has advantages over other medical imaging technologies for medically safe long term real time internal imaging monitoring applications in human patients. The technology is much more compact, portable, low power and potentially more low cost compared to other medical image technologies, making it very well suited for medical aerospace and spaceflight applications. EIT technology’s main drawback has been low image resolution, and consequently improving EIT resolution is the primary research goal, as well as increasing imaging speed for real time animation imaging. In a relatively short time the BERL group has brought together design plans, technical resources and has built and tested hardware with the purpose of improving EIT imaging technology. EIT prototype system development plans and system designs have been made to target needed EIT technical improvement in electronic and computer hardware as well as EIT software technology. New hardware design and fabrication resources and technologies have been brought together through resourceful use of existing equipment and software at BERL, and a significant advance has been made in custom electronic hardware prototyping capabilities in collaboration with EFAL, for mutual benefit for both NASA KSC laboratories. BERL has gained significant EIT software capability and tested EIT imaging algorithm code through collaboration with an internationally recognized EIT software development and research forum. A new custom workstation has been developed, built and tested using internal resources, equipment and expertise, that includes a new state-of-the-art massively parallel technology that is commercially available. Custom prototype hardware has been designed and tested, a high priority electronic design, key to improving electronic performance and image quality, has been researched and tested in four designs, with a summary of test results of the selected design illustrated here. The selected design performance exceeds the developed EIT design hardware specifications.

Michael R Lapointe↗

Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors

Purpose: To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiation therapy (SBRT). Methods and Materials: A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during SBRT for abdominal tumors. Kilovoltage images were acquired at 5- to 6-second intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for 3 sessions for each patient. Results: Intrafraction displacement patterns varied between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm, and 1.2% exceeded 0.75 cm. The calculated single-session dose to 95% of gross tumor volume differed from planned by an average of −1.2% (range, −11.1% to 4.8%) but only for 4 patients was the total 3-session calculated dose to 95% of gross tumor volume more than 3% different from planned. Conclusions: Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

WE-G-204-09: Medical Physics 2.0 in Practice: Automated QC Assessment of Clinical Chest Images

Purpose: To determine whether a proposed suite of objective image quality metrics for digital chest radiographs is useful for monitoring image quality in our clinical operation. Methods: Seventeen gridless AP Chest radiographs from a GE Optima portable digital radiography (DR) unit (Group 1), seventeen (routine) PA Chest radiographs from a GE Discovery DR unit (Group 2), and sixteen gridless (non-routine) PA Chest radiographs from the same Discovery DR unit (Group 3) were chosen for analysis. Groups were selected to represent “sub-standard” (Group 1), “standard-of-care” (Group 2), and images with a gross technical error (Group 3). Group 1 images were acquired with lower kVp (90 vs. 125), shorter source-to-image distance (127cm vs 183cm) and were expected to have lower quality than images in Group 2. Group 3 was expected to have degraded contrast versus Group 2.This evaluation was approved by the institutional Quality Improvement Assurance Board (QIAB). Images were anonymized and securely transferred to the Duke University Clinical Imaging Physics Group for analysis using software previously described{sup 1} and validated{sup 2}. Image quality for individual images was reported in terms of lung grey level(Lgl); lung noise(Ln); rib-lung contrast(RLc); rib sharpness(Rs); mediastinum detail(Md), noise(Mn), and alignment(Ma); subdiaphragm-lung contrast(SLc); and subdiaphragm area(Sa). Metrics were compared across groups. Results: Metrics agreed with published Quality Consistency Ranges with three exceptions: higher Lgl, lower RLc, and SDc. Higher bit depth (16 vs 12) accounted for higher Lgl values in our images. Values were most internally consistent for Group 2. The most sensitive metric for distinguishing between groups was Mn followed closely by Ln. The least sensitive metrics were Md and RLc. Conclusion: The software appears promising for objectively and automatically identifying substandard images in our operation. The results can be used to establish local quality consistency ranges and action limits per facility preferences.

