| Question 1: The reduction in the magnitude of the initial 3D correction vector for patient setup when using surface imaging as compared to three-point laser localization is best characterized by: |
| Reference: | Stanley DN, McConnel KA, Kirby N, et al. Comparison of initial patient setup accuracy between surface imaging and three point localization: A retrospective analysis. J Appl Clin Med Phys. 2017; 18(6): 58-61. |
| Choice A: | 10% |
| Choice B: | 25% |
| Choice C: | 50% |
| Choice D: | 75% |
| Question 2: The use of surface imaging as compared to kV orthogonal x-rays to set up postmastectomy chest wall patients showed a reduction in set up time of: |
| Reference: | Batin E, Depauw N, McDonald S, et al. Can surface imaging improve the patient setup for proton postmastectomy chest wall irradiation? Pract Radiat Oncol. 2016; 6(6):e235-241. |
| Choice A: | 10% |
| Choice B: | 25% |
| Choice C: | 50% |
| Choice D: | 75% |
| Question 3: Identify system combines radiofrequency identification (RFID), biometric authentication and surface matching technology. |
| Reference: | • AAPM 2017 annual meeting eposter, “Radiation therapy treatment deviations potentially prevented by a novel combined radio-frequency identification (RFID), biometric and surface matching technology”, Zhao H, etc. https://www.aapm.org/meetings/2017AM/PRAbs.asp?mid=127&aid=36270
• Hosiak and Pawlicki, “The Role of optical surface imaging systems in radiation therapy,” Semin RadiatOnco,28:185-193, 2018
|
| Choice A: | Biometric authentication (palm reader). |
| Choice B: | Radiofrequency identification (RFID). |
| Choice C: | Surface matching (SGRT). |
| Choice D: | All of the above. |
| Question 4: What percentage of machine related treatment deviations were found to be preventable by Identify system based on the study at University of Utah: |
| Reference: | • AAPM 2017 annual meeting eposter, “Radiation therapy treatment deviations potentially prevented by a novel combined radio-frequency identification (RFID), biometric and surface matching technology”, Zhao H, etc. https://www.aapm.org/meetings/2017AM/PRAbs.asp?mid=127&aid=36270
• Hosiak and Pawlicki, “The Role of optical surface imaging systems in radiation therapy,” Semin RadiatOnco,28:185-193, 2018.
|
| Choice A: | >25% |
| Choice B: | >50% |
| Choice C: | >75% |
| Choice D: | >90% |
| Question 5: The mean percent of overlap between a breast patient’s reference surface and their daily set up surfaces is: |
| Reference: | D.B. Wiant, Q. Verchick, P. Gates, et al., A novel method for radiotherapy patient identification using surface imaging, J. Appl. Clin. Med. Phys. 17(2), 271–278 (2016). |
| Choice A: | 15% |
| Choice B: | 33% |
| Choice C: | 65% |
| Choice D: | 83% |
| Question 6: What PTV margin would be needed for a breast treatment that lasts 15 minutes? |
| Reference: | D.B. Wiant, S. Wentworth, J.M. Maurer, C.L. Vanderstraeten, J.A. Terrell, and B.J. Sintay, Surface imaging-based analysis of intrafraction motion for breast radiotherapy patients, J. Appl. Clin. Med. Phys. 15(6), 4957 (2014). |
| Choice A: | 1 mm |
| Choice B: | 3 mm |
| Choice C: | 8 mm |
| Choice D: | 25 mm |
| Question 7: What is an important limitation of the current clinical surface imaging systems for real-time collision prediction/detection? |
| Reference: | : Padilla L, Pearson EA, Pelizzari CA. Collision prediction software for radiotherapy treatments. Med Phys. 2015;42(11):6448-6456 |
| Choice A: | he resolution of the real time surface acquired with clinical systems is too low for proper collision prediction/detection. |
| Choice B: | The DICOM reference surface only shows the extent of the anatomy imaged during simulation impeding the system from predicting/detecting collisions. |
| Choice C: | The fixed position of the cameras in the treatment room does not allow the system to see the full patient space necessary for reliable collision prediction/detection. |
| Question 8: Which reason would render the external contour of the patient’s planning CT scan insufficient for collision prediction calculations? |
| Reference: | Padilla L, Pearson EA, Pelizzari CA. Collision prediction software for radiotherapy treatments. Med Phys. 2015;42(11):6448-6456 |
| Choice A: | It introduces too much uncertainty in the calculation depending on the slice thickness of the scan. |
| Choice B: | It often excludes relevant anatomy for accurate collision predictions. |
| Choice C: | CT contours cannot be used for collision prediction calculations. |
| Question 9: Use of Statistical Process Control methodologies in radiation oncology have been shown to: |
| Reference: | • Pawlicki T, Whitaker M, Boyer A-L. Statistical process control for radiotherapy quality assurance, Med Phys , 2005, vol. 32 (pg. 2777-86)
• Breen S-L, Moseley D-J, Zhang B, et al. Statistical process control for IMRT dosimetric verification, Med Phys , 2008, vol. 35 (pg. 4417-25)
• Pawlicki T, Yoo S, Court L-E, et al. Moving from IMRT QA measurements toward independent computer calculations using control charts, Radiother Oncol , 2009, vol. 8 (pg. 330-7)
• Gerard K, Grandhaye J-P, Marchesi V, et al. A comprehensive analysis of the IMRT dose delivery process using statistical process control (SPC), Med Phys , 2009, vol. 36 (pg. 1275-85)
|
| Choice A: | Identify systematic change in a process where standard deviation methods or the use of established industry standards cannot |
| Choice B: | Have less ability to detect changes in time dependent metrics |
| Choice C: | Have shown no benefit over standard quality management practices |
| Choice D: | None of the above. |
| Question 10: SGRT techniques can be used to statistically improve (or inform) planning parameter determination such as CTV-to-PTV margin for disease specific sites: |
| Reference: | Gierga DP, Turcotte JC, Tong LW, Chen YL, DeLaney TF. Analysis of setup uncertainties for extremity sarcoma patients using surface imaging., Pract Radiat Oncol. 2014 Jul-Aug;4(4):261-6 |
| Choice A: | True. |
| Choice B: | False. |
