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DOE OSTI2014

TU-F-18A-02: Iterative Image-Domain Decomposition for Dual-Energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

TH-A-18C-10: Dynamic Intensity Weighted Region of Interest Imaging

Purpose: For image guidance tasks full image quality is not required throughout the entire image. With dynamic filtration of the kV imaging beam the noise properties of the CT image can be locally controlled, providing a high quality image around the target volume with a lower quality surrounding region while providing substantial dose sparing to the patient as well as reduced scatter fluence on the detector. Methods: A dynamic collimation device with 3mm copper blades has been designed to mount in place of the bowtie filter on the On-Board Imager (Varian Medical Systems). The beam intensity is reduced by 95% behind the copper filters and the aperture is controlled dynamically to conformally illuminate a given ROI during a standard cone-beam CT scan. A data correction framework to account for the physical effects of the collimator prior to reconstruction was developed. Furthermore, to determine the dose savings and scatter reduction a monte carlo model was built in BEAMnrc with specifics from the Varian Monte Carlo Data Package. The MC model was validated with Gafchromic film. Results: The reconstructed image shows image quality comparable to a standard scan in the specified ROI, with higher noise and streaks in the outer region but still sufficient information for alignment to high contrast structures. The monte carlo modeling showed that the scatter-to-primary ratio was reduced from 1.26 for an unfiltered scan to 0.45 for an intensity weighted scan, suggesting that image quality may be improved in the inner ROI. Dose in the inner region was reduced 10–15% due to reduced scatter and by as much as 75% in the outer region. Conclusion: Dynamic intensity-weighted ROI imaging allows reduction of imaging dose to sensitive organs away from the target region while providing images that retain their utility for patient setup and procedure guidance. Funding was provided in part by Varian Medical Systems and NIH Grants 1RO1CA120540, T32EB002103, S10 RR021039 and P30 CA14599. The contents of this work are solely the responsibility of the authors and do not necessarily represent the official views of any of the supporting organizations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

3D high spectral and spatial resolution imaging of ex vivo mouse brain

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. Conclusions: High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of two conjugate PAR images. To evaluate the proposed algorithm, digital XCAT and physical dynamic cardiac phantom datasets are used. The XCAT phantom datasets were generated with heart rates of 70 and 100 bpm, respectively, by assuming a system rotation time of 300 ms. A physical dynamic cardiac phantom was scanned using a slowly rotating XCT system so that the effective heart rate will be 70 bpm for a system rotation speed of 300 ms. Results: In the XCAT phantom experiment, motion-compensated 3D images obtained from the proposed algorithm show coronary arteries with fewer motion artifacts for all phases. Moreover, object boundaries contaminated by motion are well restored. Even though object positions and boundary shapes are still somewhat different from the ground truth in some cases, the authors see that visibilities of coronary arteries are improved noticeably and motion artifacts are reduced considerably. The physical phantom study also shows that the visual quality of motion-compensated images is greatly improved. Conclusions: The authors propose a novel PAR image-based cardiac motion estimation and compensation algorithm. The algorithm requires an angular scan range of less than 360°. The excellent performance of the proposed algorithm is illustrated by using digital XCAT and physical dynamic cardiac phantom datasets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-40: Phantom Research On Monochromatic Images Taken by Dual CBCT with Multiple Energy Sets

Purpose: To evaluate the quality of monochromatic images at the same virtual monochromatic energy using dual cone-beam computed tomography (CBCT) with either kV/kV or MV/kV or MV/MV energy sets. Methods: CT images of Catphan 504 phantom were acquired using four different KV and MV settings: 80kV, 140kV, 4MV, 6MV. Three sets of monochromatic images were calculated: 80kV-140kV, 140kV-4MV and 4MV-6MV. Each set of CBCT images were reconstructed from the same selected virtual monochromatic energy of 1MeV. Contrast-to-Noise Ratios (CNRs) were calculated and compared between each pair of images with different energy sets. Results: Between kV/MV and MV/MV images, the CNRs are comparable for all inserts. However, differences of CNRs were observed between the kV/kV and kV/MV images. Delrin’s CNR ratio between kV/kV image and kV/MV image is 1.634. LDPE’s (Low-Density Polyethylene) CNR ratio between kV/kV and kV/MV images is 0.509. Polystyrene’s CNR ratio between kV/kV image and kV/MV image is 2.219. Conclusion: Preliminary results indicated that the CNRs calculated from CBCT images reconstructed from either kV/MV projections or MV/MV projections for the same selected virtual monochromatic energy may be comparable.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specific anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-F-CAMPUS-J-05: Verification for Prompt Gamma Ray Imaging During Proton Boron Fusion Therapy

