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DOE OSTI2014

TH-E-17A-02: High-Pitch and Sparse-View Helical 4D CT Via Iterative Image Reconstruction Method Based On Tensor Framelet

Purpose: 4D CT is routinely performed during radiation therapy treatment planning of thoracic and abdominal cancers. Compared with the cine mode, the helical mode is advantageous in temporal resolution. However, a low pitch (∼0.1) for 4D CT imaging is often required instead of the standard pitch (∼1) for static imaging, since standard image reconstruction based on analytic method requires the low-pitch scanning in order to satisfy the data sufficient condition when reconstructing each temporal frame individually. In comparison, the flexible iterative method enables the reconstruction of all temporal frames simultaneously, so that the image similarity among frames can be utilized to possibly perform high-pitch and sparse-view helical 4D CT imaging. The purpose of this work is to investigate such an exciting possibility for faster imaging with lower dose. Methods: A key for highpitch and sparse-view helical 4D CT imaging is the simultaneous reconstruction of all temporal frames using the prior that temporal frames are continuous along the temporal direction. In this work, such a prior is regularized through the sparsity transform based on spatiotemporal tensor framelet (TF) as a multilevel and high-order extension of total variation transform. Moreover, GPU-based fast parallel computing of X-ray transform and its adjoint together with split Bregman method is utilized for solving the 4D image reconstruction problem efficiently and accurately. Results: The simulation studies based on 4D NCAT phantoms were performed with various pitches (i.e., 0.1, 0.2, 0.5, and 1) and sparse views (i.e., 400 views per rotation instead of standard >2000 views per rotation), using 3D iterative individual reconstruction method based on 3D TF and 4D iterative simultaneous reconstruction method based on 4D TF respectively. Conclusion: The proposed TF-based simultaneous 4D image reconstruction method enables high-pitch and sparse-view helical 4D CT with lower dose and faster speed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Investigating the limits of PET/CT imaging at very low true count rates and high random fractions in ion-beam therapy monitoring

Purpose: External beam radiotherapy with protons and heavier ions enables a tighter conformation of the applied dose to arbitrarily shaped tumor volumes with respect to photons, but is more sensitive to uncertainties in the radiotherapeutic treatment chain. Consequently, an independent verification of the applied treatment is highly desirable. For this purpose, the irradiation-induced β{sup +}-emitter distribution within the patient is detected shortly after irradiation by a commercial full-ring positron emission tomography/x-ray computed tomography (PET/CT) scanner installed next to the treatment rooms at the Heidelberg Ion-Beam Therapy Center (HIT). A major challenge to this approach is posed by the small number of detected coincidences. This contribution aims at characterizing the performance of the used PET/CT device and identifying the best-performing reconstruction algorithm under the particular statistical conditions of PET-based treatment monitoring. Moreover, this study addresses the impact of radiation background from the intrinsically radioactive lutetium-oxyorthosilicate (LSO)-based detectors at low counts. Methods: The authors have acquired 30 subsequent PET scans of a cylindrical phantom emulating a patientlike activity pattern and spanning the entire patient counting regime in terms of true coincidences and random fractions (RFs). Accuracy and precision of activity quantification, image noise, and geometrical fidelity of the scanner have been investigated for various reconstruction algorithms and settings in order to identify a practical, well-suited reconstruction scheme for PET-based treatment verification. Truncated listmode data have been utilized for separating the effects of small true count numbers and high RFs on the reconstructed images. A corresponding simulation study enabled extending the results to an even wider range of counting statistics and to additionally investigate the impact of scatter coincidences. Eventually, the recommended reconstruction scheme has been applied to exemplary postirradiation patient data-sets. Results: Among the investigated reconstruction options, the overall best results in terms of image noise, activity quantification, and accurate geometrical recovery were achieved using the ordered subset expectation maximization reconstruction algorithm with time-of-flight (TOF) and point-spread function (PSF) information. For this algorithm, reasonably accurate (better than 5%) and precise (uncertainty of the mean activity below 10%) imaging can be provided down to 80 000 true coincidences at 96% RF. Image noise and geometrical fidelity are generally improved for fewer iterations. The main limitation for PET-based treatment monitoring has been identified in the small number of true coincidences, rather than the high intrinsic random background. Application of the optimized reconstruction scheme to patient data-sets results in a 25% − 50% reduced image noise at a comparable activity quantification accuracy and an improved geometrical performance with respect to the formerly used reconstruction scheme at HIT, adopted from nuclear medicine applications. Conclusions: Under the poor statistical conditions in PET-based treatment monitoring, improved results can be achieved by considering PSF and TOF information during image reconstruction and by applying less iterations than in conventional nuclear medicine imaging. Geometrical fidelity and image noise are mainly limited by the low number of true coincidences, not the high LSO-related random background. The retrieved results might also impact other emerging PET applications at low counting statistics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-D-BRA-07: A Phantom Study to Assess the Variability in Radiomics Features Extracted From Cone-Beam CT Images

Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on each machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-91: Quantitative Assessment of Early Hepatocellular Carcinoma and Cavernous Hemangioma of Live Using In-Line Phase-Contrast X-Ray Imaging

Purpose: To investigate the potential utility of in-line phase-contrast imaging (ILPCI) technique with synchrotron radiation in detecting early hepatocellular carcinoma and cavernous hemangioma of live using in vitro model system. Methods: Without contrast agents, three typical early hepatocellular carcinoma specimens and three typical cavernous hemangioma of live specimens were imaged using ILPCI. To quantitatively discriminate early hepatocellular carcinoma tissues and cavernous hemangioma tissues, the projection images texture feature based on gray level co-occurrence matrix (GLCM) were extracted. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, difference average, difference entropy and inverse difference moment, were obtained respectively. Results: In the ILPCI planar images of early hepatocellular carcinoma specimens, vessel trees were clearly visualized on the micrometer scale. Obvious distortion deformation was presented, and the vessel mostly appeared as a ‘dry stick’. Liver textures appeared not regularly. In the ILPCI planar images of cavernous hemangioma of live specimens, typical vessels had not been found compared with the early hepatocellular carcinoma planar images. The planar images of cavernous hemangioma of live specimens clearly displayed the dilated hepatic sinusoids with the diameter of less than 100 microns, but all of them were overlapped with each other. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, and difference average, showed a statistically significant between the two types specimens image (P<0.01), except the texture parameters of difference entropy and inverse difference moment(P>0.01). Conclusion: The results indicate that there are obvious changes in morphological levels including vessel structures and liver textures. The study proves that this imaging technique has a potential value in evaluating early hepatocellular carcinoma and cavernous hemangioma of live.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-52: Decreasing Frequency of Performing TG-142 Imaging QA – 5 Year Experience

Purpose This study is an update to check if the frequency of imaging QA suggested by AAPM Task Group Report 142 (TG142) is necessary with our 5 year experience. TG142 presents recommendations for QA criteria of IGRT treatment. ACR has adopted it to be the requirements for any radiatiotherapy practices; however, we propose to reduce the frequency on image quality QA according to this 5 year study.Method and Materials: This study uses VarianIX2100 and Siemens Artiste Linacs to perform QAs on KV, MV, CBCT modalities. The QA was designed following under the recommendations of TG142. This study reports the daily imaging positioning/repositioning and imaging and treatment coordinate coincidence. QA results on kV, MV and CBCT from 4/7/2010∼3/11/15 are analyzed. KV, MV, CBCT images are taken with the Varian isocube localized at the isocenter. Digital graticule is used in the software to verify the isocenter position. CBCT images are taken with the cube placed at 1cm superior, lateral and anterior of the isocenter. In-line fusion software is used to verify the contrived shift. Digital ruler provided at the on-board-imaging software or adaptive-targeting software was used to measure the position differences. The position differences were recorded at AP,LR,SI directions. Results 5 year records on kV, MV, CBCT show the shifts in all three directions are within the tolerance of 1mm suggested in TG142 for stereotactic radiation treatment(SRS/SRT). There is no occasion where shifts are outside 1mm tolerance. Conclusions The daily imaging QA suggested in TG142 is useful in ensuring the accuracy needed for SRS/SRT in IGRT. 5 year measurements presented suggest that decreasing the frequency of imaging QA may be acceptable, in particular for institutions reporting no violation of tolerance over periods of few years.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-FG-210-02: Implementation of Image-Guided Prostate HDR Brachytherapy Using MR-Ultrasound Fusion

