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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

WE-D-17A-02: Evaluation of a Two-Dimensional Optical Dosimeter On Measuring Lateral Profiles of Proton Pencil Beams

Purpose: To evaluate the accuracy of a two-dimensional optical dosimeter on measuring lateral profiles for spots and scanned fields of proton pencil beams. Methods: A digital camera with a color image senor was utilized to image proton-induced scintillations on Gadolinium-oxysulfide phosphor reflected by a stainless-steel mirror. Intensities of three colors were summed for each pixel with proper spatial-resolution calibration. To benchmark this dosimeter, the field size and penumbra for 100mm square fields of singleenergy pencil-scan protons were measured and compared between this optical dosimeter and an ionization-chamber profiler. Sigma widths of proton spots in air were measured and compared between this dosimeter and a commercial optical dosimeter. Clinical proton beams with ranges between 80 mm and 300 mm at CDH proton center were used for this benchmark. Results: Pixel resolutions vary 1.5% between two perpendicular axes. For a pencil-scan field with 302 mm range, measured field sizes and penumbras between two detection systems agreed to 0.5 mm and 0.3 mm, respectively. Sigma widths agree to 0.3 mm between two optical dosimeters for a proton spot with 158 mm range; having widths of 5.76 mm and 5.92 mm for X and Y axes, respectively. Similar agreements were obtained for others beam ranges. This dosimeter was successfully utilizing on mapping the shapes and sizes of proton spots at the technical acceptance of McLaren proton therapy system. Snow-flake spots seen on images indicated the image sensor having pixels damaged by radiations. Minor variations in intensity between different colors were observed. Conclusions: The accuracy of our dosimeter was in good agreement with other established devices in measuring lateral profiles of pencil-scan fields and proton spots. A precise docking mechanism for camera was designed to keep aligned optical path while replacing damaged image senor. Causes for minor variations between emitted color lights will be investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-G-BRD-01: Diffusion Weighted MRI for Response Assessment of Inoperable Lung Tumors for Patients Undergoing SBRT Treatment

Purpose: To investigate early changes in tumor Apparent Diffusion Coefficients derived from diffusion weighted (DW)-MRI of lung cancer patients undergoing SBRT, as a possible early predictor of treatment response. Methods: DW-MRI scans were performed in this prospective phase I IRB-approved study of inoperable lung tumors at various time-points during the course of SBRT treatments. Axial DW scan using multi b-values ranging from 0–1000 s/mm{sup 2} were acquired in treatment position on a 3T Philips MR scanner during simulation, one hour after the first fraction (8 Gy), after a total of 5 fractions (40 Gy) and 4 weeks after SBRT delivery. A monoexponential model based on a least square fit from all b values was performed on a pixel-by-pixel basis and ADC was calculated. GTVs drawn on 4DCT for planning were mapped on the T2w MRI (acquired at exhale) after deformable registration. These volumes were then mapped on DWI scan for ADC calculation after rigid registration between the anatomical scan and diffusion scan. T2w scan on followup time points were deformably registered to the pretreatment T2 scan. Results: The first two patients in this study were analyzed. Median ADC values were 1.48, 1.48, 1.62 and 1.83 (10{sup −3}×) mm{sup 2}/s at pretreatment, after 8 Gy, after 40 Gy and 4 weeks posttreatment for the first patient and 1.57, 1.53, 1.66 and 1.72 (10{sup −3}×) mm{sup 2}/s for the second patient. ADC increased more significantly after 4 weeks of treatment rather than immediately post treatment, implying that late ADC value may be a better predictor of tumor response for SBRT treatment. The fraction of tumor pixels at high ADC values increased at 4 weeks post treatment. Conclusion: The observed increase in ADC values before the end of radiotherapy may be a surrogate for tumor response, but further patient accrual will be necessary to determine its value.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Automated identification of retinal vessels using a multiscale directional contrast quantification (MDCQ) strategy

