skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: SU-E-I-02: Characterizing Low-Contrast Resolution for Non-Circular CBCT Trajectories

Abstract

Purpose: The use of non-circular scanning trajectories with optimization-basedreconstruction algorithms can be used in conjunction with non-planaracquisition geometries for axial field-of-view (FOV) extension incone-beam CT (CBCT). To evaluate the utility of these trajectories,quantitative image quality metrics should be evaluated. Low-contrastresolution (LCR) and CT number accuracy are significant challenges forCBCT. With unprecedented axial coverage provided by thesetrajectories, measuring such metrics throughout the axial range iscritical. There are currently no phantoms designed to measurelow-contrast resolution over such an extended volume. Methods: The CATPHAN (The Phantom Laboratory, Salem NY) is the current standardfor image quality evaluation. While providing several useful modulesfor different evaluation metrics, each module was designed to beevaluated in a single slice and not for comparison across axialpositions. To characterize the LCR and HU accuracy over an extendedaxial length, we have designed and built a phantom with evaluationmodules at multiple and adjustable axial positions. Results: The modules were made from a cast polyurethane resin. Holes rangingfrom 1/8 to 5/8 inch were added at a constant radius from the modulecenter into which rods of two different plastic materials were pressedto provide two nominal levels of contrast (1.0% and 0.5%). Largerholes were bored to accept various RMI plugs with known electrondensities for HUmore » accuracy evaluation. The modules can be inserted intoan acrylic tube long enough to cover the entire axial FOV and theirpositions adjusted to desired evaluation points. Conclusion: This phantom allows us to measure the LCR and HU accuracy across theaxial coverage within a single acquisition. These metrics can be usedto characterize the impact different trajectories and reconstructionparameters have on clinically relevant image quality performancemetrics. Funding was provided in part by Varian Medical Systems and NIH R01 Grants Nos. CA158446, CA182264, EB018102, and EB000225. The contents of this poster are solely the responsibility of the authors and do not necessarily represent the official view of any of the supporting organizations.« less

Authors:
; ;  [1];  [2]
  1. The University of Chicago, Chicago, IL (United States)
  2. The Princess Margaret Cancer Centre - UHN, Toronto, ON (Canada)
Publication Date:
OSTI Identifier:
22486709
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ACCURACY; COMPUTERIZED TOMOGRAPHY; DESIGN; IMAGES; PHANTOMS; POLYURETHANES; SPATIAL RESOLUTION

