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Title: SU-G-206-17: RadShield: Semi-Automated Shielding Design for CT Using NCRP 147 and Isodose Curves

Abstract

Purpose: Computed tomography (CT) exam rooms are shielded more quickly and accurately compared to manual calculations using RadShield, a semi-automated diagnostic shielding software package. Last year, we presented RadShield’s approach to shielding radiographic and fluoroscopic rooms calculating air kerma rate and barrier thickness at many points on the floor plan and reporting the maximum values for each barrier. RadShield has now been expanded to include CT shielding design using not only NCRP 147 methodology but also by overlaying vendor provided isodose curves onto the floor plan. Methods: The floor plan image is imported onto the RadShield workspace to serve as a template for drawing barriers, occupied regions and CT locations. SubGUIs are used to set design goals, occupancy factors, workload, and overlay isodose curve files. CTDI and DLP methods are solved following NCRP 147. RadShield’s isodose curve method employs radial scanning to extract data point sets to fit kerma to a generalized power law equation of the form K(r) = ar^b. RadShield’s semiautomated shielding recommendations were compared against a board certified medical physicist’s design using dose length product (DLP) and isodose curves. Results: The percentage error found between the physicist’s manual calculation and RadShield’s semi-automated calculation of lead barrier thicknessmore » was 3.42% and 21.17% for the DLP and isodose curve methods, respectively. The medical physicist’s selection of calculation points for recommending lead thickness was roughly the same as those found by RadShield for the DLP method but differed greatly using the isodose method. Conclusion: RadShield improves accuracy in calculating air-kerma rate and barrier thickness over manual calculations using isodose curves. Isodose curves were less intuitive and more prone to error for the physicist than inverse square methods. RadShield can now perform shielding design calculations for general scattering bodies for which isodose curves are provided.« less

Authors:
;  [1];  [2];  [3]
  1. University of Oklahoma Health Science Center, Oklahoma City, OK (United States)
  2. Massachusetts General Hospital, Boston, MA (United States)
  3. The University of Oklahoma Health Sciences Center, Oklahoma City, OK (United States)
Publication Date:
OSTI Identifier:
22649316
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; COMPUTER CODES; COMPUTERIZED TOMOGRAPHY; DESIGN; DIFFUSION BARRIERS; ISODOSE CURVES; MANUALS; SHIELDING; THICKNESS