Purpose: A novel algorithm is presented to automatically identify the retinal vessels depicted in color fundus photographs. Methods: The proposed algorithm quantifies the contrast of each pixel in retinal images at multiple scales and fuses the resulting consequent contrast images in a progressive manner by leveraging their spatial difference and continuity. The multiscale strategy is to deal with the variety of retinal vessels in width, intensity, resolution, and orientation; and the progressive fusion is to combine consequent images and meanwhile avoid a sudden fusion of image noise and/or artifacts in space. To quantitatively assess the performance of the algorithm, we tested it on three publicly available databases, namely, DRIVE, STARE, and HRF. The agreement between the computer results and the manual delineation in these databases were quantified by computing their overlapping in both area and length (centerline). The measures include sensitivity, specificity, and accuracy. Results: For the DRIVE database, the sensitivities in identifying vessels in area and length were around 90% and 70%, respectively, the accuracy in pixel classification was around 99%, and the precisions in terms of both area and length were around 94%. For the STARE database, the sensitivities in identifying vessels were around 90% in area and 70% in length, and the accuracy in pixel classification was around 97%. For the HRF database, the sensitivities in identifying vessels were around 92% in area and 83% in length for the healthy subgroup, around 92% in area and 75% in length for the glaucomatous subgroup, around 91% in area and 73% in length for the diabetic retinopathy subgroup. For all three subgroups, the accuracy was around 98%. Conclusions: The experimental results demonstrate that the developed algorithm is capable of identifying retinal vessels depicted in color fundus photographs in a relatively reliable manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Evaluation of Matrix9 silicon photomultiplier array for small-animal PET

Purpose: The MatrixSL-9-30035-OEM (Matrix9) from SensL is a large-area silicon photomultiplier (SiPM) photodetector module consisting of a 3 × 3 array of 4 × 4 element SiPM arrays (total of 144 SiPM pixels) and incorporates SensL’s front-end electronics board and coincidence board. Each SiPM pixel measures 3.16 × 3.16 mm{sup 2} and the total size of the detector head is 47.8 × 46.3 mm{sup 2}. Using 8 × 8 polished LSO/LYSO arrays (pitch 1.5 mm) the performance of this detector system (SiPM array and readout electronics) was evaluated with a view for its eventual use in small-animal positron emission tomography (PET). Methods: Measurements of noise, signal, signal-to-noise ratio, energy resolution, flood histogram quality, timing resolution, and array trigger error were obtained at different bias voltages (28.0–32.5 V in 0.5 V intervals) and at different temperatures (5 °C–25 °C in 5 °C degree steps) to find the optimal operating conditions. Results: The best measured signal-to-noise ratio and flood histogram quality for 511 keV gamma photons were obtained at a bias voltage of 30.0 V and a temperature of 5 °C. The energy resolution and timing resolution under these conditions were 14.2% ± 0.1% and 4.2 ± 0.1 ns, respectively. The flood histograms show that all the crystals in the 1.5 mm pitch LSO array can be clearly identified and that smaller crystal pitches can also be resolved. Flood histogram quality was also calculated using different center of gravity based positioning algorithms. Improved and more robust results were achieved using the local 9 pixels for positioning along with an energy offset calibration. To evaluate the front-end detector readout, and multiplexing efficiency, an array trigger error metric is introduced and measured at different lower energy thresholds. Using a lower energy threshold greater than 150 keV effectively eliminates any mispositioning between SiPM arrays. Conclusions: In summary, the Matrix9 detector system can resolve high-resolution scintillator arrays common in small-animal PET with adequate energy resolution and timing resolution over a large detector area. The modular design of the Matrix9 detector allows it to be used as a building block for simple, low channel-count, yet high performance, small animal PET or PET/MRI systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-C-207-02: A Method to Estimate the Average Planar Dose From a C-Arm CBCT Acquisition

