Results for “Imaging” — Page 80

DOE OSTI2014

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R −0.58 and −0.19 for both studies, respectively. Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

MO-A-BRD-06: In Vivo Cherenkov Video Imaging to Verify Whole Breast Irradiation Treatment

Purpose: To show in vivo video imaging of Cherenkov emission (Cherenkoscopy) can be acquired in the clinical treatment room without affecting the normal process of external beam radiation therapy (EBRT). Applications of Cherenkoscopy, such as patient positioning, movement tracking, treatment monitoring and superficial dose estimation, were examined. Methods: In a phase 1 clinical trial, including 12 patients undergoing post-lumpectomy whole breast irradiation, Cherenkov emission was imaged with a time-gated ICCD camera synchronized to the radiation pulses, during 10 fractions of the treatment. Images from different treatment days were compared by calculating the 2-D correlations corresponding to the averaged image. An edge detection algorithm was utilized to highlight biological features, such as the blood vessels. Superficial dose deposited at the sampling depth were derived from the Eclipse treatment planning system (TPS) and compared with the Cherenkov images. Skin reactions were graded weekly according to the Common Toxicity Criteria and digital photographs were obtained for comparison. Results: Real time (fps = 4.8) imaging of Cherenkov emission was feasible and feasibility tests indicated that it could be improved to video rate (fps = 30) with system improvements. Dynamic field changes due to fast MLC motion were imaged in real time. The average 2-D correlation was about 0.99, suggesting the stability of this imaging technique and repeatability of patient positioning was outstanding. Edge enhanced images of blood vessels were observed, and could serve as unique biological markers for patient positioning and movement tracking (breathing). Small discrepancies exists between the Cherenkov images and the superficial dose predicted from the TPS but the former agreed better with actual skin reactions than did the latter. Conclusion: Real time Cherenkoscopy imaging during EBRT is a novel imaging tool that could be utilized for patient positioning, movement tracking, treatment monitoring, superficial dose and skin reaction estimation and prediction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based on an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Sci—Fri AM: Mountain — 02: A comparison of dose reduction methods on image quality for cone beam CT

Modern radiotherapy uses highly conformai dose distributions and therefore relies on daily image guidance for accurate patient positioning. Kilovoltage cone beam CT is one technique that is routinely used for patient set-up and results in a high dose to the patient relative to planar imaging techniques. This study uses an Elekta Synergy linac equipped with XVI cone beam CT to investigate the impact of various imaging parameters on dose and image quality. Dose and image quality are assessed as functions of x-ray tube voltage, tube current and the number of projections in the scan. In each case, the dose measurements confirm that as each parameter increases the dose increases. The assessment of high contrast resolution shows little dependence on changes to the image technique. However, low contrast visibility suggests a trade off between dose and image quality. Particularly for changes in tube potential, the dose increases much faster as a function of voltage than the corresponding increase in low contrast image quality. This suggests using moderate values of the peak tube voltage (100 – 120 kVp) since higher values result in significant dose increases with little gain in image quality. Measurements also indicate that increasing tube current achieves the greatest degree of improvement in the low contrast visibility. The results of this study highlight the need to establish careful imaging protocols to limit dose to the patient and to limit changes to the imaging parameters to those cases where there is a clear clinical requirement for improved image quality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Imaging a moving lung tumor with megavoltage cone beam computed tomography