Purpose: The purpose of this study is to verify the acquisition of the three dimensional single photon emission computed tomography (SPECT) image using prompt gamma ray originated from proton boron fusion therapy (PBFT). Methods: The real-time imaging system during the PBFT was simulated to acquire the tomographic image of the prompt gamma ray from treated tumor by the proton boron reaction, using Monte Carlo simulation (MCNPX). We acquired percentage depth dose (PDD) of the proton beam in the water phantom including the boron uptake region (BUR), the energy spectra of the prompt gamma ray and tomographic image which can show treated tumor regions. The prompt gamma ray image was reconstructed using maximum likelihood estimation maximization (MLEM) reconstruction algorithm with 64 projections. In addition, in order to evaluate the reconstructed image, the image profiles between BURs were extracted from the image. Results: In the PDD results, the Bragg-peak was amplified definitely when the proton’s maximum dose level was located at the BUR. This amplification is based on the generation of alpha particles. In addition, the prompt gamma ray peak of 719 keV was observed from the energy spectrum. Through the previous process, the tomographic image of prompt gamma ray from the BUR was reconstructed. The line profile was extracted from image including BURs, and it shows high signal-to-noise ratio. Conclusion: We confirmed that the real-time prompt gamma ray image during the PBFT was successfully deducted, and results of quantitative image analysis show good agreement with the original pattern of the BUR. This study first verified the imaging capability of the PBFT-SPECT system. In conclusion, the PBFT-SPECT system can realize the treated tumor monitoring during the PBFT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBs was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP4-13: Interfraction Treatment Monitoring Using Integrated Invivo EPID Images

Purpose: To investigate inter-fraction differences of dose delivery by analyzing portal images acquired during treatment and implement an automated system to generate a report for each fraction. Large differences in images between fractions can alert the physicist of possible machine performance issues or patient set-up errors. Methods: A Varian Novalis Tx equipped with a HD120 MLC and aS1000 electronic portal imaging device (EPID) was used in our study. EPID images are acquired in continuous acquisition mode for 32 volumetric arc therapy (VMAT) patients. The images are summed to create an image for each arc and a single image for each fraction. The first fraction is designated as the reference unless a machine error prevented acquisition of all images. The images for each beam as well as the fraction image are compared using gamma analysis at 1%/1mm, 2%/2mm and 3%/3mm. A report is then generated using an in house MatLab program containing the comparison for the current fraction as well as a history of previous fractions. The reports are automatically sent via email to the physicist for review. Fractions in which the total number of images was not within 5% of the reference number of images were not included in the results. Results: 91 of the 182 fractions recorded an image count within 5% of the reference. Gamma averages over all fractions and patients were 96.2% ±0.8% at 3%/3mm, 92.9% ±1% at 2%/2mm and 80.6% ±1.8% at 1%/1mm. The SD between fractions for each patient ranged from .004% to 10.4%. Of the 91 fractions 3 flagged due to low gamma values. After further investigation no significant errors were found. Conclusion: This toolkit can be used for in-vivo monitoring of treatment plan delivery an alert the physics staff of any inter-fraction discrepancies that may require further investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-JeP1-05: Water Equivalent Path Length Calculations Using Scatter-Corrected Head and Neck CBCT Images to Evaluate Patients for Adaptive Proton Therapy

Purpose: To establish a method to evaluate the dosimetric impact of anatomic changes in head and neck patients during proton therapy by using scatter-corrected cone-beam CT (CBCT) images. Methods: The water equivalent path length (WEPL) was calculated to the distal edge of PTV contours by using tomographic images available for six head and neck patients received photon therapy. The proton range variation was measured by calculating the difference between the distal WEPLs calculated with the planning CT and weekly treatment CBCT images. By performing an automatic rigid registration, six degrees-of-freedom (DOF) correction was made to the CBCT images to account for the patient setup uncertainty. For accurate WEPL calculations, an existing CBCT scatter correction algorithm, whose performance was already proven for phantom images, was calibrated for head and neck patient images. Specifically, two different image similarity measures, mutual information (MI) and mean square error (MSE), were tested for the deformable image registration (DIR) in the CBCT scatter correction algorithm. Results: The impact of weight loss was reflected in the distal WEPL differences with the aid of the automatic rigid registration reducing the influence of patient setup uncertainty on the WEPL calculation results. The WEPL difference averaged over distal area was 2.9 ± 2.9 (mm) across all fractions of six patients and its maximum, mostly found at the last available fraction, was 6.2 ± 3.4 (mm). The MSE-based DIR successfully registered each treatment CBCT image to the planning CT image. On the other hand, the MI-based DIR deformed the skin voxels in the planning CT image to the immobilization mask in the treatment CBCT image, most of which was cropped out of the planning CT image. Conclusion: The dosimetric impact of anatomic changes was evaluated by calculating the distal WEPL difference with the existing scatter-correction algorithm appropriately calibrated. Jihun Kim, Yang-Kyun Park, Gregory Sharp, and Brian Winey have received grant support from the NCI Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformation and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-209-08: Next Generation Dedicated 3D Breast Imaging with XACT

