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DOE OSTI2014

SU-E-J-74: Impact of Respiration-Correlated Image Quality On Tumor Motion Reconstruction in 4D-CBCT: A Phantom Study

Purpose: To investigate the effects of scanning parameters and respiratory patterns on the image quality for 4-dimensional cone-beam computed tomography(4D-CBCT) imaging, and assess the accuracy of computed tumor trajectory for lung imaging using registration of phased 4D-CBCT imaging with treatment planning-CT. Methods: We simulated a periodic and non-sinusoidal respirations with various breathing periods and amplitudes using a respiratory phantom(Quasar, Modus Medical Devices Inc) to acquire respiration-correlated 4D-CBCT images. 4D-CBCT scans(Elekta Oncology Systems Ltd) were performed with different scanning parameters for collimation size(e.g., small and medium field-of-views) and scanning speed(e.g., slow 50°·min{sup −1}, fast 100°·min{sup −1}). Using a standard CBCT-QA phantom(Catphan500, The Phantom Laboratory), the image qualities of all phases in 4D-CBCT were evaluated with contrast-to-noise ratio(CNR) for lung tissue and uniformity in each module. Using a respiratory phantom, the target imaging in 4D-CBCT was compared to 3D-CBCT target image. The target trajectory from 10-respiratory phases in 4D-CBCT was extracted using an automatic image registration and subsequently assessed the accuracy by comparing with actual motion of the target. Results: Image analysis indicated that a short respiration with a small amplitude resulted in superior CNR and uniformity. Smaller variation of CNR and uniformity was present amongst different respiratory phases. The small field-of-view with a partial scan using slow scan can improve CNR, but degraded uniformity. Large amplitude of respiration can degrade image quality. RMS of voxel densities in tumor area of 4D-CBCT images between sinusoidal and non-sinusoidal motion exhibited no significant difference. The maximum displacement errors of motion trajectories were less than 1.0 mm and 13.5 mm, for sinusoidal and non-sinusoidal breathings, respectively. The accuracy of motion reconstruction showed good overall agreement with the 4D-CBCT image quality results only using sinusoidal breathings. Conclusion: This information can be used to determine the appropriate acquisition parameters of 4D-CBCT imaging for registration accuracy and target trajectory measurements in a clinical setting.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Real-time out-of-plane artifact subtraction tomosynthesis imaging using prior CT for scanning beam digital x-ray system

Purpose: The scanning beam digital x-ray system (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real-time tomosynthesis in multiple planes. This system could be used for image guidance during lung nodule biopsy. However, the reconstructed images suffer from strong out-of-plane artifact due to the small tomographic angle of the system. Methods: The authors propose an out-of-plane artifact subtraction tomosynthesis (OPAST) algorithm that utilizes a prior CT volume to augment the run-time image processing. A blur-and-add (BAA) analytical model, derived from the project-to-backproject physical model, permits the generation of tomosynthesis images that are a good approximation to the shift-and-add (SAA) reconstructed image. A computationally practical algorithm is proposed to simulate images and out-of-plane artifacts from patient-specific prior CT volumes using the BAA model. A 3D image registration algorithm to align the simulated and reconstructed images is described. The accuracy of the BAA analytical model and the OPAST algorithm was evaluated using three lung cancer patients’ CT data. The OPAST and image registration algorithms were also tested with added nonrigid respiratory motions. Results: Image similarity measurements, including the correlation coefficient, mean squared error, and structural similarity index, indicated that the BAA model is very accurate in simulating the SAA images from the prior CT for the SBDX system. The shift-variant effect of the BAA model can be ignored when the shifts between SBDX images and CT volumes are within ±10 mm in the x and y directions. The nodule visibility and depth resolution are improved by subtracting simulated artifacts from the reconstructions. The image registration and OPAST are robust in the presence of added respiratory motions. The dominant artifacts in the subtraction images are caused by the mismatches between the real object and the prior CT volume. Conclusions: Their proposed prior CT-augmented OPAST reconstruction algorithm improves lung nodule visibility and depth resolution for the SBDX system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction

Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the proposed scanning method and image reconstruction algorithm can effectively estimate the scatter in cone-beam projections and produce tomographic images of nearly scatter-free quality. The authors believe that the proposed method would provide a fast and efficient CBCT scanning option to various applications particularly including head-and-neck scan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Metal Artifact Reduction for Orthopedic Prosthesis in Lower Extremity CT Venography: Evaluation of Image Quality and Vessel Conspicuity

Purpose: This study evaluates the image quality of lower extremity CT venography reconstructed with orthopedic metal artifact reduction (O-MAR) in patients with unilateral or bilateral metallic prostheses in the hip or knee. Methods: This retrospective study was approved by our institutional review board, and informed consent was waived. Twenty-nine patients of lower extremity CT with 51 metallic hip or knee prostheses were reconstructed to both standard CT images and O-MAR images. The subjective image quality and vessel conspicuity for both images were evaluated by two readers using five-point scales (0–4). Vessel conspicuity scores of 3 or 4 were considered diagnostically acceptable. Image noise was measured in the air and subcutaneous fat. Results: O-MAR images showed significantly higher scores of subjective image quality (p < .001) and vessel conspicuity (p = .002) than standard CT images. Diagnostic acceptance of vessel conspicuity was not significantly different between O-MAR images and standard CT images (p = 1.000). O-MAR images showed significantly less image noise than conventional CT images (p < .001 for both air and subcutaneous fat). Conclusion: O-MAR may be an effective solution for the metal artifacts in lower extremity CT venography; however, the distance between prostheses and vessels affects the diagnostic acceptance in patients with metallic hip or knee prostheses. Level of Evidence: Level 4, Case Series.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A concept to collect neutron and x-ray images on the same line of sight at NIF

Neutron and x-ray images are collected at the National Ignition Facility (NIF) to measure the size and shape of inertial confinement fusion implosions. The x-ray images provide a measure of the size and shape of the hot region of the deuterium-tritium fuel while the neutron images provide a measure of the size and shape of the burning plasma. Although these two types of images are collected simultaneously, they are not collected along the same line of sight (LOS). One 14 MeV neutron image is collected on the NIF equator, and two x-ray images are collected along the polar axis and nearly perpendicular to the neutron imaging line of sight on the equator. Both measurements use pinhole apertures to form the images, but existing x-ray imaging provides time-resolved measurements while the neutron images are time-integrated. Detailed comparisons of the x-ray and neutron images can provide information on the fuel assembly, but these studies have been limited because the implosions are not azimuthally symmetric and the images are collected along different LOS. We have developed a conceptual design of a time-integrated x-ray imaging system that could be added to the existing neutron imaging LOS. This new system would allow these detailed studies, providing important information on the fuel assembly of future implosions. Here we present this conceptual design and the expected performance characteristics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography

Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-94: Automated Image Quality Assessment of Radiographic Systems Using An Anthropomorphic Phantom