Purpose: Respiratory motion may affect the accuracy of image guidance of radiation treatment of lung cancer. A cone beam computed tomography (CBCT) image spans several breathing cycles, resulting in a blurred object with a theoretical size equal to the sum of tumor size and breathing motion. However, several factors may affect this theoretical relationship. The objective of this study was to analyze the effect of tumor motion on megavoltage (MV)-CBCT images, by comparing target sizes on simulation and pretreatment images of a large cohort of lung cancer patients. Methods: Ninety-three MV-CBCT images from 17 patients were analyzed. Internal target volumes were contoured on each MV-CBCT dataset [internal target volume (ITV{sub CB})]. Their extent in each dimension was compared to that of two volumes contoured on simulation 4-dimensional computed tomography (4D-CT) images: the combination of the tumor contours of each phase of the 4D-CT (ITV{sub 4D}) and the volume contoured on the average CT calculated from the 4D-CT phases (ITV{sub ave}). Tumor size and breathing amplitude were assessed by contouring the tumor on each CBCT raw projection where it could be unambiguously identified. The effect of breathing amplitude on the quality of the MV-CBCT image reconstruction was analyzed. Results: The mean differences between the sizes of ITV{sub CB} and ITV{sub 4D} were −1.6 ± 3.3 mm (p < 0.001), −2.4 ± 3.1 mm (p < 0.001), and −7.2 ± 5.3 mm (p < 0.001) in the anterior/posterior (AP), left/right (LR), and superior/inferior (SI) directions, respectively, showing that MV-CBCT underestimates the full target size. The corresponding mean differences between ITV{sub CB} and ITV{sub ave} were 0.3 ± 2.6 mm (p = 0.307), 0.0 ± 2.4 mm (p = 0.86), and −4.0 ± 4.3 mm (p < 0.001), indicating that the average CT image is more representative of what is visible on MV-CBCT in the AP and LR directions. In the SI directions, differences between ITV{sub CB} and ITV{sub ave} could be separated into two groups based on tumor motion: −3.2 ± 3.2 mm for tumor motion less than 15 mm and −10.9 ± 6.3 mm for tumor motion greater than 15 mm. Deviations of measured target extents from their theoretical values derived from tumor size and motion were correlated with motion amplitude similarly for both MV-CBCT and average CT images, suggesting that the two images were subject to similar motion artifacts for motion less than 15 mm. Conclusions: MV-CBCT images are affected by tumor motion and tend to under-represent the full target volume. For tumor motion up to 15 mm, the volume contoured on average CT is comparable to that contoured on the MV-CBCT. Therefore, the average CT should be used in image registration for localization purposes, and the standard 5 mm PTV margin seems adequate. For tumor motion greater than 15 mm, an additional setup margin may need to be used to account for the increased uncertainty in tumor localization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Characteristic image quality of a third generation dual-source MDCT scanner: Noise, resolution, and detectability

Purpose: The purpose of this work was to assess the inherent image quality characteristics of a new multidetector computed tomography system in terms of noise, resolution, and detectability index as a function of image acquisition and reconstruction for a range of clinically relevant settings. Methods: A multisized image quality phantom (37, 30, 23, 18.5, and 12 cm physical diameter) was imaged on a SOMATOM Force scanner (Siemens Medical Solutions) under variable dose, kVp, and tube current modulation settings. Images were reconstructed with filtered back projection (FBP) and with advanced modeled iterative reconstruction (ADMIRE) with iterative strengths of 3, 4, and 5. Image quality was assessed in terms of the noise power spectrum (NPS), task transfer function (TTF), and detectability index for a range of detection tasks (contrasts of approximately 45, 90, 300, −900, and 1000 HU, and 2–20 mm diameter) based on a non-prewhitening matched filter model observer with eye filter. Results: Image noise magnitude decreased with decreasing phantom size, increasing dose, and increasing ADMIRE strength, offering up to 64% noise reduction relative to FBP. Noise texture in terms of the NPS was similar between FBP and ADMIRE (<5% shift in peak frequency). The resolution, based on the TTF, improved with increased ADMIRE strength by an average of 15% in the TTF 50% frequency for ADMIRE-5. The detectability index increased with increasing dose and ADMIRE strength by an average of 55%, 90%, and 163% for ADMIRE 3, 4, and 5, respectively. Assessing the impact of mA modulation for a fixed average dose over the length of the phantom, detectability was up to 49% lower in smaller phantom sections and up to 26% higher in larger phantom sections for the modulated scan compared to a fixed tube current scan. Overall, the detectability exhibited less variability with phantom size for modulated scans compared to fixed tube current scans. Conclusions: Image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose. The use of tube current modulation resulted in more consistent image quality with changing phantom size.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-D-207-03: Development of 4D-CBCT Imaging System with Dual Source KV X-Ray Tubes

