| Question 1: Which QA data storage method is best 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 2: 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 above |
| Question 3: What is a folksonomy? |
| Reference: | Pink, Daniel H. (11 December 2005). "Folksonomy". New York Times. Retrieved 14 July 2009 |
| Choice A: | A user generated way of classifying items |
| Choice B: | A classification method that is controlled by a certain group |
| Choice C: | A type of hippie commune |
| Choice D: | All above |
| Question 4: There is a Hierarchy of Effectiveness with respect to error mitigation strategies. Automation is considered to be a technology-focused and effective technique. Another effective technology solution is: |
| Reference: | The challenge of maximizing safety in
radiation oncology, LB Marks, M Jackson, L Xie, SX Chang, KD Burkhardt, L Mazur, EL Jones, P Aponaro, D LaChapelle, DC Baynes, and RD Adams, Practical Radiation Oncology, 1, 2-14, 2011.
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| Choice A: | Use of a checklist in a treatment management system |
| Choice B: | Adding electronic alerts and reminders that users should do something |
| Choice C: | Use of forcing function such that plans can only be treated if properly approved |
| Choice D: | Training of all staff on how to use the treatment planning system |
| Question 5: Common error pathways were analyzed from high priority data submitted to the Radiation Oncology – Incident Learning System (RO-ILS). One of the largest fault areas is “wrong shift instructions given to therapists”. The data were analyzed with |
| Reference: | Common error pathways seen in the RO-ILS data that demonstrate opportunities for improving treatment safety, G Ezzell, B Chera, A Dicker, E Ford, L Potters, L Santanam, and S Weintraub, Practical Radiation Oncology, 8, pp 123-132, 2018. |
| Choice A: | A process map outlining all steps with and without errors |
| Choice B: | A fault tree analysis of the types of errors that occurred |
| Choice C: | A full failure mode analysis for all parts of the process |
| Choice D: | An analysis based on that submitted by each institution |
| Question 6: Automated treatment planning checks have been commissioned and clinically implemented to evaluate: |
| Reference: | Automating checks of plan check automation, T Halabi and H-M Lu, JACMP, JACMP 15, pp. 1-8, 2014
Improving treatment plan evaluation with automation, EL Covington, X Chen, KC Younge, C Lee, MM Matuszak, ML Kessler, W Keranen, E Acosta, AM Dougherty, SE Filpansick, and JM Moran, JACMP,17, pp 16-31, 2016. |
| Choice A: | Concordance of prescription and plan doses |
| Choice B: | Match anatomy for patient on-treatment imaging decisions |
| Choice C: | Best placement of isocenter |
| Choice D: | Best treatment planning approach (3D, IMRT, VMAT) |
| Question 7: Automated treatment planning tools have been demonstrated to: |
| Reference: | Automated IMRT planning in Pinnacle: A study in head-and-neck cancer. Strahlentherapy Onkologie, 193: 1031-1038, 2017. |
| Choice A: | Determine beam arrangement and beam shapes only |
| Choice B: | Save planning time only |
| Choice C: | Save planning time and improve quality |
| Choice D: | Allow physicians to do their own planning and quality checks |
| Question 8: Compared with the conventional programing and statistics, which of the following descriptions about artificial intelligence and machine learning is correct: |
| Reference: | Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2. |
| Choice A: | Requires prior assumptions about the underlying relationships between the variables |
| Choice B: | Can self-learn and improve from data without relying on rules-based programming |
| Choice C: | Functionality is formed by previous defined algorithms |
| Choice D: | Is about sample, population and hypothesis |
| Question 9: A complete automatic QA process for precision radiation therapy should include: |
| 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 analysis |
| Choice C: | Automatic reporting and storing |
| Choice D: | All above |
| Question 10: The advantages of machine learning based patient specific QA process include: |
| Reference: | G. Valdes, R. Scheuermann, et al. A mathematical framework for virtual IMRT QA using machine learning. Medical Physics. 43(7) 4323-34. 2016. |
| Choice A: | Can analyze the correlation between complexity metrics and passing rates |
| Choice B: | Efficient at detecting clinically relevant errors |
| Choice C: | Allows the identification and troubleshooting of different sources of error |
| Choice D: | All above |