Purpose: In a large, academic medical center, consistent radiographic imaging performance is difficult to routinely monitor and maintain, especially for a fleet consisting of multiple vendors, models, software versions, and numerous imaging protocols. Thus, an automated image quality control methodology has been implemented using routine image quality assessment with a physical, stylized anthropomorphic chest phantom. Methods: The “Duke” Phantom (Digital Phantom 07-646, Supertech, Elkhart, IN) was imaged twice on each of 13 radiographic units from a variety of vendors at 13 primary care clinics. The first acquisition used the clinical PA chest protocol to acquire the post-processed “FOR PRESENTATION” image. The second image was acquired without an antiscatter grid followed by collection of the “FOR PROCESSING” image. Manual CNR measurements were made from the largest and thickest contrast-detail inserts in the lung, heart, and abdominal regions of the phantom in each image. An automated image registration algorithm was used to estimate the CNR of the same insert using similar ROIs. Automated measurements were then compared to the manual measurements. Results: Automatic and manual CNR measurements obtained from “FOR PRESENTATION” images had average percent differences of 0.42%±5.18%, −3.44%±4.85%, and 1.04%±3.15% in the lung, heart, and abdominal regions, respectively; measurements obtained from “FOR PROCESSING” images had average percent differences of -0.63%±6.66%, −0.97%±3.92%, and −0.53%±4.18%, respectively. The maximum absolute difference in CNR was 15.78%, 10.89%, and 8.73% in the respective regions. In addition to CNR assessment of the largest and thickest contrast-detail inserts, the automated method also provided CNR estimates for all 75 contrast-detail inserts in each phantom image. Conclusion: Automated analysis of a radiographic phantom has been shown to be a fast, robust, and objective means for assessing radiographic image quality. The method reduces the burden of manual measurements and provides a means by which to monitor and compare radiographic system performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-99: Reconstruction of Cone Beam CT Image Using Volumetric Modulated Arc Therapy Exit Beams

Purpose: To test the possibility of obtaining an image of the treated volume during volumetric modulated arc therapy (VMAT) with exit beams. Method: Using a Varian Clinac 21EX and MVCT detector the following three sets of detector projection data were obtained for cone beam CT reconstruction with and without a Catphan 504 phantom. 1) 72 projection images from 20 × 16 cm{sup 2} open beam with 3 MUs, 2) 72 projection images from 20 × 16 cm{sup 2} MLC closed beam with 14 MUs. 3) 137 projection images from a test RapicArc QA plan. All projection images were obtained in ‘integrated image’ mode. We used OSCaR code to reconstruct the cone beam CT images. No attempts were made to reduce scatter or artifacts. Results: With projection set 1) we obtained a good quality MV CBCT image by optimizing the reconstruction parameters. Using projection set 2) we were not able to obtain a CBCT image of the phantom, which was determined to be due to the variation of interleaf leakage with gantry angle. From projection set 3), we were able to obtain a weak but meaningful signal in the image, especially in the target area where open beam signals were dominant. This finding suggests that one might be able to acquire CBCT images with rough body shape and some details inside the irradiated target area. Conclusion: Obtaining patient images using the VMAT exit beam is challenging but possible. We were able to determine sources of image degradation such as gantry angle dependent interleaf leakage and beams with a large scatter component. We are actively working on improving image quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-G-18A-07: Clinical Evaluation of Normalized Metal Artifact Reduction in KVCT Using MVCT Prior Images (MVCT-NMAR) Technique in Radiotherapy

Purpose: To evaluate the metal artifacts in diagnostic kVCT images of patients that are corrected using a normalized metal artifact reduction method with MVCT prior images, MVCT-NMAR. Methods: An MVCTNMAR algorithm was developed and applied to five patients: three with bilateral hip prostheses, one with unilateral hip prosthesis and one with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces, and for radiotherapy dose calculations. They were also compared against the corresponding images corrected by a commercial metal artifact reduction technique, O-MAR, on a Phillips™ CT scanner. Results: The use of MVCT images for correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiotherapy. These improvements are significant over the commercial correction method, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in O-MAR corrected images are removed in the MVCT-NMAR corrected images. Large dose reduction is possible outside the planning target volume (e.g., 59.2 Gy in comparison to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images are used in TomoTherapy™ treatment plans, as the corrected images no longer require directional blocks for prostate plans in order to avoid the image artifact regions. Conclusion: The use of MVCT-NMAR corrected images in radiotherapy treatment planning could improve the treatment plan quality for cancer patients with metallic implants. Moti Raj Paudel is supported by the Vanier Canada Graduate Scholarship, the Endowed Graduate Scholarship in Oncology and the Dissertation Fellowship at the University of Alberta. The authors acknowledge the CIHR operating grant number MOP 53254.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Dual energy CT: How well can pseudo-monochromatic imaging reduce metal artifacts?