60 APPLIED LIFE SCIENCES↗

SU-C-209-06: Improving X-Ray Imaging with Computer Vision and Augmented Reality

Purpose: To determine the feasibility of using a computer vision algorithm and augmented reality interface to reduce repeat rates and improve consistency of image quality and patient exposure in general radiography. Methods: A prototype device, designed for use with commercially available hardware (Microsoft Kinect 2.0) capable of depth sensing and high resolution/frame rate video, was mounted to the x-ray tube housing as part of a Philips DigitalDiagnost digital radiography room. Depth data and video was streamed to a Windows 10 PC. Proprietary software created an augmented reality interface where overlays displayed selectable information projected over real-time video of the patient. The information displayed prior to and during x-ray acquisition included: recognition and position of ordered body part, position of image receptor, thickness of anatomy, location of AEC cells, collimated x-ray field, degree of patient motion and suggested x-ray technique. Pre-clinical data was collected in a volunteer study to validate patient thickness measurements and x-ray images were not acquired. Results: Proprietary software correctly identified ordered body part, measured patient motion, and calculated thickness of anatomy. Pre-clinical data demonstrated accuracy and precision of body part thickness measurement when compared with other methods (e.g. laser measurement tool). Thickness measurements provided the basis for developing a database of thickness-based technique charts that can be automatically displayed to the technologist. Conclusion: The utilization of computer vision and commercial hardware to create an augmented reality view of the patient and imaging equipment has the potential to drastically improve the quality and safety of x-ray imaging by reducing repeats and optimizing technique based on patient thickness. Society of Pediatric Radiology Pilot Grant; Washington University Bear Cub Fund.

60 APPLIED LIFE SCIENCES↗

A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images

In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.

Memon, Nasir D.↗

Neutrino Heating Drives a Supernova (Silent Animation)

When a neutron star forms, compression creates heat that generates neutrinos. When the star’s core collapses, a shock wave propagates around the star but stalls. The neutrinos reenergize a stalled shock wave, and the convection created leads to an asymmetric explosion that shoots elements into the cosmos. The heat content, or entropy, is shown, with greater entropy represented by “warmer” hues. At center is a volume rendering of the developing explosion above the newly formed neutron star (based on a simulation with the CHIMERA code); side images of orthogonal slices through the star reveal additional detail. The movie starts 100 milliseconds after the formation of the neutron star, depicts the shockwave’s bounce and follows astrophysical events up to 432 milliseconds after the bounce.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT

Purpose: Variation in function of different lung regions has been ignored so far for conventional lung cancer treatment planning, which may lead to higher risk of radiation induced lung disease. 4DCT based lung ventilation imaging provides a novel yet convenient approach for lung functional imaging as 4DCT is taken as routine for lung cancer treatment. Our work aims to evaluate the impact of accounting for spatial heterogeneity in lung function using 4DCT based lung ventilation imaging for proton and IMRT plans. Methods: Six patients with advanced stage lung cancer of various tumor locations were retrospectively evaluated for the study. Proton and IMRT plans were designed following identical planning objective and constrains for each patient. Ventilation images were calculated from patients’ 4DCT using deformable image registration implemented by Velocity AI software based on Jacobian-metrics. Lung was delineated into two function level regions based on ventilation (low and high functional area). High functional region was defined as lung ventilation greater than 30%. Dose distribution and statistics in different lung function area was calculated for patients. Results: Variation in dosimetric statistics of different function lung region was observed between proton and IMRT plans. In all proton plans, high function lung regions receive lower maximum dose (100.2%–108.9%), compared with IMRT plans (106.4%–119.7%). Interestingly, three out of six proton plans gave higher mean dose by up to 2.2% than IMRT to high function lung region. Lower mean dose (lower by up to 14.1%) and maximum dose (lower by up to 9%) were observed in low function lung for proton plans. Conclusion: A systematic approach was developed to generate function lung ventilation imaging and use it to evaluate plans. This method hold great promise in function analysis of lung during planning. We are currently studying more subjects to evaluate this tool.

60 APPLIED LIFE SCIENCES↗

HEIGHT VARIATION OF THE VECTOR MAGNETIC FIELD IN SOLAR SPICULES

Proving the magnetic configuration of solar spicules has hitherto been difficult due to the lack of spatial resolution and image stability during off-limb ground-based observations. We report spectropolarimetric observations of spicules taken in the He i 1083 nm spectral region with the Tenerife Infrared Polarimeter II at the German Vacuum Tower Telescope of the Observatorio del Teide (Tenerife, Canary Islands, Spain). The data provide the variation with geometrical height of the Stokes I, Q, U, and V profiles, whose encoded information allows the determination of the magnetic field vector by means of the HAZEL inversion code. The inferred results show that the average magnetic field strength at the base of solar spicules is about 80 gauss, and then it decreases rapidly with height to about 30 gauss at a height of 3000 km above the visible solar surface. Moreover, the magnetic field vector is close to vertical at the base of the chromosphere and has mid-inclinations (about 50°) above 2 Mm height.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-G-IeP1-07: Inaccuracy of Lesion Blood Flow Quantification Related to the Proton Density Reference Image in Arterial Spin Labeling MRI of Brain Tumors