Ultrasound (US) is one of the most widely used imaging modalities in medical practice. Since US imaging offers real-time imaging capability, it has becomes an excellent option to provide image guidance for brachytherapy (IGBT). (1) The physics and the fundamental principles of US imaging are presented, and the typical steps required to commission an US system for IGBT is provided for illustration. (2) Application of US for prostate HDR brachytherapy, including partial prostate treatments using MR-ultrasound co-registration to enable a focused treatment on the disease within the prostate is also presented. Prostate HDR with US image guidance planning can benefit from real time visualization of the needles, and fusion of the ultrasound images with T2 weighted MR allows the focusing of the treatment to the specific areas of disease within the prostate, so that the entire gland need not be treated. Finally, (3) ultrasound guidance for an eye plaque program is presented. US can be a key component of placement and QA for episcleral plaque brachytherapy for ocular cancer, and the UCLA eye plaque program with US for image guidance is presented to demonstrate the utility of US verification of plaque placement in improving the methods and QA in episcleral plaque brachytherapy. Learning Objectives: To understand the physics of an US system and the necessary aspects of commissioning US for image guided brachytherapy (IGBT). To understand real time planning of prostate HDR using ultrasound, and its application in partial prostate treatments using MR-ultrasound fusion to focus treatment on disease within the prostate. To understand the methods and QA in applying US for localizing the target and the implant during a episcleral plaque brachytherapy procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-EF-303-10: Single- Detector Proton Radiography as a Portal Imaging Equivalent for Proton Therapy

Purpose: In proton therapy, patient alignment is of critical importance due to the sensitivity of the proton range to tissue heterogeneities. Traditionally proton radiography is used for verification of the water-equivalent path length (WEPL), which dictates the depth protons reach. In this work we propose its use for alignment. Additionally, many new proton centers have cone-beam computed tomography in place of beamline X-ray imaging and so proton radiography offers a unique patient alignment verification similar to portal imaging in photon therapy. Method: Proton radiographs of a CIRS head phantom were acquired using the Beam Imaging System (BIS) (IBA, Louvain-la-Neuve) in a horizontal beamline. A scattered beam was produced using a small, dedicated, range modulator (RM) wheel fabricated out of aluminum. The RM wheel was rotated slowly (20 sec/rev) using a stepper motor to compensate for the frame rate of the BIS (120 ms). Dose rate functions (DRFs) over two RM wheel rotations were acquired. Calibration was made with known thicknesses of homogeneous solid water. For each pixel the time width, skewness and kurtosis of the DRFs were computed. The time width was used to compute the object WEPL. In the heterogeneous phantom, the excess skewness and excess kurtosis (i.e. difference from homogeneous cases) were computed and assessed for suitability for patient set up. Results: The technique allowed for the simultaneous production of images that can be used for WEPL verification, showing few internal details, and excess skewness and kurtosis images that can be used for soft tissue alignment. These latter images highlight areas where range mixing has occurred, correlating with phantom heterogeneities. Conclusion: The excess skewness and kurtosis images contain details that are not visible in the WET images. These images, unique to the time-resolved proton radiographic method, could be used for patient set up according to soft tissues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A minimum spanning forest based classification method for dedicated breast CT images

Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting model used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Luminescence imaging of water during carbon-ion irradiation for range estimation

Purpose: The authors previously reported successful luminescence imaging of water during proton irradiation and its application to range estimation. However, since the feasibility of this approach for carbon-ion irradiation remained unclear, the authors conducted luminescence imaging during carbon-ion irradiation and estimated the ranges. Methods: The authors placed a pure-water phantom on the patient couch of a carbon-ion therapy system and measured the luminescence images with a high-sensitivity, cooled charge-coupled device camera during carbon-ion irradiation. The authors also carried out imaging of three types of phantoms (tap-water, an acrylic block, and a plastic scintillator) and compared their intensities and distributions with those of a phantom containing pure-water. Results: The luminescence images of pure-water phantoms during carbon-ion irradiation showed clear Bragg peaks, and the measured carbon-ion ranges from the images were almost the same as those obtained by simulation. The image of the tap-water phantom showed almost the same distribution as that of the pure-water phantom. The acrylic block phantom’s luminescence image produced seven times higher luminescence and had a 13% shorter range than that of the water phantoms; the range with the acrylic phantom generally matched the calculated value. The plastic scintillator showed ∼15 000 times higher light than that of water. Conclusions: Luminescence imaging during carbon-ion irradiation of water is not only possible but also a promising method for range estimation in carbon-ion therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using an active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

