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Sci‐Thur AM: YIS – 08: Automated Imaging Quality Assurance for Image‐Guided Small Animal Irradiators
Author(s) -
Johnstone Chris,
BazalovaCarter Magdalena
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4961758
Subject(s) - imaging phantom , quality assurance , image quality , voxel , nuclear medicine , computer science , software , noise (video) , medical physics , computer vision , medicine , image (mathematics) , external quality assessment , pathology , programming language
Purpose: To develop quality assurance (QA) standards and tolerance levels for image quality of small animal irradiators. Methods: A fully automated in‐house QA software for image analysis of a commercial microCT phantom was created. Quantitative analyses of CT linearity, signal‐to‐noise ratio (SNR), uniformity and noise, geometric accuracy, modulation transfer function (MTF), and CT number evaluation was performed. Phantom microCT scans from seven institutions acquired with varying parameters (kVp, mA, time, voxel size, and frame rate) and five irradiator units (Xstrahl SARRP, PXI X‐RAD 225Cx, PXI X‐RAD SmART, GE explore CT/RT 140, and GE Explore CT 120) were analyzed. Multi‐institutional data sets were compared using our in‐house software to establish pass/fail criteria for each QA test. Results: CT linearity (R2>0.996) was excellent at all but Institution 2. Acceptable SNR (>35) and noise levels (<55HU) were obtained at four of the seven institutions, where failing scans were acquired with less than 120mAs. Acceptable MTF (>1.5 lp/mm for MTF=0.2) was obtained at all but Institution 6 due to the largest scan voxel size (0.35mm). The geometric accuracy passed (<1.5%) at five of the seven institutions. Conclusion: Our QA software can be used to rapidly perform quantitative imaging QA for small animal irradiators, accumulate results over time, and display possible changes in imaging functionality from its original performance and/or from the recommended tolerance levels. This tool will aid researchers in maintaining high image quality, enabling precise conformal dose delivery to small animals.