Purpose: Exposure to radiation increases the risk of cancer. We have designed a new imaging paradigm, X-ray induced acoustic computed tomography (XACT). Applying this innovative technology to breast imaging, an X-ray exposure can generate a 3D acoustic image, which dramatically reduces the radiation dose to patients when compared to conventional breast CT. Methods: Theoretical calculations are done to determine the appropriate X-ray energy and ultrasound frequency in breast XACT imaging. A series of breast CT image along the coronal plane from a patient with calcifications in the breast tissue are used as the source image. HU value based segmentation is done to distinguish the skin, adipose tissue, glandular tissue, breast calcification, and chest bone from each CT image. X-ray dose deposition in each pixel is calculated based on the tissue type by using GEANT4 Monte Carlo toolkits. The initial pressure rise caused by X-ray energy deposition is calculated according to tissue properties. Then, the X-ray induced acoustic wave propagation is simulated by K-WAVE toolkit. Breast XACT images are reconstructed from the recorded time-dependent ultrasound waves. Results: For imaging a breast with large size (16cm in diameter at chest wall), the photon energy of X-ray source and the central frequency of ultrasound detector is determined as 20keV and 5.5MHz. Approximately 10 times contrast between a calcification and the breast tissue can be acquire from XACT image. The calcification can be clearly identified from the reconstructed XACT image. Conclusion: XACT technique takes the advantages of X-ray absorption contrast and high ultrasonic resolution. With the proposed innovative technology, one can potentially reduce radiation dose to patient in 3D breast imaging as compared with current x-ray modalities, while still maintaining high imaging contrast and spatial resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanel of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Integrated PET/MR breast cancer imaging: Attenuation correction and implementation of a 16-channel RF coil

Purpose: This study aims to develop, implement, and evaluate a 16-channel radiofrequency (RF) coil for integrated positron emission tomography/magnetic resonance (PET/MR) imaging of breast cancer. The RF coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. Methods: A 16-channel breast array RF coil was designed for integrated PET/MR hybrid imaging of breast cancer lesions. The RF coil features a lightweight rigid design and is positioned with a spacer at a defined position on the patient table of an integrated PET/MR system. Attenuation correction is performed by generating and applying a dedicated 3D CT-based template attenuation map. Reposition accuracy of the RF coil on the system patient table while using the positioning frame was tested in repeated measurements using MR-visible markers. The MR, PET, and PET/MR imaging performances were systematically evaluated using modular breast phantoms. Attenuation correction of the RF coil was evaluated with difference measurements of the active breast phantoms filled with radiotracer in the PET detector with and without the RF coil in place, serving as a standard of reference measurement. The overall PET/MR imaging performance and PET quantification accuracy of the new 16-channel RF coil and its AC were then evaluated in first clinical examinations on ten patients with local breast cancer. Results: The RF breast array coil provides excellent signal-to-noise ratio and signal homogeneity across the volume of the breast phantoms in MR imaging and visualizes small structures in the phantoms down to 0.4 mm in plane. Difference measurements with PET revealed a global loss and thus attenuation of counts by 13% (mean value across the whole phantom volume) when the RF coil is placed in the PET detector. Local attenuation ranging from 0% in the middle of the phantoms up to 24% was detected in the peripheral regions of the phantoms at positions closer to attenuating hardware structures of the RF coil. The position accuracy of the RF coil on the patient table when using the positioning frame was determined well below 1 mm for all three spatial dimensions. This ensures perfect position match between the RF coil and its three-dimensional attenuation template during the PET data reconstruction process. When applying the CT-based AC of the RF coil, the global attenuation bias was mostly compensated to ±0.5% across the entire breast imaging volume. The patient study revealed high quality MR, PET, and combined PET/MR imaging of breast cancer. Quantitative activity measurements in all 11 breast cancer lesions of the ten patients resulted in increased mean difference values of SUV{sub max} 11.8% (minimum 3.2%; maximum 23.2%) between nonAC images and images when AC of the RF breast coil was applied. This supports the quantitative results of the phantom study as well as successful attenuation correction of the RF coil. Conclusions: A 16-channel breast RF coil was designed for optimized MR imaging performance and PET transparency and was successfully integrated with its dedicated attenuation correction template into a whole-body PET/MR system. Systematic PET/MR imaging evaluation with phantoms and an initial study on patients with breast cancer provided excellent MR and PET image quality and accurate PET quantification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Profile Images and Annotations for Vehicle Re-identification Algorithms (PRIMAVERA)

