2019 AAPM Annual Meeting
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Session Title: Session in Memory of Karl Prado: Recent Advancements in Quality Assurance for Radiation Therapy
Question 1: Compared with the conventional manual QA processes, which of the following descriptions about autonomous QA processes is correct:
Reference:Gilmer Valdes, Olivier Morin, Yanisley Valenciaga, Niel Kirby, Jean Pouliot, Cynthia Chuang: Use of TrueBeam developer mode for imaging QA, Journal of Applied Clinical Medical Physics, 16 (4), 322-333(2015)
Choice A:More efficient, but less accurate
Choice B:More efficient, but complicated and unstable
Choice C:More efficient, more stable and accurate
Choice D:Less efficient, but more stable and accurate
Question 2: Typically, an autonomous QA process includes:
Reference:Cesare H Jenkins, Dominik J Naczynski, Shu-Jung S Yu, Yong Yang and Lei Xing, Automating quality assurance of digital linear accelerators using a radioluminescent phosphor coated phantom and optical imaging, Phys. Med. Biol. 61, L29-L37 (2016)
Choice A:Automatic data acquisition
Choice B:Automatic data processing
Choice C:Automatic analysis and reporting
Choice D:All of the above
Question 3: Which statement is true about why machine learning methods are useful in physics QA?
Reference:Baozhou Sun, Dao Lam, Deshan Yang, Kevin Grantham, Tiezhi Zhang, Sasa Mutic, Tianyu Zhao, A machine learning approach to the accurate prediction of monitor units for a compact proton machine, Medical Physics, March 2018
Choice A:To predict physics QA passing rates, machine learning methods could be more accurate than the conventional methods (i.e. multi-variable linear fitting).
Choice B:For detecting errors in the patient treatment plan parameters, the machine learning models can detect more errors than conventional rule-based error detection methods.
Choice C:Both A and B are true.
Question 4: Select the best machine learning method for extracting knowledge (for example, lung + IMRT -> prescription = 60 Gy) from patient datasets.
Reference:Altaf et al., Applications of association rule mining in health informatics: a survey, Journal Artificial Intelligence Review, vol 47 Issue 3, March 2017
Choice A:Bayesian network
Choice B:Association rules
Choice C:Decision trees
Choice D:Artificial neural networks
Question 5: Which QA data storage method is best suited for future data analysis, mining, and sharing?
Reference:M.Y.Y. Law, B. Liu, L.W. Chan, Informatics in Radiology—DICOM-RT based electronic patient record information system for radiation therapy, Radiographics, 29 (2009), pp. 961–972
Choice A:Portable document format (PDF)
Choice B:Database
Choice C:Excel spreadsheets
Choice D:Paper
Question 6: What benefit does QA protocol standardization provide?
Reference:Santanam, L. et al. Standardizing naming conventions in radiation oncology. Int. J. Radiat. Oncol. Biol. Phys. 83, 1344–1349 (2012)
Choice A:Improved communication between multiple clinics
Choice B:Ensures that efficient QA procedures are being used
Choice C:Improves data analysis
Choice D:All of the above
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