Citation Formats

DeLorenzo, M, Rutel, I, Yang, K, and Wu, D. SU-G-206-17: RadShield: Semi-Automated Shielding Design for CT Using NCRP 147 and Isodose Curves. United States: N. p., 2016. Web. doi:10.1118/1.4956958.
DeLorenzo, M, Rutel, I, Yang, K, & Wu, D. SU-G-206-17: RadShield: Semi-Automated Shielding Design for CT Using NCRP 147 and Isodose Curves. United States. doi:10.1118/1.4956958.
DeLorenzo, M, Rutel, I, Yang, K, and Wu, D. Wed . "SU-G-206-17: RadShield: Semi-Automated Shielding Design for CT Using NCRP 147 and Isodose Curves". United States. doi:10.1118/1.4956958.
@article{osti_22649316,
title = {SU-G-206-17: RadShield: Semi-Automated Shielding Design for CT Using NCRP 147 and Isodose Curves},
author = {DeLorenzo, M and Rutel, I and Yang, K and Wu, D},
abstractNote = {Purpose: Computed tomography (CT) exam rooms are shielded more quickly and accurately compared to manual calculations using RadShield, a semi-automated diagnostic shielding software package. Last year, we presented RadShield’s approach to shielding radiographic and fluoroscopic rooms calculating air kerma rate and barrier thickness at many points on the floor plan and reporting the maximum values for each barrier. RadShield has now been expanded to include CT shielding design using not only NCRP 147 methodology but also by overlaying vendor provided isodose curves onto the floor plan. Methods: The floor plan image is imported onto the RadShield workspace to serve as a template for drawing barriers, occupied regions and CT locations. SubGUIs are used to set design goals, occupancy factors, workload, and overlay isodose curve files. CTDI and DLP methods are solved following NCRP 147. RadShield’s isodose curve method employs radial scanning to extract data point sets to fit kerma to a generalized power law equation of the form K(r) = ar^b. RadShield’s semiautomated shielding recommendations were compared against a board certified medical physicist’s design using dose length product (DLP) and isodose curves. Results: The percentage error found between the physicist’s manual calculation and RadShield’s semi-automated calculation of lead barrier thickness was 3.42% and 21.17% for the DLP and isodose curve methods, respectively. The medical physicist’s selection of calculation points for recommending lead thickness was roughly the same as those found by RadShield for the DLP method but differed greatly using the isodose method. Conclusion: RadShield improves accuracy in calculating air-kerma rate and barrier thickness over manual calculations using isodose curves. Isodose curves were less intuitive and more prone to error for the physicist than inverse square methods. RadShield can now perform shielding design calculations for general scattering bodies for which isodose curves are provided.},
doi = {10.1118/1.4956958},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: Computed tomography (CT) exam rooms are shielded more quickly and accurately compared to manual calculations using RadShield, a semi-automated diagnostic shielding software package. Last year, we presented RadShield’s approach to shielding radiographic and fluoroscopic rooms calculating air kerma rate and barrier thickness at many points on the floor plan and reporting the maximum values for each barrier. RadShield has now been expanded to include CT shielding design using not only NCRP 147 methodology but also by overlaying vendor provided isodose curves onto the floor plan. Methods: The floor plan image is imported onto the RadShield workspace to serve asmore » a template for drawing barriers, occupied regions and CT locations. SubGUIs are used to set design goals, occupancy factors, workload, and overlay isodose curve files. CTDI and DLP methods are solved following NCRP 147. RadShield’s isodose curve method employs radial scanning to extract data point sets to fit kerma to a generalized power law equation of the form K(r) = ar^b. RadShield’s semi-automated shielding recommendations were compared against a board certified medical physicist’s design using dose length product (DLP) and isodose curves. Results: The percentage error found between the physicist’s manual calculation and RadShield’s semi-automated calculation of lead barrier thickness was 3.42% and 21.17% for the DLP and isodose curve methods, respectively. The medical physicist’s selection of calculation points for recommending lead thickness was roughly the same as those found by RadShield for the DLP method but differed greatly using the isodose method. Conclusion: RadShield improves accuracy in calculating air-kerma rate and barrier thickness over manual calculations using isodose curves. Isodose curves were less intuitive and more prone to error for the physicist than inverse square methods. RadShield can now perform shielding design calculations for general scattering bodies for which isodose curves are provided.« less
  • Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifiesmore » the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.« less
  • The recently published Report No. 147 of The National Council on Radiation Protection and Measurements entitled 'Structural shielding design for medical x-ray imaging facilities' provides an update of shielding recommendations for x rays used for medical imaging. The goal of this report is to ensure that the shielding in these facilities limits radiation exposures to employees and members of the public to acceptable levels. Board certified medical and health physicists, as defined in this report, are the 'qualified experts' who are competent to design radiation shielding for these facilities. As such, physicists must be aware of the new technical informationmore » and the changes from previous reports that Report No. 147 supersedes. In this article we summarize the new data, models and recommendations for the design of radiation barriers in medical imaging facilities that are presented in Report No. 147.« less
  • Purpose: To quantify a radiology team’s assessment of image quality differences between two CT scanner models currently in clinical use, with emphasis on spatial resolution that could be impacted by focal spot size. Methods: Modulation Transfer Functions (MTF) measurements were performed by scanning the impulse source insert module of the Catphan 600 at 120/140 kVp with both large (LFS) and small (SFS) focal spots and reconstructed to 2.5mm and 5.0mm thicknesses on a GE Discovery CT750 HD and a LightSpeed VCT CT scanner. MTFs were calculated by summing the 2D PSF along one-dimension to obtain line-spread-function (LSF), and calculating themore » Fourier Transform of the zero-padded and background corrected LSF. Spatial resolution performance was evaluated by comparing MTF curves, 50% and 10% MTF cutoff, and total area under the MTF curve (AUC). In addition, images of the Catphan high-contrast module and a Kagaku anthropomorphic body phantom were acquired from the HD scanner for visual comparisons. Results: For each scanner model, SFS was superior to LFS spatial resolution with respect to 50%/10% MTF cutoff and AUC. For the HD, 50%/10% cutoff was 4.29/7.22cm-1 for the LFS and 4.43/7.45cm-1 for the SFS. VCT outperformed HD, with 50%/10% cutoff of 4.40/7.29 cm-1 for LFS and 4.62/7.47cm-1 for SFS. Scanner model performance in order of decreasing AUC performance was VCT SFS (7.43), HD SFS (7.20), VCT LFS (7.09) and HD LFS (6.93). Visual evaluations of Kagaku phantom images confirmed that VCT outperformed HD. Conclusion: VCT outperformed HD and small focal spot is desired for either model over large focal spot in term of spatial resolution – in agreement with radiologist feedback of overall image quality. In-depth evaluations of clinical impact and focal spot selection mechanisms is currently being assessed.« less
  • Purpose: The purpose of this study was to: 1) compare scanners output by measuring normalized CTDIw (mGy/100mAs) in different CT makes and models and at different kV’s, and 2) quantify the relationship between kV and CTDI and compare this relationship between the different manufacturers. Methods: Study included forty scanners of major CT manufacturers and of various models. Exposure was measured at center and 12 o’clock holes of head and body CTDI phantoms, at all available kV’s, and with the largest or second largest available collimation in each scanner. Average measured CTDI’s from each CT manufacturer were also plotted against kVmore » and the fitting equation: CTDIw (normalized) = a.kVb was calculated. The power (b) value may be considered as an indicator of spectral filtration, which affects the degree of beam hardening. Also, HVLs were measured at several scanners. Results: Results showed GE scanners, on average, had higher normalized CTDIw than those of Siemens and Philips, in both phantom sizes and at all kV’s. ANOVA statistic indicated the difference was statistically significant (p < 0.05). Comparison between Philips and Siemens, however, was not statistically significant. Curve fitting showed b values ranged from 2.4 to 2.9 (for Head periphery and center, respectively); and was about 2.8 for Body phantom periphery, and 3.2 at the center of Body phantom. Fitting equations (kV vs. CTDI) will be presented and discussed. GE’s CTDIw vs. HVL showed very strong correlation (r > 0.99). Conclusion: Partial characterization of scanners output was performed which may be helpful in dose estimation to internal organs. The relatively higher output from GE scanners may be attributed to lower filtration. Work is still in progress to obtain CTDI values from other scanners as well as to measure their HVLs.« less