Purpose: Cerebral blood flow quantification in arterial spin labeling (ASL) MRI requires an estimate of the equilibrium magnetization of blood, which is often obtained by a set of proton density (PD) reference image. Normally, a constant blood-brain partition coefficient is assumed across the brain. However, this assumption may not be valid for brain lesions. This study aimed to evaluate the impact of lesion-related PD variations on ASL quantification in patients with brain tumors. Methods: MR images for posttreatment evaluation of 42 patients with brain tumors were retrospectively analyzed. These images were acquired on a 3T MRI scanner, including T2-weighted FLAIR, 3D pseudo-continuous ASL and post-contrast T1-weighted images. Anatomical images were coregistered with ASL images using the SPM software. Regions of interest (ROIs) of the enhancing and FLAIR lesions were manually drawn on the coregistered images. ROIs of the contralateral normal appearing tissues were also determined, with the consideration of approximating coil sensitivity patterns in lesion ROIs. Relative lesion blood flow (lesion/contralateral tissue) was calculated from both the CBF map (dependent on the PD) and the ΔM map for comparison. Results: The signal intensities in both enhancing and FLAIR lesions were significantly different than contralateral tissues on the PD reference image (p<0.001). The percent signal difference ranged from −15.9 to 19.2%, with a mean of 5.4% for the enhancing lesion, and from −2.8 to 22.9% with a mean of 10.1% for the FLAIR lesion. The high/low lesion-related PD signal resulted in inversely proportional under-/over-estimation of blood flow in both enhancing and FLAIR lesions. Conclusion: Significant signal differences were found between lesions and contralateral tissues in the PD reference image, which introduced errors in blood flow quantification in ASL. The error can be up to 20% in individual patients with an average of 5- 10% for the group of patients with brain tumors.

60 APPLIED LIFE SCIENCES↗

TU-FG-BRB-05: A 3 Dimensional Prompt Gamma Imaging System for Range Verification in Proton Radiotherapy

Purpose: To report on the initial developments of a clinical 3-dimensional (3D) prompt gamma (PG) imaging system for proton radiotherapy range verification. Methods: The new imaging system under development consists of a prototype Compton camera to measure PG emission during proton beam irradiation and software to reconstruct, display, and analyze 3D images of the PG emission. For initial test of the system, PGs were measured with a prototype CC during a 200 cGy dose delivery with clinical proton pencil beams (ranging from 100 MeV – 200 MeV) to a water phantom. Measurements were also carried out with the CC placed 15 cm from the phantom for a full range 150 MeV pencil beam and with its range shifted by 2 mm. Reconstructed images of the PG emission were displayed by the clinical PG imaging software and compared to the dose distributions of the proton beams calculated by a commercial treatment planning system. Results: Measurements made with the new PG imaging system showed that a 3D image could be reconstructed from PGs measured during the delivery of 200 cGy of dose, and that shifts in the Bragg peak range of as little as 2 mm could be detected. Conclusion: Initial tests of a new PG imaging system show its potential to provide 3D imaging and range verification for proton radiotherapy. Based on these results, we have begun work to improve the system with the goal that images can be produced from delivery of as little as 20 cGy so that the system could be used for in-vivo proton beam range verification on a daily basis.

60 APPLIED LIFE SCIENCES↗

SU-E-T-139: Automated Daily EPID Exit Dose Analysis Uncovers Treatment Variations

