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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↗
DOE OSTI2022

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

Purpose: The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. Methods: The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. Results: For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. Conclusions: This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Concept of an upright wearable positron emission tomography imager in humans

Abstract Background Positron Emission Tomography ( PET ) is traditionally used to image patients in restrictive positions, with few devices allowing for upright, brain‐dedicated imaging. Our team has explored the concept of wearable PET imagers which could provide functional brain imaging of freely moving subjects. To test feasibility and determine future considerations for development, we built a rudimentary proof‐of‐concept prototype (Helmet_ PET ) and conducted tests in phantoms and four human volunteers. Methods Twelve Silicon Photomultiplier‐based detectors were assembled in a ring with exterior weight support and an interior mechanism that could be adjustably fitted to the head. We conducted brain phantom tests as well as scanned four patients scheduled for diagnostic F 18‐ FDG PET / CT imaging. For human subjects the imager was angled such that field of view included basal ganglia and visual cortex to test for typical resting‐state pattern. Imaging in two subjects was performed ~4 hr after PET / CT imaging to simulate lower injected F 18‐ FDG dose by taking advantage of the natural radioactive decay of the tracer (F 18 half‐life of 110 min), with an estimated imaging dosage of 25% of the standard. Results We found that imaging with a simple lightweight ring of detectors was feasible using a fraction of the standard radioligand dose. Activity levels in the human participants were quantitatively similar to standard PET in a set of anatomical ROI s. Typical resting‐state brain pattern activation was demonstrated even in a 1 min scan of active head rotation. Conclusion To our knowledge, this is the first demonstration of imaging a human subject with a novel wearable PET imager that moves with robust head movements. We discuss potential research and clinical applications that will drive the design of a fully functional device. Designs will need to consider trade‐offs between a low weight device with high mobility and a heavier device with greater sensitivity and larger field of view.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Automated Patient Identification and Localization Error Detection Using 2-Dimensional to 3-Dimensional Registration of Kilovoltage X-Ray Setup Images

Purpose: To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials: Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results: A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions: An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope

From neutron user principal investigator: We kindly request the public release of three neutron imaging datasets through ONCat. All datasets were collected from two forensic specimens, B12W and M8N, sectioned from zinc-filled steel-wire sockets recovered from the collapsed Arecibo Telescope. The dataset titled “Neutron radiographs of B12W and M8N socket sections of the Arecibo telescope” contains normalized two-dimensional (2D) neutron radiographs of the specimens, showing the geometry and spatial distribution of the steel wires embedded within the zinc matrix, as well as internal features such as voids and cracks. The dataset titled “Neutron computed tomography of B12W and M8N socket sections of the Arecibo telescope” contains normalized 2D neutron projection images acquired over a range of specimen rotation angles for one selected region of each specimen. These projection images were used to reconstruct three-dimensional (3D) tomographic volumes that reveal the embedded-wire geometry and internal defects. The dataset titled “Bragg edge imaging (BEI) of B12W and M8N socket sections of the Arecibo telescope” contains six time-of-flight (TOF) neutron imaging datasets, three from each specimen, acquired at regions of interest selected based on the radiographs. The spatially resolved 2D TOF images show the zinc matrix and embedded steel wires, and the wavelength-dependent neutron transmission data were used to characterize crystallographic texture within the zinc. All components and their condition are in the public domain as they are the property of the National Science Foundation (NSF). The neutron imaging data, part geometries, and detailed forensic information have been widely published in the Arecibo Telescope Collapse Forensic Report by Thornton Tomasetti Engineers and others (NASA report and NASEM report).

Bilheux, Hassina↗
DOE OSTI2022

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

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