Purpose: Coherent scatter based imaging has shown improved contrast and molecular specificity over conventional digital mammography however the biological risks have not been quantified due to a lack of accurate information on absorbed dose. This study intends to characterize the dose distribution and average glandular dose from coded aperture coherent scatter spectral imaging of the breast. The dose deposited in the breast from this new diagnostic imaging modality has not yet been quantitatively evaluated. Here, various digitized anthropomorphic phantoms are tested in a Monte Carlo simulation to evaluate the absorbed dose distribution and average glandular dose using clinically feasible scan protocols. Methods: Geant4 Monte Carlo radiation transport simulation software is used to replicate the coded aperture coherent scatter spectral imaging system. Energy sensitive, photon counting detectors are used to characterize the x-ray beam spectra for various imaging protocols. This input spectra is cross-validated with the results from XSPECT, a commercially available application that yields x-ray tube specific spectra for the operating parameters employed. XSPECT is also used to determine the appropriate number of photons emitted per mAs of tube current at a given kVp tube potential. With the implementation of the XCAT digital anthropomorphic breast phantom library, a variety of breast sizes with differing anatomical structure are evaluated. Simulations were performed with and without compression of the breast for dose comparison. Results: Through the Monte Carlo evaluation of a diverse population of breast types imaged under real-world scan conditions, a clinically relevant average glandular dose for this new imaging modality is extrapolated. Conclusion: With access to the physical coherent scatter imaging system used in the simulation, the results of this Monte Carlo study may be used to directly influence the future development of the modality to keep breast dose to a minimum while still maintaining clinically viable image quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-177: A Novel Image Analysis Technique (center Pixel Method) to Quantify End-To-End Tests

Purpose: To implement a novel image analysis technique, “center pixel method”, to quantify end-to-end tests accuracy of a frameless, image guided stereotactic radiosurgery system. Methods: The localization accuracy was determined by delivering radiation to an end-to-end prototype phantom. The phantom was scanned with 0.8 mm slice thickness. The treatment isocenter was placed at the center of the phantom. In the treatment room, CBCT images of the phantom (kVp=77, mAs=1022, slice thickness 1 mm) were acquired to register to the reference CT images. 6D couch correction were applied based on the registration results. Electronic Portal Imaging Device (EPID)-based Winston Lutz (WL) tests were performed to quantify the errors of the targeting accuracy of the system at 15 combinations of gantry, collimator and couch positions. The images were analyzed using two different methods. a) The classic method. The deviation was calculated by measuring the radial distance between the center of the central BB and the full width at half maximum of the radiation field. b) The center pixel method. Since the imager projection offset from the treatment isocenter was known from the IsoCal calibration, the deviation was determined between the center of the BB and the central pixel of the imager panel. Results: Using the automatic registration method to localize the phantom and the classic method of measuring the deviation of the BB center, the mean and standard deviation of the radial distance was 0.44 ± 0.25, 0.47 ± 0.26, and 0.43 ± 0.13 mm for the jaw, MLC and cone defined field sizes respectively. When the center pixel method was used, the mean and standard deviation was 0.32 ± 0.18, 0.32 ± 0.17, and 0.32 ± 0.19 mm respectively. Conclusion: Our results demonstrated that the center pixel method accurately analyzes the WL images to evaluate the targeting accuracy of the radiosurgery system. The work was supported by a Research Scholar Grant, RSG-15-137-01-CCE from the American Cancer Society.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-222: Using PET Imaging to Evaluate Proliferation and Blood Flow in Irradiated and Non-Irradiated Bone Marrow 1 Year After Chemoradiation Therapy