Purpose: To evaluate a fully automated EPID exit dose system for its ability to detect daily treatment deviations including patient setup, delivery, and anatomy changes. Methods: PerFRACTION (Sun Nuclear Corporation) software is a system that uses integrated EPID images taken during patient treatment and automatically pulled from the Aria database and analyzed based on user-defined comparisons. This was used to monitor 20 plans consisting of a total of 859 fields for 18 patients, for a total of 251 fractions. Nine VMAT, 5 IMRT, and 6 3D plans were monitored. The Gamma analysis was performed for each field within a plan, comparing the first fraction against each of the other fractions in each treatment course. A 2% dose difference, 1 mm distance-to-agreement, and 10% dose threshold was used. These tight tolerances were chosen to achieve a high sensitivity to treatment variations. The field passed if 93% of the pixels had a Gamma of 1 or less. Results: Twenty-nine percent of the fields failed. The average plan passing rate was 92.5%.The average 3D plan passing rate was less than for VMAT or IMRT, 84%, vs. an average of 96.2%. When fields failed, an investigation revealed changes in patient anatomy or setup variations, often also leading to variations of transmission through immobilization devices. Conclusion: PerFRACTION is a fully automated system for determining daily changes in dose transmission through the patient that requires no effort other than for the imager panel to be deployed during treatment. A surprising number of fields failed the analysis and can be attributed to important treatment variations that would otherwise not be appreciated. Further study of inter-fraction treatment variations is possible and warranted. Sun Nuclear Corporation provided a license to the software described.

60 APPLIED LIFE SCIENCES↗

SU-F-J-103: Assessment of Liver Tumor Contrast for Radiation Therapy: Inter-Patient and Inter-Sequence Variability

Purpose: To determine the variation in tumor contrast between different MRI sequences and between patients for the purpose of MRI-based treatment planning. Methods: Multiple MRI scans of 11 patients with cancer(s) in the liver were included in this IRB-approved study. Imaging sequences consisted of T1W MRI, Contrast-Enhanced T1W MRI, T2W MRI, and T2*/T1W MRI. MRI images were acquired on a 1.5T GE Signa scanner with a four-channel torso coil. We calculated the tumor-to-tissue contrast to noise ratio (CNR) for each MR sequence by contouring the tumor and a region of interest (ROI) in a homogeneous region of the liver using the Eclipse treatment planning software. CNR was calculated (I-Tum-I-ROI)/SD-ROI, where I-Tum and I-ROI are the mean values of the tumor and the ROI respectively, and SD-ROI is the standard deviation of the ROI. The same tumor and ROI structures were used in all measurements for different MR sequences. Inter-patient Coefficient of variation (CV), and inter-sequence CV was determined. In addition, mean and standard deviation of CNR were calculated and compared between different MR sequences. Results: Our preliminary results showed large inter-patient CV (range: 37.7% to 88%) and inter-sequence CV (range 5.3% to 104.9%) of liver tumor CNR, indicating great variations in tumor CNR between MR sequences and between patients. Tumor CNR was found to be largest in CE-T1W (8.5±7.5), followed by T2W (4.2±2.4), T1W (3.4±2.2), and T2*/T1W (1.7±0.6) MR scans. The inter-patient CV of tumor CNR was also the largest in CE-T1W (88%), followed by T1W (64.3%), T1W (56.2%), and T2*/T1W (37.7) MR scans. Conclusion: Large inter-sequence and inter-patient variations were observed in liver tumor CNR. CE-T1W MR images on average provided the best tumor CNR. Efforts are needed to optimize tumor contrast and its consistency for MRI-based treatment planning of cancer in the liver. This project is supported by NIH grant: 1R21CA165384.

60 APPLIED LIFE SCIENCES↗

MO-FG-CAMPUS-TeP1-01: An Efficient Method of 3D Patient Dose Reconstruction Based On EPID Measurements for Pre-Treatment Patient Specific QA

Purpose: To demonstrate an efficient and clinically relevant patient specific QA method by reconstructing 3D patient dose from 2D EPID images for IMRT plans. Also to determine the usefulness of 2D QA metrics when assessing 3D patient dose deviations. Methods: Using the method developed by King et al (Med Phys 39(5),2839–2847), EPID images of IMRT fields were acquired in air and converted to dose at 10 cm depth (SAD setup) in a flat virtual water phantom. Each EPID measured dose map was then divided by the corresponding treatment planning system (TPS) dose map calculated with an identical setup, to derive a 2D “error matrix”. For each field, the error matrix was used to adjust the doses along the respective ray lines in the original patient 3D dose. All field doses were combined to derive a reconstructed 3D patient dose for quantitative analysis. A software tool was developed to efficiently implement the entire process and was tested with a variety of IMRT plans for 2D (virtual flat phantom) and 3D (in-patient) QA analysis. Results: The method was tested on 60 IMRT plans. The mean (± standard deviation) 2D gamma (2%,2mm) pass rate (2D-GPR) was 97.4±3.0% and the mean 2D gamma index (2D-GI) was 0.35±0.06. The 3D PTV mean dose deviation was 1.8±0.8%. The analysis showed very weak correlations between both the 2D-GPR and 2D-GI when compared with PTV mean dose deviations (R2=0.3561 and 0.3632 respectively). Conclusion: Our method efficiently calculates 3D patient dose from 2D EPID images, utilising all of the advantages of an EPID-based dosimetry system. In this study, the 2D QA metrics did not predict the 3D patient dose deviation. This tool allows reporting of the 3D volumetric dose parameters thus providing more clinically relevant patient specific QA.