Purpose: The purposes of this work are to develop 4D-CBCT imaging system with orthogonal dual source kV X-ray tubes, and to determine the imaging doses from 4D-CBCT scans. Methods: Dual source kV X-ray tubes were used for the 4D-CBCT imaging. The maximum CBCT field of view was 200 mm in diameter and 150 mm in length, and the imaging parameters were 110 kV, 160 mA and 5 ms. The rotational angle was 105°, the rotational speed of the gantry was 1.5°/s, the gantry rotation time was 70 s, and the image acquisition interval was 0.3°. The observed amplitude of infrared marker motion during respiration was used to sort each image into eight respiratory phase bins. The EGSnrc/BEAMnrc and EGSnrc/DOSXYZnrc packages were used to simulate kV X-ray dose distributions of 4D-CBCT imaging. The kV X-ray dose distributions were calculated for 9 lung cancer patients based on the planning CT images with dose calculation grid size of 2.5 x 2.5 x 2.5 mm. The dose covering a 2-cc volume of skin (D2cc), defined as the inner 5 mm of the skin surface with the exception of bone structure, was assessed. Results: A moving object was well identified on 4D-CBCT images in a phantom study. Given a gantry rotational angle of 105° and the configuration of kV X-ray imaging subsystems, both kV X-ray fields overlapped at a part of skin surface. The D2cc for the 4D-CBCT scans was in the range 73.8–105.4 mGy. Linear correlation coefficient between the 1000 minus averaged SSD during CBCT scanning and D2cc was −0.65 (with a slope of −0.17) for the 4D-CBCT scans. Conclusion: We have developed 4D-CBCT imaging system with dual source kV X-ray tubes. The total imaging dose with 4D-CBCT scans was up to 105.4 mGy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

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

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

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A Monte Carlo study on {sup 223}Ra imaging for unsealed radionuclide therapy

Purpose: Radium-223 ({sup 223}Ra), an α-emitting radionuclide, is used in unsealed radionuclide therapy for metastatic bone tumors. The demand for qualitative {sup 223}Ra imaging is growing to optimize dosimetry. The authors simulated {sup 223}Ra imaging using an in-house Monte Carlo simulation code and investigated the feasibility and utility of {sup 223}Ra imaging. Methods: The Monte Carlo code comprises two modules, HEXAGON and NAI. The HEXAGON code simulates the photon and electron interactions in the tissues and collimator, and the NAI code simulates the response of the NaI detector system. A 3D numeric phantom created using computed tomography images of a chest phantom was installed in the HEXAGON code. {sup 223}Ra accumulated in a part of the spine, and three x-rays and 19 γ rays between 80 and 450 keV were selected as the emitted photons. To evaluate the quality of the {sup 223}Ra imaging, the authors also simulated technetium-99m ({sup 99m}Tc) imaging under the same conditions and compared the results. Results: The sensitivities of the three photopeaks were 147 counts per unit of source activity (cps MBq{sup −1}; photopeak: 84 keV, full width of energy window: 20%), 166 cps MBq{sup −1} (154 keV, 15%), and 158 cps MBq{sup −1} (270 keV, 10%) for a low-energy general-purpose (LEGP) collimator, and those for the medium-energy general-purpose (MEGP) collimator were 33, 13, and 8.0 cps MBq{sup −1}, respectively. In the case of {sup 99m}Tc, the sensitivity was 55 cps MBq{sup −1} (141 keV, 20%) for LEGP and 52 cps MBq{sup −1} for MEGP. The fractions of unscattered photons of the total photons reflecting the image quality were 0.09 (84 keV), 0.03 (154 keV), and 0.02 (270 keV) for the LEGP collimator and 0.41, 0.25, and 0.50 for the MEGP collimator, respectively. Conversely, this fraction was approximately 0.65 for the simulated {sup 99m}Tc imaging. The sensitivity with the LEGP collimator appeared very high. However, almost all of the counts were because of photons that penetrated or were scattered in the collimator; therefore, the proportions of unscattered photons were small. Conclusions: Their simulation study revealed that the most promising scheme for {sup 223}Ra imaging is an 84-keV window using an MEGP collimator. The sensitivity of the photopeaks above 100 keV is too low for {sup 223}Ra imaging. A comparison of the fractions of unscattered photons reveals that the sensitivity and image quality are approximately two-thirds of those for {sup 99m}Tc imaging.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-DE-202-01: Image-Guided Focused Ultrasound Surgery and Therapy