Purpose: To compare proliferation and blood flow in pelvic and thoracic bone marrow 1 year after pelvic chemoradiation. Methods: Sixteen pelvic cancer patients were enrolled in an IRB-approved protocol to acquire FLT PET images during radiation therapy simulation (baseline) and 1 year after chemoradiation therapy. Three subjects also had optional O-15 water PET images acquired 1 year after chemoradiation therapy. Baseline FLT PET images were used to create IMRT plans to spare pelvic bone marrow identified as regions with FLT SUV ≥ 2 without compromising PTV coverage or OAR sparing. Marrow VOIs were defined using a 50% maximum pixel value threshold on baseline FLT PET images (VIEW, PMOD version 3.5) in the sacrum and thoracic spine representing irradiated and non-irradiated regions, respectively. FLT PET and O-15 water PET images acquired 1 year after therapy were co-registered to baseline images (FUSION PMOD) and the same VOIs were used to measure proliferation (FLT SUV) and blood flow (O-15 water uptake). Separate image-based input functions were used for blood flow quantitation in each VOI. Results: Mean 1 year FLT SUV in sacral and thoracic VOIs for were 1.1 ± 0.4 and 6.5 ± 1.7, respectively for N = 16 subjects and were 1.2 ± 0.2 and 5.6 ± 1.6, respectively for N = 3 subjects who also underwent O-15 water imaging. Blood flow measures in equivalent sacral and thoracic marrow regions (N = 3) were 21.3 ± 8.7 and 18.3 ± 4.9 mL/min/100mL respectively. Conclusion: Decreased bone marrow proliferation measured by FLT SUV does not appear to correspond to decreased blood flow as measured by O-15 water PET imaging. Based on this small sample at a single time point, reduced blood supply does not explain reductions in bone marrow proliferative activity 1 year after chemoradiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-IeP3-11: On the Utility of Pixel Variance to Characterize Noise for Image Receptors of Digital Radiography Systems

Purpose: To characterize noise for image receptors of digital radiography systems based on pixel variance. Methods: Nine calibrated digital image receptors associated with nine new portable digital radiography systems (Carestream Health, Inc., Rochester, NY) were used in this study. For each image receptor, thirteen images were acquired with RQA5 beam conditions for input detector air kerma ranging from 0 to 110 µGy, and linearized ‘For Processing’ images were extracted. Mean pixel value (MPV), standard deviation (SD) and relative noise (SD/MPV) were obtained from each image using ROI sizes varying from 2.5×2.5 to 20×20 mm{sup 2}. Variance (SD{sup 2}) was plotted as a function of input detector air kerma and the coefficients of the quadratic fit were used to derive structured, quantum and electronic noise coefficients. Relative noise was also fitted as a function of input detector air kerma to identify noise sources. The fitting functions used least-squares approach. Results: The coefficient of variation values obtained using different ROI sizes was less than 1% for all the images. The structured, quantum and electronic coefficients obtained from the quadratic fit of variance (r>0.97) were 0.43±0.10, 3.95±0.27 and 2.89±0.74 (mean ± standard deviation), respectively, indicating that overall the quantum noise was the dominant noise source. However, for one system electronic noise coefficient (3.91) was greater than quantum noise coefficient (3.56) indicating electronic noise to be dominant. Using relative noise values, the power parameter of the fitting equation (|r|>0.93) showed a mean and standard deviation of 0.46±0.02. A 0.50 value for this power parameter indicates quantum noise to be the dominant noise source whereas values around 0.50 indicate presence of other noise sources. Conclusion: Characterizing noise from pixel variance assists in identifying contributions from various noise sources that, eventually, may affect image quality. This approach may be integrated during periodic quality assessments of digital image receptors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia

Purpose: The values in a PET image which represent activity concentrations of a radioactive tracer are influenced by a large number of parameters including patient conditions as well as image acquisition and reconstruction. This work investigates noise characteristics in PET images for various image acquisition and image reconstruction parameters. Methods: Different phantoms with homogeneous activity distributions were scanned using several acquisition parameters and reconstructed with numerous sets of reconstruction parameters. Images from six PET scanners from different vendors were analyzed and compared with respect to quantitative noise characteristics. Local noise metrics, which give rise to a threshold value defining the metric of hypoxic fraction, as well as global noise measures in terms of noise power spectra (NPS) were computed. In addition to variability due to different reconstruction parameters, spatial variability of activity distribution and its noise metrics were investigated. Patient data from clinical trials were mapped onto phantom scans to explore the impact of the scanner’s intrinsic noise variability on quantitative clinical analysis. Results: Local noise metrics showed substantial variability up to an order of magnitude for different reconstruction parameters. Investigations of corresponding NPS revealed reconstruction dependent structural noise characteristics. For the acquisition parameters, noise metrics were guided by Poisson statistics. Large spatial non-uniformity of the noise was observed in both axial and radial direction of a PET image. In addition, activity concentrations in PET images of homogeneous phantom scans showed intriguing spatial fluctuations for most scanners. The clinical metric of the hypoxic fraction was shown to be considerably influenced by the PET scanner’s spatial noise characteristics. Conclusion: We showed that a hypoxic fraction metric based on noise characteristics requires careful consideration of the various dependencies in order to justify its quantitative validity. This work may result in recommendations for harmonizing QA of PET imaging for multi-institutional clinical trials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-BRA-06: 3D Image Acquisition and Reconstruction Explained with Online Animations

Purpose: Understanding the principles of 3D imaging and image reconstruction is fundamental to the field of medical imaging. Clinicians, technologists, physicists, patients, students, and inquisitive minds all stand to benefit from greater comprehension of the supporting technologies. To help explain the basic principles of 3D imaging, we developed multi-frame animations that convey the concepts of tomographic imaging. The series of free (gif) animations are accessible online, and provide a multimedia introduction to the main concepts of image reconstruction. Methods: Text and animations were created to convey the principles of analytic tomography in CT, PET, and SPECT. Specific topics covered included: principles of sinograms/image data storage, forward projection, principles of PET acquisitions, and filtered backprojection. A total of 8 animations were created and presented for CT, PET, and digital phantom formats. In addition, a free executable is also provided to allow users to create their own tomographic animations – providing an opportunity for interaction and personalization to help foster user interest. Results: Tutorial text and animations have been posted online, freely available to view or download. The animations are in first position in a google search of “image reconstruction animations”. The website currently receives approximately 200 hits/month, from all over the world, and the usage is growing. Positive feedback has been collected from users. Conclusion: We identified a need for improved teaching tools to help visualize the (temporally variant) concepts of image reconstruction, and have shown that animations can be a useful tool for this aspect of education. Furthermore, posting animations freely on the web has shown to be a good way to maximize their impact in the community. In future endeavors, we hope to expand this animated content, to cover principles of iterative reconstruction, as well as other phenomena relating to imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-209-03: Assessing Image Quality

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-BRA-01: SCIENCE COUNCIL JUNIOR INVESTIGATOR COMPETITION WINNER: Acceleration of a Limited-Angle Intrafraction Verification (LIVE) System Using Adaptive Prior Knowledge Based Image Estimation

Purpose: To develop an adaptive prior knowledge based image estimation method to reduce the scan angle needed in the LIVE system to reconstruct 4D-CBCT for intrafraction verification. Methods: The LIVE system has been previously proposed to reconstructs 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. This system uses limited-angle beam’s eye view (BEV) MV cine images acquired from the treatment beam together with the orthogonally acquired limited-angle kV projections to reconstruct 4D-CBCT images for target verification during treatment. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to further reduce the scanning angle needed to reconstruct the CBCT images. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on projections acquired in limited angle (orthogonal 6°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of patient motion.The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the efficacy of this technique with LIVE system. A lung patient was simulated with different scenario, including baseline drifts, amplitude change and phase shift. Limited-angle orthogonal kV and beam’s eye view (BEV) MV projections were generated for each scenario. The CBCT reconstructed by these projections were compared with the ground-truth generated in XCAT.Volume-percentage-difference (VPD) and center-of-mass-shift (COMS) were calculated between the reconstructed and the ground-truth tumors to evaluate the reconstruction accuracy. Results: Using orthogonal-view of 6° kV and BEV- MV projections, the VPD/COMS values were 12.7±4.0%/0.7±0.5 mm, 13.0±5.1%/0.8±0.5 mm, and 11.4±5.4%/0.5±0.3 mm for the three scenarios, respectively. Conclusion: The technique enables LIVE to accurately reconstruct 4D-CBCT images using only orthogonal 6° angle, which greatly improves the efficiency and reduces dose of LIVE for intrafraction verification.

60 APPLIED LIFE SCIENCES↗