| Question 1: For lung tumors, simulations of full adapt (i.e. daily replanning) have shown that a single midtreatment adaptation achieves approximately what percentage of benefit (relative to full adapt) for target dose escalation and normal tissue sparing? |
| Reference: | Benefits of adaptive radiation therapy in lung cancer as a function of replanning frequency. Dial C, Weiss E, Siebers JV, Hugo GD. Med Phys. 2016 Apr;43(4):1787 |
| Choice A: | 10-25% |
| Choice B: | 30-45% |
| Choice C: | 50-65% |
| Choice D: | 80-95% |
| Question 2: How much treatment planning time savings has been shown to be possible when producing breast plans using an automated script vs. manual treatment planning approaches? |
| Reference: | Usefulness of EZFluence software for radiotherapy planning of breast cancer treatment. Yoder T, Hsia AT, Xu Z, Stessin A, Ryu S. Med Dosim. 2019 Jan 2. pii: S0958-3947(18)30137-7. doi: 10.1016/j.meddos.2018.12.001. [Epub ahead of print] |
| Choice A: | 25% |
| Choice B: | 45% |
| Choice C: | 65% |
| Choice D: | 85% |
| Question 3: Which of the following is not true regarding the use of checklist? |
| Reference: | B. Burian, A. Clebone, K. Dismukes, and K. Ruskin, “More Thank a Tick Box: Medical Checklists Development, Design, and Use†Anesthesia & Analgesia 2018;126(1):223-32 |
| Choice A: | They are an important safety feature that should be built into health care. |
| Choice B: | Increasing checklist items always results in improved safety. |
| Choice C: | Implementation of an automated system increases the reliability of a checklist. |
| Choice D: | Automated checklist allows time for greater investigation into variations. |
| Question 4: Automated Weekly Chart Checks removes the responsibility to perform weekly chart checks. |
| Reference: | SW. Hadley, ML Kessler, DW Litzenberg, C Lee, J Irrer, X Chen, E Acosta, G Weyburne, W Keranen, k Lam, E Covington, KC Younge, MM Matuszak, and JM Moran, “ SafetyNet: streamlining and automating QA in radiotherapy†Journal of Applied Clinical Medical Physics 2016;17(1):387-95 |
| Choice A: | True |
| Choice B: | False |
| Question 5: Which of the following are the main ways the Eclipse Scripting can be implemented? |
| Reference: | Varian Medical Systems. Eclipse Scripting API Reference Guide (P1021698-003-C). November 2017. Pages 31-32 |
| Choice A: | Plug-in single file |
| Choice B: | Plug-in binary |
| Choice C: | Stand-alone executable |
| Choice D: | A and B |
| Choice E: | A, B, and C |
| Question 6: What does the API provide that make it easy to locate an associated DICOM file associated to a series, image, or plan? |
| Reference: | Carden, R. (2018). Daemons: A tour through Varian’s DICOM API. In J. Pyyry & W. Keranen (Eds.), Varian APIs: A handbook for programming in the Varian oncology software ecosystem (pp.47-48) |
| Choice A: | Patient name |
| Choice B: | DICOM UIDs |
| Choice C: | Plan ID |
| Choice D: | DICOM tags |
| Choice E: | Series name |
| Question 7: Compared to manual treatment planning, which has been shown to be true for automated treatment planning? |
| Reference: | Kisling K et al. A risk assessment of automated treatment planning and recommendations for clinical deployment. Med Phys. 2019 Apr 19. doi: 10.1002/mp.13552.
Della Gala G et al. Fully automated VMAT treatment planning for advanced-stage NSCLC patients. Strahlenther Onkol. 2017 May;193(5):402-409.
Court LE et al. Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System. J Vis Exp. 2018 Apr 11;(134). doi: 10.3791/57411. |
| Choice A: | Treatment planning time reduced by 50% or more, physicians determine plans clinically acceptable for 50% or more, variability in planning approaches are substantially reduced. |
| Choice B: | Costs for automated planning are substantially higher than manual |
| Choice C: | Automated planning is only applicable for IMRT or VMAT |
| Choice D: | Automated planning eliminates need for dosimetrists, physicians and physicians to be involved in treatment planning. |
| Question 8: Which statement is true about automated planning solutions? |
| Reference: | Krayenbuehl J et al. Planning comparison of five automated treatment planning solutions for locally advanced head and neck cancer. Radiat Oncol. 2018 Sep 10;13(1):170. doi: 10.1186/s13014-018-1113-z.
Court LE et al. Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System. J Vis Exp. 2018 Apr 11;(134). doi: 10.3791/57411.
Della Gala G et al. Fully automated VMAT treatment planning for advanced-stage NSCLC patients. Strahlenther Onkol. 2017 May;193(5):402-409. |
| Choice A: | They have only been shown to work for a limited number of treatment planning systems |
| Choice B: | The approach is only applicable to targets without large concavities |
| Choice C: | Automated planning solutions do not work for sites where the dose distribution needs to be directed along a tangential axis e.g. breast |
| Choice D: | Automated planning has been shown to work for a broad range of planning systems, and target sites for 3D, VMAT and IMRT planning |
| Question 9: What currently is the primary limitation in achieving automated collision detection? |
| Reference: | Tsiakalos, MF, et al. “Graphical treatment simulation and automated collision detection for conformal and stereotactic radiotherapy treatment planning.†MedPhys 2001; 28(7): 1359-63. |
| Choice A: | Inaccuracy in machine hardware dimension modeling |
| Choice B: | Lack of precision detection and decision algorithm |
| Choice C: | Incomplete coverage of the CT over the entirety of the patient |
| Choice D: | Unwillingness of the physicists and therapists to trust the result of current detection algorithm |
| Choice E: | Difficulty in determining the exact location of the iso with respect to the patient and the hardwares (nozzle, table, and accessories) |
| Question 10: Which of the following is false: |
| Reference: | Wu, Binbin, et al. “Patient geometryâ€driven information retrieval for IMRT treatment plan quality control.†MedPhys 2009; 36(12): 5497-5505. |
| Choice A: | Past patient treatment plan data can be used to personalize the dosimetric quality metrics for a new patient. |
| Choice B: | The utility of past patient data to obtain personalized metrics is subject to the quality of treatment for prior patients. |
| Choice C: | Data driven models for quality continually improve with time with more patient data |
| Choice D: | None of the above |