This dataset contains 636,246 profile images of vehicles representing 13,963 unique vehicles. The data was collected by a set of roadside sensors over the course of three years. Each time a vehicle passed by one of the sensors, a series of images was collected. The images were processed to detect and localize each vehicle, and a license plate reader collocated with the sensor was used to provide a unique ID for the vehicle. Actual license plate numbers have been obfuscated by replacing with an arbitrary numerical ID for each vehicle. After localizing the vehicle in each image, the original RGB image was rotated, scaled, and shifted to produce a new RGB image of size 234x234 pixels such that the outermost two wheels are located at predetermined pixel locations in the image. In this way, all vehicle images are aligned to one another. This registration process occasionally results in a portion of certain vehicles being cutoff at the edges of the image. The dataset has been partitioned into two sets called training and validation. The two partitions no common vehicles, i.e., a vehicle present in one partition is guaranteed not to be present in the other. In this way, an algorithm can be validated against a set of new vehicles that were not seen during the training process. The training set contains 543,926 images from 64,440 vehicle passes representing 11,918 unique vehicles, while the validation set contains 92,320 images from 10,991 vehicle passes representing 2,045 unique vehicles. Vehicle images are organized by directories corresponding to unique vehicles. The file naming scheme is as follows: veh_{vehID}_tr_{passID}_{frameID}_{elevation}_{timeofday}.jpg where {vehID} is the vehicle ID (unique across the entire dataset), {passID} is an identifier for each tracked vehicle pass (unique across the entire dataset), {frameID} is the index of the frame within the given vehicle pass starting at 0, {elevation} is a two-letter string indicating whether the sensor was elevated (el) or at ground-level (gl), and {timeofday} is a two-letter string indicating whether the image was captured during daytime (dt) or nighttime (nt).

image↗
DOE OSTI2014

Development of Automated Software Program for the Analysis of Alzheimer's Disease Scans: Evaluation of PET imaging with PBR-111 in HV and AD subjects

Study goal: A Phase 1 evaluation of the kinetics, clearance and cerebral distribution of one novel peripheral benzodiazepine receptors(PBR)positron emission tomography (PET) imaging agent, 18F-PBR-111 following intravenous administration in healthy volunteers and Alzheimer's disease (AD) patients. Short title: Evaluation of PET imaging with PBR-111 in HV and AD subjects Proof of Mechanism. Primary Objective: To evaluate the cerebral distribution of PBR-111 positron emission tomography (PET) for detection/exclusion of microglial activation in patients with Alzheimer's disease subjects compared to healthy volunteers. Secondary objectives: - To assess the dynamic uptake and washout of [18F]PBR-111, a potential imaging bio-marker for inflammatory changes in brain, using positron emission tomography in subjects with Alzheimer's disease (AD) and healthy volunteers (HV). - To perform blood metabolite characterization of [18F]PBR-111 in subjects with AD and HV to determine the nature of metabolites in assessment of [18F]-PBR-111 as a PET brain imaging agent. Name of radioactive drug substance: PBR-111 Dose(s): The applied PBR-111 radioactive dose will be up to 5.0 mCi, diluted in a maximum of 10 ml of saline. The radioligand will be administered as a slow intravenous bolus injection (i.e., 6 sec/ml) into a large vein (e.g., antecubital vein). Route of administration: Intravenous injection Duration of treatment: Single administration of a diagnostic agent Indication: PBR-111 positron emission tomography (PET) imaging has the potential to detect microglial activation. In the presence of PBR-111 uptake (representative of microglial activation), inflammation in the brain can be detected. Diagnosis and main criteria for inclusion: Study participants will be HVs and patients diagnosed with probable AD. HVs must be 18 years of age (at least four subjects 50 years of age) and have no evidence of cognitive impairment or other neurologic disease by medical history. The lack of cognitive impairment will also be based on a Clinical Dementia Rating (CDR) of 0. Patients with probable AD must be 50 years of age and must fulfill the National Institute of Neurological and Communicative Disorders and Stroke, Alzheimer's Disease and Related Disorders Association [NINCDS-ADRDA] criteria for probable AD. The CDR score must be 1.0 and 2.0 and have a modified Hachinski of 4. All HVs and all patients with probable AD must be able to comply with all study procedures. Study design: This is a Phase 1, open-label, single-center, non-randomized single dose study to assess the kinetics, clearance and cerebral distribution of PBR-111 PET imaging in detecting microglial activation in the brain in patients with probable AD compared to HVs. All aspects related to image acquisition, processing, and visual as well as quantitative evaluation will be developed, optimized, and validated (where required). Each subject will be required to visit the study center during the screening phase and on the PBR-111 PET imaging day (baseline). A telephone follow-up visit will be performed 7 days (± 3 days) after PBR-111 PET administration. At the screening visit, each subject (or caregiver in the case of AD subjects) will be asked to provide written informed consent or assent. During the screening phase (maximum duration of 60 days) subject medical, neurological, and surgical history, clinical assessments, and a neuro-psychiatric evaluation will be performed on all eligible subjects. Subjects will be allowed to leave the center after all evaluations have been completed. During this period an MRI of the brain will be performed during the screening period. If an MRI of the brain has been performed within six months of the imaging visit using the methods described in the protocol, and there has been no medically significant events in the interim, the previous MRI may be used. During the PBR-111 PET imaging day, all subjects will receive a single intravenous injection of PBR-111 and scanning will be performed over a 3.5 hour period. Each subject will have a telephone follow-up 7 days (± 3 days) thereafter to assess for adverse events. Methodology: - Assessments to provide clinical characterization of the AD subjects will be performed. - After administration of PBR-111, images will be generated with state-of-the-art PET imaging. Images will be assessed quantitatively for the presence of microglial activation by a nuclear physician blinded to clinical data. - Total radioactivity and estimation of the fraction of radioactivity associated to the un-metabolized tracer will be determined. In addition, the metabolite patterns of PBR-111 are determined in venous plasma and arterial samples based on high-performance liquid chromatography (HPLC) analyses. - Arterial sampling will be acquired in the initial two AD and two HV subjects and modeling will be assessed to determine if additional arterial sampling is necessary.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum ghost imaging microscopy depth-of-field study