Purpose: The planar average dose in a C-arm Cone Beam CT (CBCT) acquisition had been estimated in the past by averaging the four peripheral dose measurements in a CTDI phantom and then using the standard 2/3rds peripheral and 1/3 central CTDIw method (hereafter referred to as Dw). The accuracy of this assumption has not been investigated and the purpose of this work is to test the presumed relationship. Methods: Dose measurements were made in the central plane of two consecutively placed 16cm CTDI phantoms using a 0.6cc ionization chamber at each of the 4 peripheral dose bores and in the central dose bore for a C-arm CBCT protocol. The same setup was scanned with a circular cut-out of radiosensitive gafchromic film positioned between the two phantoms to capture the planar dose distribution. Calibration curves for color pixel value after scanning were generated from film strips irradiated at different known dose levels. The planar average dose for red and green pixel values was calculated by summing the dose values in the irradiated circular film cut out. Dw was calculated using the ionization chamber measurements and film dose values at the location of each of the dose bores. Results: The planar average dose using both the red and green pixel color calibration curves were within 10% agreement of the planar average dose estimated using the Dw method of film dose values at the bore locations. Additionally, an average of the planar average doses calculated using the red and green calibration curves differed from the ionization chamber Dw estimate by only 5%. Conclusion: The method of calculating the planar average dose at the central plane of a C-arm CBCT non-360 rotation by calculating Dw from peripheral and central dose bore measurements is a reasonable approach to estimating the planar average dose. Research Grant, Siemens AG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT

Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantify image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-45: Feasibility for Using Iodine Quantification to Assist Diagnosis in Dual Energy Contrast-Enhanced Digital Mammography

Purpose: The objective of this study is to develop quantitative calibration between image quality indexes and iodine concentration with dual-energy (DE) contrast-enhanced digital mammography (CEDM) techniques and further serve as the assistance for diagnosis. Methods: Custom-made acrylic phantom with dimensions of 24×30 cm{sup 2} simulated breast thickness from 2 to 6 cm was used in the calibration. The phantom contained matrix of four times four holes of 3 mm deep with a diameter of 15 mm for filling contrast agent with area density ranged from 0.1 to 10 mg/cm{sup 2}. All the image acquisitions were performed on a full-field digital mammography system (Senographe Essential, GE) with dual energy acquisitions. Mean pixel value (MPV), and contrast-to-noise ratio (CNR) were used for evaluating the relationship between image quality indexes and iodine concentration. Iodine map and CNR map could further be constructed with these calibration curves applied pixel by pixel utilized MATLAB software. Minimum iodine concentration could also be calculated with the visibility threshold of CNR=5 according the Rose model. Results: When evaluating the DE subtraction images, MPV increased linearly as the iodine concentration increased with all the phantom thickness surveyed (R{sup 2} between 0.989 and 0.992). Lesions with increased iodine uptake could thus be enhanced in the color-encoded iodine maps, and the mean iodine concentration could be obtained through the ROI measurements. As for investigating CNR performance, linear relationships were also shown between the iodine concentration and CNR (R{sup 2} between 0.983 and 0.990). Minimum iodine area density of 1.45, 1.73, 1.80, 1.73 and 1.72 mg/cm{sup 2} for phantom thickness of 2, 3, 4, 5, 6 cm were calculated based on Rose’s visualization criteria. Conclusion: Quantitative calibration between image quality indexes and iodine concentrations may further serving as the assistance for analyzing contrast enhancement for patient participating the dual energy CEDM procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-49: Simulation Study for Removing Scatter Radiation in Cesium-Iodine Based Flat Panel Detector System