60 APPLIED LIFE SCIENCES↗

Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms

Purpose: The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. Methods: Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settings for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30–49 mm, T3 = 50–69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) VOLPARA volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied. Results: For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection. Conclusions: These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.

60 APPLIED LIFE SCIENCES↗

Supermassive black holes and their host galaxies. II. The correlation with near-infrared luminosity revisited

We present an investigation of the scaling relations between supermassive black hole (SMBH) masses, M {sub •}, and their host galaxies' K-band bulge (L {sub bul}) and total (L {sub tot}) luminosities. The wide-field WIRCam imager at the Canada-France-Hawaii-Telescope was used to obtain the deepest and highest resolution near-infrared images available for a sample of 35 galaxies with securely measured M {sub •}, selected irrespective of Hubble type. For each galaxy, we derive bulge and total magnitudes using a two-dimensional image decomposition code that allows us to account, if necessary, for large- and small-scale disks, cores, bars, nuclei, rings, envelopes, and spiral arms. We find that the present-day M {sub •}-L {sub bul} and M {sub •}-L {sub tot} relations have consistent intrinsic scatter, suggesting that M {sub •} correlates equally well with bulge and total luminosity of the host. Our analysis provides only mild evidence of a decreased scatter if the fit is restricted to elliptical galaxies. The log-slopes of the M {sub •}-L {sub bul} and M {sub •}-L {sub tot} relations are 0.75 ± 0.10 and 0.92 ± 0.14, respectively. However, while the slope of the M {sub •}-L {sub bul} relation depends on the detail of the image decomposition, the characterization of M {sub •}-L {sub tot} does not. Given the difficulties and ambiguities of decomposing galaxy images into separate components, our results indicate that L {sub tot} is more suitable as a tracer of SMBH mass than L {sub bul}, and that the M {sub •}-L {sub tot} relation should be used when studying the co-evolution of SMBHs and galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Automation of PCXMC and ImPACT for NASA Astronaut Medical Imaging Dose and Risk Tracking

To automate astronaut organ and effective dose calculations from occupational X-ray and computed tomography (CT) examinations incorporating PCXMC and ImPACT tools and to estimate the associated lifetime cancer risk per the National Council on Radiation Protection & Measurements (NCRP) using MATLAB(R). Methods: NASA follows guidance from the NCRP on its operational radiation safety program for astronauts. NCRP Report 142 recommends that astronauts be informed of the cancer risks from reported exposures to ionizing radiation from medical imaging. MATLAB(R) code was written to retrieve exam parameters for medical imaging procedures from a NASA database, calculate associated dose and risk, and return results to the database, using the Microsoft .NET Framework. This code interfaces with the PCXMC executable and emulates the ImPACT Excel spreadsheet to calculate organ doses from X-rays and CTs, respectively, eliminating the need to utilize the PCXMC graphical user interface (except for a few special cases) and the ImPACT spreadsheet. Results: Using MATLAB(R) code to interface with PCXMC and replicate ImPACT dose calculation allowed for rapid evaluation of multiple medical imaging exams. The user inputs the exam parameter data into the database and runs the code. Based on the imaging modality and input parameters, the organ doses are calculated. Output files are created for record, and organ doses, effective dose, and cancer risks associated with each exam are written to the database. Annual and post-flight exposure reports, which are used by the flight surgeon to brief the astronaut, are generated from the database. Conclusions: Automating PCXMC and ImPACT for evaluation of NASA astronaut medical imaging radiation procedures allowed for a traceable and rapid method for tracking projected cancer risks associated with over 12,000 exposures. This code will be used to evaluate future medical radiation exposures, and can easily be modified to accommodate changes to the risk calculation procedure.

Bahadori, Amir↗

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