Purpose: Dual Energy CT (DECT) provides so-called monoenergetic images based on a linear combination of the original polychromatic images. At certain patient-specific energy levels, corresponding to certain patient- and slice-dependent linear combination weights, e.g., E = 160 keV corresponds to α = 1.57, a significant reduction of metal artifacts may be observed. The authors aimed at analyzing the method for its artifact reduction capabilities to identify its limitations. The results are compared with raw data-based processing. Methods: Clinical DECT uses a simplified version of monochromatic imaging by linearly combining the low and the high kV images and by assigning an energy to that linear combination. Those pseudo-monochromatic images can be used by radiologists to obtain images with reduced metal artifacts. The authors analyzed the underlying physics and carried out a series expansion of the polychromatic attenuation equations. The resulting nonlinear terms are responsible for the artifacts, but they are not linearly related between the low and the high kV scan: A linear combination of both images cannot eliminate the nonlinearities, it can only reduce their impact. Scattered radiation yields additional noncanceling nonlinearities. This method is compared to raw data-based artifact correction methods. To quantify the artifact reduction potential of pseudo-monochromatic images, they simulated the FORBILD abdomen phantom with metal implants, and they assessed patient data sets of a clinical dual source CT system (100, 140 kV Sn) containing artifacts induced by a highly concentrated contrast agent bolus and by metal. In each case, they manually selected an optimal α and compared it to a raw data-based material decomposition in case of simulation, to raw data-based material decomposition of inconsistent rays in case of the patient data set containing contrast agent, and to the frequency split normalized metal artifact reduction in case of the metal implant. For each case, the contrast-to-noise ratio (CNR) was assessed. Results: In the simulation, the pseudo-monochromatic images yielded acceptable artifact reduction results. However, the CNR in the artifact-reduced images was more than 60% lower than in the original polychromatic images. In contrast, the raw data-based material decomposition did not significantly reduce the CNR in the virtual monochromatic images. Regarding the patient data with beam hardening artifacts and with metal artifacts from small implants the pseudo-monochromatic method was able to reduce the artifacts, again with the downside of a significant CNR reduction. More intense metal artifacts, e.g., as those caused by an artificial hip joint, could not be suppressed. Conclusions: Pseudo-monochromatic imaging is able to reduce beam hardening, scatter, and metal artifacts in some cases but it cannot remove them. In all cases, the CNR is significantly reduced, thereby rendering the method questionable, unless special post processing algorithms are implemented to restore the high CNR from the original images (e.g., by using a frequency split technique). Raw data-based dual energy decomposition methods should be preferred, in particular, because the CNR penalty is almost negligible.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Clinical introduction of image lag correction for a cone beam CT system

Purpose: Image lag in the flat-panel detector used for Linac integrated cone beam computed tomography (CBCT) has a degrading effect on CBCT image quality. The most prominent visible artifact is the presence of bright semicircular structure in the transverse view of the scans, known also as radar artifact. Several correction strategies have been proposed, but until now the clinical introduction of such corrections remains unreported. In November 2013, the authors have clinically implemented a previously proposed image lag correction on all of their machines at their main site in Amsterdam. The purpose of this study was to retrospectively evaluate the effect of the correction on the quality of CBCT images and evaluate the required calibration frequency. Methods: Image lag was measured in five clinical CBCT systems (Elekta Synergy 4.6) using an in-house developed beam interrupting device that stops the x-ray beam midway through the data acquisition of an unattenuated beam for calibration. A triple exponential falling edge response was fitted to the measured data and used to correct image lag from projection images with an infinite response. This filter, including an extrapolation for saturated pixels, was incorporated in the authors’ in-house developed clinical CBCT reconstruction software. To investigate the short-term stability of the lag and associated parameters, a series of five image lag measurement over a period of three months was performed. For quantitative analysis, the authors have retrospectively selected ten patients treated in the pelvic region. The apparent contrast was quantified in polar coordinates for scans reconstructed using the parameters obtained from different dates with and without saturation handling. Results: Visually, the radar artifact was minimal in scans reconstructed using image lag correction especially when saturation handling was used. In patient imaging, there was a significant reduction of the apparent contrast from 43 ± 16.7 to 15.5 ± 11.9 HU without the saturation handling and to 9.6 ± 12.1 HU with the saturation handling, depending on the date of the calibration. The image lag correction parameters were stable over a period of 3 months. The computational load was increased by approximately 10%, not endangering the fast in-line reconstruction. Conclusions: The lag correction was successfully implemented clinically and removed most image lag artifacts thus improving the image quality. Image lag correction parameters were stable for 3 months indicating low frequency of calibration requirements.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-C-202-07: Protocol and Hardware for Improved Flood Field Calibration of TrueBeam FFF Cine Imaging