Purpose: This study aims to identify the feasibility of a novel cesium-iodine (CsI)-based flat-panel detector (FPD) for removing scatter radiation in diagnostic radiology. Methods: The indirect FPD comprises three layers: a substrate, scintillation, and thin-film-transistor (TFT) layer. The TFT layer has a matrix structure with pixels. There are ineffective dimensions on the TFT layer, such as the voltage and data lines; therefore, we devised a new FPD system having net-like lead in the substrate layer, matching the ineffective area, to block the scatter radiation so that only primary X-rays could reach the effective dimension.To evaluate the performance of this new FPD system, we conducted a Monte Carlo simulation using MCNPX 2.6.0 software. Scatter fractions (SFs) were acquired using no grid, a parallel grid (8:1 grid ratio), and the new system, and the performances were compared.Two systems having different thicknesses of lead in the substrate layer—10 and 20μm—were simulated. Additionally, we examined the effects of different pixel sizes (153×153 and 163×163μm) on the image quality, while keeping the effective area of pixels constant (143×143μm). Results: In case of 10μm lead, the SFs of the new system (∼11%) were lower than those of the other system (∼27% with no grid, ∼16% with parallel grid) at 40kV. However, as the tube voltage increased, the SF of new system (∼19%) was higher than that of parallel grid (∼18%) at 120kV. In the case of 20μm lead, the SFs of the new system were lower than those of the other systems at all ranges of the tube voltage (40–120kV). Conclusion: The novel CsI-based FPD system for removing scatter radiation is feasible for improving the image contrast but must be optimized with respect to the lead thickness, considering the system’s purposes and the ranges of the tube voltage in diagnostic radiology. This study was supported by a grant(K1422651) from Institute of Health Science, Korea University.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-J-114: A Practical Hybrid Method for Improving the Quality of CT-CBCT Deformable Image Registration for Head and Neck Radiotherapy

Purpose: Accurate deformable image registration (DIR) between CT and CBCT in H&N is challenging. In this study, we propose a practical hybrid method that uses not only the pixel intensities but also organ physical properties, structure volume of interest (VOI), and interactive local registrations. Methods: Five oropharyngeal cancer patients were selected retrospectively. For each patient, the planning CT was registered to the last fraction CBCT, where the anatomy difference was largest. A three step registration strategy was tested; Step1) DIR using pixel intensity only, Step2) DIR with additional use of structure VOI and rigidity penalty, and Step3) interactive local correction. For Step1, a public-domain open-source DIR algorithm was used (cubic B-spline, mutual information, steepest gradient optimization, and 4-level multi-resolution). For Step2, rigidity penalty was applied on bony anatomies and brain, and a structure VOI was used to handle the body truncation such as the shoulder cut-off on CBCT. Finally, in Step3, the registrations were reviewed on our in-house developed software and the erroneous areas were corrected via a local registration using level-set motion algorithm. Results: After Step1, there were considerable amount of registration errors in soft tissues and unrealistic stretching in the posterior to the neck and near the shoulder due to body truncation. The brain was also found deformed to a measurable extent near the superior border of CBCT. Such errors could be effectively removed by using a structure VOI and rigidity penalty. The rest of the local soft tissue error could be corrected using the interactive software tool. The estimated interactive correction time was approximately 5 minutes. Conclusion: The DIR using only the image pixel intensity was vulnerable to noise and body truncation. A corrective action was inevitable to achieve good quality of registrations. We found the proposed three-step hybrid method efficient and practical for CT/CBCT registrations in H&N. My department receives grant support from Industrial partners: (a) Varian Medical Systems, Palo Alto, CA, and (b) Philips HealthCare, Best, Netherlands.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-775: Use of Electronic Portal Imaging Device (EPID) for Quality Assurance (QA) of Electron Beams On Varian Truebeam System