Quantum ghost imaging approaches have been proposed to enhance biological microscopy, for example, using 2D visible detectors to provide IR images or providing additional dimensions of spatial or spectral information. Toward the goal of making such imaging schemes practical, we compare image quality and depth-of-field between traditional images and ghost images at the same excitation levels. We measure how image quality and depth-of-field depend on the parameters of the entangled light produced using type-I spontaneous parametric down-conversion (SPDC). We use a pair of time-synchronized, photon-timing single-photon avalanche diode (SPAD) array detectors to capture two distinct microscope imaging paths simultaneously on a photon-pair-by-photon-pair basis: one in a traditional imaging pathway and the other a quantum ghost imaging pathway. We calculate the depth-of-field, resolution, contrast, and signal-to-noise ratio (SNR) through the parameter space of a β-Barium Borate (BBO) type-I bulk non-linear crystal length and angle. Our results provide a basis for choosing parameters for quantum ghost imaging with type-I SPDC sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Data-driven high-fidelity 2D microstructure reconstruction via non-local patch-based image inpainting

Microstructure reconstruction problems are usually limited to the representation with finitely many number of phases, e.g. binary and ternary. However, images of microstructure obtained through experimental, for example, using microscope, are often represented as a RGB or grayscale image. Because the phase-based representation is discrete, more rigid, and provides less flexibility in modeling the microstructure, as compared to RGB or grayscale image, there is a loss of information in the conversion. In this paper, a microstructure reconstruction method, which produces images at the fidelity of experimental microscopy, i.e. RGB or grayscale image, is proposed without introducing any physics-based microstructure descriptor. Furthermore, the image texture is preserved and the microstructure image is represented with continuous variables (as in RGB or grayscale images), instead of binary or categorical variables, which results in a high-fidelity image of microstructure reconstruction. The advantage of the proposed method is its quality of reconstruction, which can be applied to any other binary or multiphase 2D microstructure. The proposed method can be thought of as a subsampling approach to expand the microstructure dataset, while preserving its image texture. Moreover, the size of the reconstructed image is more flexible, compared to other machine learning microstructure reconstruction method, where the size must be fixed beforehand. In addition, the proposed method is capable of joining the microstructure images taken at different locations to reconstruct a larger microstructure image. A significant advantage of the proposed method is to remedy the data scarcity problem in materials science, where experimental data is scare and hard to obtain. The proposed method can also be applied to generate statistically equivalent microstructures, which has a strong implication in microstructure-related uncertainty quantification applications. The proposed microstructure reconstruction method is demonstrated with the UltraHigh Carbon Steel micrograph DataBase (UHCSDB).

97 MATHEMATICS AND COMPUTING↗