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

Title: SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

Abstract

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 identifies 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 possessingmore » 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

Authors:
; ; ; ;  [1]
  1. UCLA Radiological Sciences, Los Angeles, CA (United States)
Publication Date:
OSTI Identifier:
22649306
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:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; BIOMEDICAL RADIOGRAPHY; CLINICAL TRIALS; IMAGES; PERFORMANCE; PHANTOMS

Citation Formats

Wahi-Anwar, M, Lo, P, Kim, H, Brown, M, and McNitt-Gray, M. SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials. United States: N. p., 2016. Web. doi:10.1118/1.4956942.
Wahi-Anwar, M, Lo, P, Kim, H, Brown, M, & McNitt-Gray, M. SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials. United States. doi:10.1118/1.4956942.
Wahi-Anwar, M, Lo, P, Kim, H, Brown, M, and McNitt-Gray, M. 2016. "SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials". United States. doi:10.1118/1.4956942.
@article{osti_22649306,
title = {SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials},
author = {Wahi-Anwar, M and Lo, P and Kim, H and Brown, M and McNitt-Gray, M},
abstractNote = {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 identifies 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.},
doi = {10.1118/1.4956942},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • The medical linear accelerator (linac) integrated with a kilovoltage (kV) flat-panel imager has been emerging as an important piece of equipment for image-guided radiation therapy. Due to the sagging of the linac head and the flexing of the robotic arms that mount the x-ray tube and flat-panel detector, geometric nonidealities generally exist in the imaging geometry no matter whether it is for the two-dimensional projection image or three-dimensional cone-beam computed tomography. Normally, the geometric parameters are established during the commissioning and incorporated in correction software in respective image formation or reconstruction. A prudent use of an on-board imaging system necessitatesmore » a routine surveillance of the geometric accuracy of the system like the position of the x-ray source, imager position and orientation, isocenter, rotation trajectory, and source-to-imager distance. Here we describe a purposely built phantom and a data analysis software for monitoring these important parameters of the system in an efficient and automated way. The developed tool works equally well for the megavoltage (MV) electronic portal imaging device and hence allows us to measure the coincidence of the isocenters of the MV and kV beams of the linac. This QA tool can detect an angular uncertainty of 0.1 deg. of the x-ray source. For spatial uncertainties, such as the source position, the imager position, or the kV/MV isocenter misalignment, the demonstrated accuracy of this tool was better than 1.6 mm. The developed tool provides us with a simple, robust, and objective way to probe and monitor the geometric status of an imaging system in a fully automatic process and facilitate routine QA workflow in a clinic.« less
  • Purpose: To create an accurate map of the distribution of radiation dose deposition in healthy and target tissues during radionuclide therapy.Methods: Serial quantitative SPECT/CT images were acquired at 4, 24, and 72 h for 28 {sup 177}Lu-octreotate peptide receptor radionuclide therapy (PRRT) administrations in 17 patients with advanced neuroendocrine tumors. Deformable image registration was combined with an in-house programming algorithm to interpolate pharmacokinetic uptake and clearance at a voxel level. The resultant cumulated activity image series are comprised of values representing the total number of decays within each voxel's volume. For PRRT, cumulated activity was translated to absorbed dose basedmore » on Monte Carlo-determined voxel S-values at a combination of long and short ranges. These dosimetric image sets were compared for mean radiation absorbed dose to at-risk organs using a conventional MIRD protocol (OLINDA 1.1).Results: Absorbed dose values to solid organs (liver, kidneys, and spleen) were within 10% using both techniques. Dose estimates to marrow were greater using the voxelized protocol, attributed to the software incorporating crossfire effect from nearby tumor volumes.Conclusions: The technique presented offers an efficient, automated tool for PRRT dosimetry based on serial post-therapy imaging. Following retrospective analysis, this method of high-resolution dosimetry may allow physicians to prescribe activity based on required dose to tumor volume or radiation limits to healthy tissue in individual patients.« less