Purpose: In a previous study we have demonstrated the feasibility of using EPID to QA electron beam parameters on a single Varian TrueBeam LINAC. This study aims to provide further investigation on (1) reproducibility of using EPID to detect electron beam energy changes on multiple machines and (2) evaluation of appropriate calibration methods to compare results from different EPIDs. Methods: Ad-hoc mode electron beam images were acquired in developer mode with XML code. Electron beam data were collected on a total of six machines from four institutions. A custom-designed double-wedge phantom was placed on the EPID detector. Two calibration methods - Pixel Sensitivity Map (PSM) and Large Source-to-Imager Distance Flood Field (LSID-FF) - were used. To test the sensitivity of EPID in detecting energy drifts, Bending Magnet Current (BMC) was detuned to invoke energy changes corresponding to ∼±1.5 mm change in R50% of PDD on two machines from two institutions. Percent depth ionization (PDI) curves were then analyzed and compared with the respective baseline images using LSID-FF calibration. For reproducibility testing, open field EPID images and images with a standard testing phantom were collected on multiple machines. Images with and without PSM correction for same energies on different machines were overlaid and compared. Results: Two pixel shifts were observed in PDI curve when energy changes exceeded the TG142 tolerance. PSM showed the potential to correct the differences in pixel response of different imagers. With PSM correction, the histogram of images differences obtained from different machines showed narrower distributions than those images without PSM correction. Conclusion: EPID is sensitive for electron energy changes and the results are reproducible on different machines. When overlaying images from different machines, PSM showed the ability to partially eliminate the intrinsic variation of various imagers. Research Funding from Varian Medical Systems Inc.Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-EF-204-11: Impact of Using Multi-Slice Training Sets On the Performance of a Channelized Hotelling Observer in a Low-Contrast Detection Task in CT

Purpose: To investigate using multiple CT image slices from a single acquisition as independent training images for a channelized Hotelling observer (CHO) model to reduce the number of repeated scans for CHO-based CT image quality assessment. Methods: We applied a previously validated CHO model to detect low contrast disk objects formed from cross-sectional images of three epoxy-resin-based rods (diameters: 3, 5, and 9 mm; length: ∼5cm). The rods were submerged in a 35x 25 cm2 iodine-doped water filled phantom, yielding-15 HU object contrast. The phantom was scanned 100 times with and without the rods present. Scan and reconstruction parameters include: 5 mm slice thickness at 0.5 mm intervals, 120 kV, 480 Quality Reference mAs, and a 128-slice scanner. The CHO’s detectability index was evaluated as a function of factors related to incorporating multi-slice image data: object misalignment along the z-axis, inter-slice pixel correlation, and number of unique slice locations. In each case, the CHO training set was fixed to 100 images. Results: Artificially shifting the object’s center position by as much as 3 pixels in any direction relative to the Gabor channel filters had insignificant impact on object detectability. An inter-slice pixel correlation of >∼0.2 yielded positive bias in the model’s performance. Incorporating multi-slice image data yielded slight negative bias in detectability with increasing number of slices, likely due to physical variations in the objects. However, inclusion of image data from up to 5 slice locations yielded detectability indices within measurement error of the single slice value. Conclusion: For the investigated model and task, incorporating image data from 5 different slice locations of at least 5 mm intervals into the CHO model yielded detectability indices within measurement error of the single slice value. Consequently, this methodology would Result in a 5-fold reduction in number of image acquisitions. This project was supported by National Institutes of Health grants R01 EB017095 and U01 EB017185 from the National Institute of Biomedical Imaging and Bioengineering.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-204-07: Automated Characterization of Perceptual Quality of Clinical Chest Radiographs: Improvements in Lung, Spine, and Hardware Detection