Citation Formats

Davis, A, Pan, X, Pelizzari, C, and Pearson, E. SU-E-I-02: Characterizing Low-Contrast Resolution for Non-Circular CBCT Trajectories. United States: N. p., 2015. Web. doi:10.1118/1.4923999.
Davis, A, Pan, X, Pelizzari, C, & Pearson, E. SU-E-I-02: Characterizing Low-Contrast Resolution for Non-Circular CBCT Trajectories. United States. doi:10.1118/1.4923999.
Davis, A, Pan, X, Pelizzari, C, and Pearson, E. Mon . "SU-E-I-02: Characterizing Low-Contrast Resolution for Non-Circular CBCT Trajectories". United States. doi:10.1118/1.4923999.
@article{osti_22486709,
title = {SU-E-I-02: Characterizing Low-Contrast Resolution for Non-Circular CBCT Trajectories},
author = {Davis, A and Pan, X and Pelizzari, C and Pearson, E},
abstractNote = {Purpose: The use of non-circular scanning trajectories with optimization-basedreconstruction algorithms can be used in conjunction with non-planaracquisition geometries for axial field-of-view (FOV) extension incone-beam CT (CBCT). To evaluate the utility of these trajectories,quantitative image quality metrics should be evaluated. Low-contrastresolution (LCR) and CT number accuracy are significant challenges forCBCT. With unprecedented axial coverage provided by thesetrajectories, measuring such metrics throughout the axial range iscritical. There are currently no phantoms designed to measurelow-contrast resolution over such an extended volume. Methods: The CATPHAN (The Phantom Laboratory, Salem NY) is the current standardfor image quality evaluation. While providing several useful modulesfor different evaluation metrics, each module was designed to beevaluated in a single slice and not for comparison across axialpositions. To characterize the LCR and HU accuracy over an extendedaxial length, we have designed and built a phantom with evaluationmodules at multiple and adjustable axial positions. Results: The modules were made from a cast polyurethane resin. Holes rangingfrom 1/8 to 5/8 inch were added at a constant radius from the modulecenter into which rods of two different plastic materials were pressedto provide two nominal levels of contrast (1.0% and 0.5%). Largerholes were bored to accept various RMI plugs with known electrondensities for HU accuracy evaluation. The modules can be inserted intoan acrylic tube long enough to cover the entire axial FOV and theirpositions adjusted to desired evaluation points. Conclusion: This phantom allows us to measure the LCR and HU accuracy across theaxial coverage within a single acquisition. These metrics can be usedto characterize the impact different trajectories and reconstructionparameters have on clinically relevant image quality performancemetrics. Funding was provided in part by Varian Medical Systems and NIH R01 Grants Nos. CA158446, CA182264, EB018102, and EB000225. The contents of this poster are solely the responsibility of the authors and do not necessarily represent the official view of any of the supporting organizations.},
doi = {10.1118/1.4923999},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}
  • Purpose: To introduce the Joint Commission's requirements for annual diagnostic physics testing of all nuclear medicine equipment, effective 7/1/2014, and to highlight an acceptable methodology for testing lowcontrast resolution of the nuclear medicine imaging system. Methods: The Joint Commission's required diagnostic physics evaluations are to be conducted for all of the image types produced clinically by each scanner. Other accrediting bodies, such as the ACR and the IAC, have similar imaging metrics, but do not emphasize testing low-contrast resolution as it relates clinically. The proposed method for testing low contrast resolution introduces quantitative metrics that are clinically relevant. The acquisitionmore » protocol and calculation of contrast levels will utilize a modified version of the protocol defined in AAPM Report #52. Results: Using the Rose criterion for lesion detection with a SNRpixel = 4.335 and a CNRlesion = 4, the minimum contrast levels for 25.4 mm and 31.8 mm cold spheres were calculated to be 0.317 and 0.283, respectively. These contrast levels are the minimum threshold that must be attained to guard against false positive lesion detection. Conclusion: Low contrast resolution, or detectability, can be properly tested in a manner that is clinically relevant by measuring the contrast level of cold spheres within a Jaszczak phantom using pixel values within ROI's placed in the background and cold sphere regions. The measured contrast levels are then compared to a minimum threshold calculated using the Rose criterion and a CNRlesion = 4. The measured contrast levels must either meet or exceed this minimum threshold to prove acceptable lesion detectability. This research and development activity was performed by the authors while employed at West Physics Consulting, LLC. It is presented with the consent of West Physics, which has authorized the dissemination of the information and/or techniques described in the work.« less