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-CAMPUS-JeP1-03: Luminescence Imaging of Water During Proton Beam Irradiation for Range Estimation

Purpose: Since proton therapy has the ability to selectively deliver a dose to a target tumor, the dose distribution should be accurately measured. A precise and efficient method to evaluate the dose distribution is desired. We found that luminescence was emitted from water during proton irradiation and thought this phenomenon could be used for estimating the dose distribution. Methods: For this purpose, we placed water phantoms set on a table with a spot-scanning proton-therapy system, and luminescence images of these phantoms were measured with a high-sensitivity cooled charge coupled device (CCD) camera during proton-beam irradiation. We also conducted the imaging of phantoms of pure-water, fluorescein solution and acrylic block. We made three dimensional images from the projection data. Results: The luminescence images of water phantoms during the proton-beam irradiations showed clear Bragg peaks, and the measured proton ranges from the images were almost the same as those obtained with an ionization chamber. The image of the pure-water phantom also showed almost the same distribution as the tap-water phantom, indicating that the luminescence image was not related to impurities in the water. The luminescence image of fluorescein solution had ∼3 times higher intensity than water, with the same proton range as that of water. The luminescence image of the acrylic phantom had 14.5% shorter proton range than that of water; the proton range in the acrylic phantom was relatively matched with the calculated value. The luminescence images of the tap-water phantom during proton irradiation could be obtained in less than 2 sec. Three dimensional images were successfully obtained which have more quantitative information. Conclusion: Luminescence imaging during proton-beam irradiation has the potential to be a new method for range estimations in proton therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-FG-BRB-11: Design and Evaluation of a Robotic C-Arm CBCT System for Image-Guided Proton Therapy

Purpose: To describe the design and performance of a ceiling-mounted robotic C-arm CBCT system for image-guided proton therapy. Methods: Uniquely different from traditional C-arm CBCT used in interventional radiology, the imaging system was designed to provide volumetric image guidance for patients treated on a 190-degree proton gantry system and a 6 degree-of-freedom (DOF) robotic patient positioner. The mounting of robotic arms to the ceiling rails, rather than gantry or nozzle, provides the flexibility in imaging locations (isocenter, iso+27cm in X, iso+100cm in Y) in the room and easier upgrade as technology advances. A kV X-ray tube and a 43×43cm flat panel imager were mounted to a rotating C-ring (87cm diameter), which is coupled to the C-arm concentrically. Both C-arm and the robotic arm remain stationary during imaging to maintain high position accuracy. Source-to-axis distance and source-to-imager distance are 100 and 150cm, respectively. A 14:1 focused anti-scatter grid and a bowtie filer are used for image acquisition. A unique automatic collimator device of 4 independent blades for adjusting field of view and reducing patient dose has also been developed. Results: Sub-millimeter position accuracy and repeatability of the robotic C-arm were measured with a laser tracker. High quality CBCT images for positioning can be acquired with a weighted CTDI of 3.6mGy (head in 200° full fan mode: 100kV, 20mA, 20ms, 10fps)-8.7 mGy (pelvis in 360° half fan mode: 125kV, 42mA, 20ms, 10fps). Image guidance accuracy achieved <1mm (3D vector) with automatic 3D-3D registration for anthropomorphic head and pelvis phantoms. Since November 2015, 22 proton therapy patients have undergone daily CBCT imaging for 6 DOF positioning. Conclusion: Decoupled from gantry and nozzle, this CBCT system provides a unique solution for volumetric image guidance with half/partial proton gantry systems. We demonstrated that daily CBCT can be integrated into proton therapy for pre-treatment position verification.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-202-01: Pitfalls and Remedies in PET/CT Imaging for RT Planning

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy. The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-202-02: The Use of Hypoxia PET Imaging for Radiotherapy

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy. The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand the basics of using FDG PET/CT for tumor response evaluation. Learn about recent advancement in PET/CT radiomics and non-FDG PET tracers for response assessment. This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Deep machine learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging

Two-photon excitation fluorescence (2PEF) allows imaging of tissue up to about one millimeter in thickness. Typically, reducing fluorescence excitation exposure reduces the quality of the image. However, using deep learning super resolution techniques, these low-resolution images can be converted to high-resolution images. This work explores improving human tissue imaging by applying deep learning to maximize image quality while reducing fluorescence excitation exposure. We analyze two methods: a method based on U-Net, and a patch-based regression method. Both methods are evaluated on a skin dataset and an eye dataset. The eye dataset includes 1200 paired high power and low power images of retinal organoids. The skin dataset contains multiple frames of each sample of human skin. High-resolution images were formed by averaging 70 frames for each sample and low-resolution images were formed by averaging the first 7 and 15 frames for each sample. The skin dataset includes 550 images for each of the resolution levels. We track two measures of performance for the two methods: mean squared error (MSE) and structural similarity index measure (SSIM). For the eye dataset, the patches method achieves an average MSE of 27,611 compared to 146,855 for the U-Net method, and an average SSIM of 0.636 compared to 0.607 for the U-Net method. For the skin dataset, the patches method achieves an average MSE of 3.768 compared to 4.032 for the U-Net method, and an average SSIM of 0.824 compared to 0.783 for the U-Net method. Despite better performance on image quality, the patches method is worse than the U-Net method when comparing the speed of prediction, taking 303 seconds to predict one image compared to less than one second for the U-Net method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Neutron Transmission Imaging with a Portable D-T Neutron Generator

Fast-neutron transmission imaging provides complementary information to x-ray transmission imaging. While fast neutron imaging resolution is generally below x-ray imaging, 14-MeV neutrons have an advantage over portable x-ray systems. Neutrons have higher transmission through high-Z materials due to a more uniform attenuation as a function of material atomic number Z compared to X-rays, and can therefore image low-Z materials inside high-Z materials. As a result, portable neutron transmission imaging has many applications, including inspection of concrete and welds for corrosion in vehicles, bridges, and other infrastructure, measurement of material levels in containers, and inspection of suspicious packages. Fast-neutron imaging is also more practical for field use than thermal-neutron imaging due to the size and shielding requirements typical of thermal-imaging systems compared to the availability of small 14.1 MeV D-T neutron generators. However, there are limitations in portable fast-neutron imaging systems, including limited neutron output, limited light produced by neutron scintillators, and lower resolution due to neutron source spot size and 2-3 mm scintillator thickness. In addition, digital-panel dark-noise is roughly 100x higher than neutron scintillator light, and variations in noise across the panel and in time is comparable to the imaging signal. Here we discuss recent efforts in developing a portable fast-neutron radiography system, including an improved neutron scintillator, mitigation of panel noise, and new commercial portable D-T neutron generators. We also present MCNP efforts to model neutron imaging, including scintillator resolution and the effects of neutron scattering from the object and surrounding materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Bayesian Spatially Varying Multi-Regularization Image Deblurring

Many scientific experiments such as those found in astronomy, geology, microbiology, and X-ray radiography require the use of high-energy instruments to capture images. Since blur and noise are inevitably present in any imaging system, the images must be \deblurred" to extract the full information content. Mathematically, image deblurring is an ill-posed inverse problem that requires regularization. The regularization, in turn, has a large effect on the deblurred image: different regularization strengths, and types, lead to drastically different reconstructions. Moreover, many images contain a mixture of smooth and sharp features which suggests the use of multi-regularization, i.e., varying the type of regularization (e.g. Tikhonov or total variation) across the image. We address these issues by formulating the image deblurring problem within a hierarchical Bayesian framework in which we spatially adapt the strength of the regularization and also vary the regularization type across the image. In this way, the image itself, along with corresponding regularization strength at each pixel, are described jointly by a posterior distribution which we can sample by Markov chain Monte Carlo (MCMC) methods. We illustrate our techniques on simplified test problems and apply them to high-energy X-ray images taken at the Nevada National Security Site. Numerical tests show that our new method is robustly applicable and increases the quality of the image reconstruction when compared to other (Bayesian) methods.

97 MATHEMATICS AND COMPUTING↗