Purpose: Flattening filter free photon energies are commonly used for high dose treatments such as SBRT, where localization accuracy is essential. Often, MV cine imaging may be employed to verify correct localization. TrueBeam Electronic Portal Imaging Devices (EPIDs) equipped with the 40×30cm{sup 2} Image Detection Unit (IDU) are prone to image saturation at the image center especially for higher dose rates. While saturation often does not occur for cine imaging during treatment because the beam is attenuated by the patient, the flood field calibration is affected when the standard calibration procedure is followed. Here we describe the hardware and protocol to achieve improved image quality for this model of TrueBeam EPID. Methods: A stainless steel filter of uniform thickness was designed to have sufficient attenuation to avoid panel saturation for both 6XFFF and 10XFFF at the maximum dose rates (1400 MU/min & 2400 MU/min, respectively). The cine imaging flood field calibration was then acquired with the filter in place for the FFF energies under the standard calibration geometry (SDD=150cm). Image quality during MV cine was assessed with & without the modified flood field calibration using a low contrast resolution phantom and an anthropomorphic phantom. Results: When the flood field is acquired using the standard procedure (no filter in place), a pixel gain artifact is clearly present in the image center (r=3cm for 10XFFF at 2400 MU/min) which appears similar to and may be mis-attributed to panel saturation in the subject image. The artifact obscured all low contrast inserts at the image center and was also visible on the anthropomorphic phantom. Using the filter for flood field calibration eliminated the artifact. Conclusion: Use of a modified flood field calibration procedure improves image quality for cine MV imaging with TrueBeams equipped with the 40×30cm{sup 2} IDU.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-207B-07: Deep Convolutional Neural Network Image Matching for Ultrasound Guidance in Radiotherapy

Purpose: Robust matching of ultrasound images is a challenging problem as images of the same anatomy often present non-trivial differences. This poses an obstacle for ultrasound guidance in radiotherapy. Thus our objective is to overcome this obstacle by designing and evaluating an image blocks matching framework based on a two channel deep convolutional neural network. Methods: We extend to 3D an algorithmic structure previously introduced for 2D image feature learning [1]. To obtain the similarity between two 3D image blocks A and B, the 3D image blocks are divided into 2D patches Ai and Bi. The similarity is then calculated as the average similarity score of Ai and Bi. The neural network was then trained with public non-medical image pairs, and subsequently evaluated on ultrasound image blocks for the following scenarios: (S1) same image blocks with/without shifts (A and A-shift-x); (S2) non-related random block pairs; (S3) ground truth registration matched pairs of different ultrasound images with/without shifts (A-i and A-reg-i-shift-x). Results: For S1 the similarity scores of A and A-shift-x were 32.63, 18.38, 12.95, 9.23, 2.15 and 0.43 for x=ranging from 0 mm to 10 mm in 2 mm increments. For S2 the average similarity score for non-related block pairs was −1.15. For S3 the average similarity score of ground truth registration matched blocks A-i and A-reg-i-shift-0 (1≤i≤5) was 12.37. After translating A-reg-i-shift-0 by 0 mm, 2 mm, 4 mm, 6 mm, 8 mm, and 10 mm, the average similarity scores of A-i and A-reg-i-shift-x were 11.04, 8.42, 4.56, 2.27, and 0.29 respectively. Conclusion: The proposed method correctly assigns highest similarity to corresponding 3D ultrasound image blocks despite differences in image content and thus can form the basis for ultrasound image registration and tracking.[1] Zagoruyko, Komodakis, “Learning to compare image patches via convolutional neural networks', IEEE CVPR 2015,pp.4353–4361.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-16: Planar KV Imaging Dose Reduction Study