Purpose: To develop and validate more robust methods for automated lung, spine, and hardware detection in AP/PA chest images. This work is part of a continuing effort to automatically characterize the perceptual image quality of clinical radiographs. [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] Methods: Our previous implementation of lung/spine identification was applicable to only one vendor. A more generalized routine was devised based on three primary components: lung boundary detection, fuzzy c-means (FCM) clustering, and a clinically-derived lung pixel probability map. Boundary detection was used to constrain the lung segmentations. FCM clustering produced grayscale- and neighborhood-based pixel classification probabilities which are weighted by the clinically-derived probability maps to generate a final lung segmentation. Lung centerlines were set along the left-right lung midpoints. Spine centerlines were estimated as a weighted average of body contour, lateral lung contour, and intensity-based centerline estimates. Centerline estimation was tested on 900 clinical AP/PA chest radiographs which included inpatient/outpatient, upright/bedside, men/women, and adult/pediatric images from multiple imaging systems. Our previous implementation further did not account for the presence of medical hardware (pacemakers, wires, implants, staples, stents, etc.) potentially biasing image quality analysis. A hardware detection algorithm was developed using a gradient-based thresholding method. The training and testing paradigm used a set of 48 images from which 1920 51×51 pixel{sup 2} ROIs with and 1920 ROIs without hardware were manually selected. Results: Acceptable lung centerlines were generated in 98.7% of radiographs while spine centerlines were acceptable in 99.1% of radiographs. Following threshold optimization, the hardware detection software yielded average true positive and true negative rates of 92.7% and 96.9%, respectively. Conclusion: Updated segmentation and centerline estimation methods in addition to new gradient-based hardware detection software provide improved data integrity control and error-checking for automated clinical chest image quality characterization across multiple radiography systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A novel approach to assess the treatment response using Gaussian random field in PET

Purpose: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. Methods: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128{sup 2} pixels) with lesions of various diameters (2–6 mm), multiple tumor-to-background contrasts (3–10), and different changes in intensity (6.25%–30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient. Results: It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient. Conclusions: In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

IMRT QA: Selecting gamma criteria based on error detection sensitivity

Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose threshold was consistent across all studied combinations of %Diff/DTA. Criteria such as 2%/3 mm and 3%/2 mm with a 50% threshold at 90% pixels passing are shown to be more appropriately sensitive without being overly strict. However, a broadening of the penumbra by as much as 5 mm in the beam configuration was difficult to detect with commonly used criteria, as well as with the previously mentioned criteria utilizing a threshold of 50%. Conclusions: We have introduced the error curve method, an analysis technique which allows the quantitative determination of gamma criteria sensitivity to induced errors. The application of the error curve method using DMLC IMRT plans measured on the ArcCHECK® device demonstrated that large errors can potentially be missed in IMRT QA with commonly used gamma criteria (e.g., 3%/3 mm, threshold = 10%, 90% pixels passing). Additionally, increasing the dose threshold value can offer dramatic increases in error sensitivity. This approach may allow the selection of more meaningful gamma criteria for IMRT QA and is straightforward to apply to other combinations of devices and treatment techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

An efficient computational approach to model statistical correlations in photon counting x-ray detectors

Purpose: To introduce and evaluate an increment matrix approach (IMA) describing the signal statistics of energy-selective photon counting detectors including spatial–spectral correlations between energy bins of neighboring detector pixels. The importance of the occurring correlations for image-based material decomposition is studied. Methods: An IMA describing the counter increase patterns in a photon counting detector is proposed. This IMA has the potential to decrease the number of required random numbers compared to Monte Carlo simulations by pursuing an approach based on convolutions. To validate and demonstrate the IMA, an approximate semirealistic detector model is provided, simulating a photon counting detector in a simplified manner, e.g., by neglecting count rate-dependent effects. In this way, the spatial–spectral correlations on the detector level are obtained and fed into the IMA. The importance of these correlations in reconstructed energy bin images and the corresponding detector performance in image-based material decomposition is evaluated using a statistically optimal decomposition algorithm. Results: The results of IMA together with the semirealistic detector model were compared to other models and measurements using the spectral response and the energy bin sensitivity, finding a good agreement. Correlations between the different reconstructed energy bin images could be observed, and turned out to be of weak nature. These correlations were found to be not relevant in image-based material decomposition. An even simpler simulation procedure based on the energy bin sensitivity was tested instead and yielded similar results for the image-based material decomposition task, as long as the fact that one incident photon can increase multiple counters across neighboring detector pixels is taken into account. Conclusions: The IMA is computationally efficient as it required about 10{sup 2} random numbers per ray incident on a detector pixel instead of an estimated 10{sup 8} random numbers per ray as Monte Carlo approaches would need. The spatial–spectral correlations as described by IMA are not important for the studied image-based material decomposition task. Respecting the absolute photon counts and thus the multiple counter increases by a single x-ray photon, the same material decomposition performance could be obtained with a simpler detector description using the energy bin sensitivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT protocol parameters with an average DSC of 0.86 ± 0.04 (range: 0.80–0.99).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-BRA-07: Applications of Combined KV/MV CBCT Imaging with a High-DQE MV Detector