  • Purpose: We demonstrate a novel X-ray phase-contrast (XPC) method for lung imaging representing a paradigm shift in the way small animal functional imaging is performed. In our method, information regarding airway microstructure that is encoded within speckle texture of a single XPC radiograph is decoded to produce 2D parametric images that will spatially resolve changes in lung properties such as microstructure sizes and air volumes. Such information cannot be derived from conventional lung radiography or any other 2D imaging modality. By computing these images at different points within a breathing cycle, dynamic functional imaging will be readily achieved without themore » need for tomography. Methods: XPC mouse lung radiographs acquired in situ with an in-line X-ray phase contrast benchtop system. The lung air volume is varied and controlled with a small animal ventilator. XPC radiographs will be acquired for various lung air volume levels representing different phases of the respiratory cycle. Similar data will be acquired of microsphere-based lung phantoms containing hollow glass spheres with known distributions of diameters. Image texture analysis is applied to the data to investigate relationships between texture characteristics and airspace/microsphere physical properties. Results: Correlations between Fourier-based texture descriptors (FBTDs) and regional lung air volume indicate that the texture features in 2D radiographs reveal information on 3D properties of the lungs. For example, we find for a 350 × 350 πm2 lung ROI a linear relationship between injected air volume and FBTD value with slope and intercept of 8.9×10{sup 5} and 7.5, respectively. Conclusion: We demonstrate specific image texture measures related to lung speckle features are correlated with physical characteristics of refracting elements (i.e. lung air spaces). Furthermore, we present results indicating the feasibility of implementing the technique with a simple imaging system design, short exposures, and low dose which provides potential for widespread use in laboratory settings for in vivo studies. This research was supported in part by NSF Award CBET1263988.« less
  • Purpose: CARE kV is a tool that automatically recommends optimal kV setting for individual patient for specific CT examination. The use of CARE kV depends on topogram and the user-selected contrast behavior. CARE kV is expected to reduce radiation dose while improving image quality. However, this may work only for certain groups of patients and/or certain CT examinations. This study is to investigate the effects of CARE kV on radiation dose of non-contrast examination of CT abdomen/pelvis. Methods: Radiation dose (CTDIvol and DLP) from patients who underwent abdomen/pelvis non-contrast examination with and without CARE kV were retrospectively reviewed. All patientsmore » were scanned in the same scanner (Siemens Somatom AS64). To mitigate any possible influences due to technologists’ unfamiliarity with the CARE kV, the data with CARE kV were retrieved 1.5 years after the start of CARE kV usage. T-test was used for significant difference in radiation dose. Results: Volume CTDIs and DLPs from 18 patients before and 24 patients after the use of CARE kV were obtained in a duration of one month. There is a slight increase in both average CTDIvol and average DLP with CARE kV compared to those without CARE kV (25.52 mGy vs. 22.65 mGy for CTDIvol; 1265.81 mGy-cm vs. 1199.19 mGy-cm). Statistically there was no significant difference. Without CARE kV, 140 kV was used in 9 of 18 patients, while with CARE KV, 140 kV was used in 15 of 24 patients. 80kV was not used in either group. Conclusion: The use of CARE kV may save time for protocol optimization and minimize variability among technologists. Radiation dose reduction was not observed in non-contrast examinations of CT abdomen/pelvis. This was partially because our CT protocols were tailored according to patient size before CARE kV and partially because of large size patients.« less
  • Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions includedmore » two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.« less
  • Purpose: Tumors such as the prostate focal lesions and the brain metastases have extremely low CT contrast and MRI is usually used for target delineation. The target contours are propagated to the CT for treatment planning and patient positioning. We have employed an advanced denoising method eliminating the noise and allow magnification of subtle contrast of these focal lesions on CT. Methods: Five prostate and two brain metastasis patients with MRI T2, diffusion or dynamic contrast enhanced (DCE) images confirmed focal lesions were included. One brain patients had 5 metastases. A block matching 3D (BM3D) algorithm was adapted to reducemore » the noise of kVCT images used for treatment planning. The gray-level range of the resultant images was narrowed to magnify the tumor-normal tissue contrast. Results: For the prostate patients, denoised kVCT images showed focal regions at 5, 8,11-1, 2, and 8–10 oclock for the 5 patients, this is highly consistent to the radiologist confirmed focal lesions based on MRI at 5, 7, 11-1, 2 and 8–10 oclock in the axial plane. These CT focal regions matched well with the MRI focal lesions in the cranio-caudal position. The average increase in density compared to background prostate glands was 0.86%, which corresponds to ∼50% increase in cellularity and is lower than the average CT noise level of 2.4%. For the brain patients, denoised kVCT showed 5/6 metastases. The high CT-density region of a metastasis is 2-mm off from its corresponding elevated MRI perfusion center. Overall the detecting sensitivity was 91%. Conclusion: It has been preliminarily demonstrated that the higher tumor cellularity can be detected using kVCT. The low contrast-to-noise information requires advanced denoising to reveal. The finding is significant to radiotherapy by providing an additional tool to locate focal lesions for confirming MRI-CT registration and providing a highly accessible outcome assessment tool.« less