Purpose: IGRT has become an indispensable tool in modern radiotherapy with kV imaging used in many departments due to superior image quality and lower dose when compared to MV imaging. Many departments use manufacturer supplied protocols for imaging which are not always optimised between image quality and radiation dose (ALARA). Methods: Whole body phantom PBU-50 (Kyoto Kagaku ltd., Japan) for imaging in radiology has been imaged on Varian iX accelerator (Varian Medical Systems, USA) with OBI 1.5 system. Manufacturer’s default protocols were adapted by modifying kV and mAs values when imaging different anatomical regions of the phantom (head, thorax, abdomen, pelvis, extremities). Images with different settings were independently reviewed by two persons and their suitability for IGRT set-up correction protocols were evaluated. The suitable images with the lowest mAs were then selected. The entrance surface dose (ESD) for manufacturer’s default protocols and modified protocols were measured with RTI Black Piranha (RTI Group, Sweden) and compared. Image quality was also measured with kVQC phantom (Standard Imaging, USA) for different protocols. The modified protocols have been applied for clinical work. Results: For most cases optimized protocols reduced the ESD on average by a factor of 3(range 0.9–8.5). Further reduction in ESD has been observed by applying bow-tie filter designed for CBCT. The largest reduction in dose (12.2 times) was observed for Thorax lateral protocol. The dose was slightly increased (by 10%) for large pelvis AP protocol. Conclusion: Manufacturer’s default IGRT protocols could be optimised to reduce the ESD to the patient without losing the necessary image quality for patient set-up correction. For patient set-up with planar kV imaging the bony anatomy is mostly used and optimization should focus on this aspect. Therefore, the current approach with anthropomorphic phantom is more advantageous in optimization over standard kV quality control phantoms and SNR metrics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-EF-207A-05: Feasibility of Applying SMEIR Method On Small Animal 4D Cone Beam CT Imaging

Purpose: Small animal cone beam CT imaging has been widely used in preclinical research. Due to the higher respiratory rate and heat beats of small animals, motion blurring is inevitable and needs to be corrected in the reconstruction. Simultaneous motion estimation and image reconstruction (SMEIR) method, which uses projection images of all phases, proved to be effective in motion model estimation and able to reconstruct motion-compensated images. We demonstrate the application of SMEIR for small animal 4D cone beam CT imaging by computer simulations on a digital rat model. Methods: The small animal CBCT imaging system was simulated with the source-to-detector distance of 300 mm and the source-to-object distance of 200 mm. A sequence of rat phantom were generated with 0.4 mm{sup 3} voxel size. The respiratory cycle was taken as 1.0 second and the motions were simulated with a diaphragm motion of 2.4mm and an anterior-posterior expansion of 1.6 mm. The projection images were calculated using a ray-tracing method, and 4D-CBCT were reconstructed using SMEIR and FDK methods. The SMEIR method iterates over two alternating steps: 1) motion-compensated iterative image reconstruction by using projections from all respiration phases and 2) motion model estimation from projections directly through a 2D-3D deformable registration of the image obtained in the first step to projection images of other phases. Results: The images reconstructed using SMEIR method reproduced the features in the original phantom. Projections from the same phase were also reconstructed using FDK method. Compared with the FDK results, the images from SMEIR method substantially improve the image quality with minimum artifacts. Conclusion: We demonstrate that it is viable to apply SMEIR method to reconstruct small animal 4D-CBCT images.

60 APPLIED LIFE SCIENCES↗