  • Purpose: To assess dose delivery accuracy to clinically significant points in a realistic patient geometry for two separate pelvic radiotherapy scenarios. Methods: An inhomogeneous pelvic phantom was transported to 36 radiotherapy centers in Australia and New Zealand. The phantom was treated according to Phase III rectal and prostate trial protocols. Point dose measurements were made with thermoluminescent dosimeters (TLDs) and an ionisation chamber. Comprehensive site-demographic, treatment planning, and physical data were collected for correlation with measurement outcomes. Results: Dose delivery to the prescription point for the rectal treatment was consistent with planned dose (mean difference between planned and measured dosemore » - 0.1 {+-} 0.3% std err). Dose delivery in the region of the sacral hollow was consistently higher than planned (+1.2 {+-} 0.2%). For the prostate treatment, dose delivery to the prostate volume was consistent with planned doses (-0.49 {+-} 0.2%) and planned dose uniformity, though with a tendency to underdose the PTV at the prostate-rectal border. Measured out-of-field doses were significantly higher than planned. Conclusions: A phantom based on realistic anatomy and heterogeneity can be used to comprehensively assess the influence of multiple aspects of the radiotherapy treatment process on dose delivery. The ability to verify dose delivery for two trials with a single phantom was advantageous.« less
  • Purpose: Report on implementation of a Virtual EPID Standard Phantom Audit (VESPA) for IMRT to support credentialing of facilities for clinical trials. Data is acquired by local facility staff and transferred electronically. Analysis is performed centrally. Methods: VESPA is based on published methods and a clinically established IMRT QA procedure, here extended to multi-vendor equipment. Facilities, provided with web-based comprehensive instructions and CT datasets, create IMRT treatment plans. They deliver the treatments directly to their EPID without phantom or couch in the beam. They also deliver a set of simple calibration fields. Collected EPID images are uploaded electronically. In themore » analysis, the dose is projected back into a virtual phantom and 3D gamma analysis is performed. 2D dose planes and linear dose profiles can be analysed when needed for clarification. Results: Pilot facilities covering a range of planning and delivery systems have performed data acquisition and upload successfully. Analysis showed agreement comparable to local experience with the method. Advantages of VESPA are (1) fast turnaround mainly driven by the facility’s capability to provide the requested EPID images, (2) the possibility for facilities performing the audit in parallel, as there is no need to wait for a phantom, (3) simple and efficient credentialing for international facilities, (4) a large set of data points, and (5) a reduced impact on resources and environment as there is no need to transport heavy phantoms or audit staff. Limitations of the current implementation of VESPA for trials credentialing are that it does not provide absolute dosimetry, therefore a Level 1 audit still required, and that it relies on correctly delivered open calibration fields, which are used for system calibration. Conclusion: The implemented EPID based IMRT audit system promises to dramatically improve credentialing efficiency for clinical trials and wider applications. VESPA for VMAT will follow soon.« less
  • The goal of the study was to evaluate the first CR digital mammography system ( registered Konica-Minolta) in Mexico in clinical routine for cancer detection in a screening population and to determine if high resolution CR digital imaging is equivalent to state-of-the-art screen-film imaging. The mammograms were evaluated by two observers with cytological or histological confirmation for BIRADS 3, 4 and 5. Contrast, exposure and artifacts of the images were evaluated. Different details like skin, retromamillary space and parenchymal structures were judged. The detectability of microcalcifications and lesions were compared and correlated to histology. The difference in sensitivity of CRmore » Mammography (CRM) and Screen Film Mammography (SFM) was not statistically significant. However, CRM had a significantly lower recall rate, and the lesion detection was equal or superior to conventional images. There is no significant difference in the number of microcalcifications and highly suspicious calcifications were equally detected on both film-screen and digital images. Different anatomical regions were better detectable in digital than in conventional mammography.« less