Purpose: To investigate whether a high detection quantum efficiency (DQE) MV detector makes combined kV/MV CBCT clinically practical. Methods: Combined kV/MV CBCT was studied for scan time reduction (STR) and metal artifact reduction (MAR). 6MV CBCT data (dose rate = 0.017 MU/degree) were collected using 1) a novel focused pixelated cadmium tungstate (CWO) scintillator (15mm thickness, DQE(0) = 22%, 0.784mm pixel pitch) coupled to a flat panel imager, and 2) a commercial portal imager with a 133mg/cm{sup 2} gadolinium oxysulfide (GOS) screen (DQE(0) = 1.2%). The 100kVp data were acquired using a commercial imager employing a columnar cesium iodide scintillator (DQE(0) = 70%) with a dose rate of 0.0016 cGy/degree. For STR, MV and kV projections spanning 105° were combined to constitute a complete CBCT scan. Total dose was ∼2cGy and acquisition time was 18s. For MAR, only the metalcorrupted pixels in the kV projections were replaced with MV data resulting in a total dose of less than 1cGy for a 360° scan. Image quality was assessed using an 18-cm diameter electron density phantom with nine tissue inserts, some of which were replaced with steel rods for MAR studies. Results: The CWO contrast-to-noise ratio (CNR) was ∼4.0x higher than the GOS CNR and was ∼4.8x lower than the kV CNR when normalized for dose. When CWO MV data were combined with kV data for STR, all contrast inserts were visible, but only two were detectable in the composite kV/GOS image. Metal artifacts were greatly reduced using the kV/MV MAR technique with all contrast inserts clearly visible in the composite kV/CWO image but only two inserts visible in the composite kV/GOS image. Conclusion: We have demonstrated that a high DQE MV detector significantly improves kV/MV CBCT image quality thus enabling scan time reduction and metal artifact reduction without a severe dose penalty. AW and JS-L are employees of Varian, RF is an employee of Siemens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-SPS-06: Implementation of a Back-Projection Algorithm for 2D in Vivo Dosimetry with An EPID System

Purpose: To implement a back-projection algorithm for 2D dose reconstructions for in vivo dosimetry in radiation therapy using an Electronic Portal Imaging Device (EPID) based on amorphous silicon. Methods: An EPID system was used to calculate dose-response function, pixel sensitivity map, exponential scatter kernels and beam hardenig correction for the back-projection algorithm. All measurements were done with a 6 MV beam. A 2D dose reconstruction for an irradiated water phantom (30×30×30 cm{sup 3}) was done to verify the algorithm implementation. Gamma index evaluation between the 2D reconstructed dose and the calculated with a treatment planning system (TPS) was done. Results: A linear fit was found for the dose-response function. The pixel sensitivity map has a radial symmetry and was calculated with a profile of the pixel sensitivity variation. The parameters for the scatter kernels were determined only for a 6 MV beam. The primary dose was estimated applying the scatter kernel within EPID and scatter kernel within the patient. The beam hardening coefficient is σBH= 3.788×10{sup −4} cm{sup 2} and the effective linear attenuation coefficient is µAC= 0.06084 cm{sup −1}. The 95% of points evaluated had γ values not longer than the unity, with gamma criteria of ΔD = 3% and Δd = 3 mm, and within the 50% isodose surface. Conclusion: The use of EPID systems proved to be a fast tool for in vivo dosimetry, but the implementation is more complex that the elaborated for pre-treatment dose verification, therefore, a simplest method must be investigated. The accuracy of this method should be improved modifying the algorithm in order to compare lower isodose curves.

60 APPLIED LIFE SCIENCES↗