| Question 1: The typical steps for creating a KBP predictive model are: prior plan data collection, dosimetric/anatomical feature extraction and selection, model review to remove outliers and model robustness testing. |
| Reference: | • Boutilier JJ, Craig T, Sharpe MB, et al. Sample size requirements for knowledge-based treatment planning. Med Phys 2016; 43: 1212–21
• Delaney AR, Tol JP, Dahele M, et al. Effect of dosimetric outliers on the performance of a commercial knowledge-based planning solution. Int J Radiat Oncol Biol Phys 2015; 94: 469–77.
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| Choice A: | True. |
| Choice B: | False. |
| Question 2: Targets/organs’ DVH objectives estimated from KBP model are patient geometry-specific, while APE employs a pre-set of generic coverage/sparing goals which are protocol-specific. |
| Reference: | • B Wu, M Kusters, M Kunze-busch, et al. Cross-institutional knowledge-based planning (KBP) implementation and its performance comparison to Auto-Planning Engine (APE). Radiother Oncol 2017; 123: 57-62. |
| Choice A: | True. |
| Choice B: | False. |
| Question 3: What have knowledge-based models demonstrated in retrospective evaluations of clinical trials in the spine and prostate? |
| Reference: | • Moore KL(1), Schmidt R(2), Moiseenko V(3), Olsen LA(4), Tan J(4), Xiao Y(5), Galvin J(5), Pugh S(6), Seider MJ(7), Dicker AP(5), Bosch W(4), Michalski J(4), Mutic S(4). Quantifying Unnecessary Normal Tissue Complication Risks due to Suboptimal Planning: A Secondary Study of RTOG 0126.nt J Radiat Oncol Biol Phys. 2015 Jun 1;92(2):228-35.
• Younge KC(1), Marsh RB(2), Owen D(2), Geng H(3), Xiao Y(3), Spratt DE(2), Foy J(2), Suresh K(2), Wu QJ(4), Yin FF(4), Ryu S(5), Matuszak MM(2). Improving Quality and Consistency in NRG Oncology Radiation Therapy Oncology Group 0631 for Spine Radiosurgery via Knowledge-Based Planning. Int J Radiat Oncol Biol Phys. 2018 Mar 15;100(4):1067-1074.
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| Choice A: | Improve overall survival. |
| Choice B: | Produce equivalent or improved dose volume metrics in normal tissues compared to manual clinical plans.. |
| Choice C: | Improve conformality of treatment plans. |
| Choice D: | Increase treatment planning time. |
| Question 4: The use of knowledge-based planning is being tested in which current prospective clinical trial? |
| Reference: | https://www.cancer.gov/about-cancer/treatment/clinical-trials/search/v?id=NCI-2015-00835&r=1 |
| Choice A: | RTOG 0631 (Spine SBRT) |
| Choice B: | NRG SPN001 (Spine) |
| Choice C: | NRG GY006 (Gyn) |
| Choice D: | RTOG0126 (Prostate) |
| Question 5: What has the use of automatic planning techniques demonstrated? |
| Reference: | • Gallio, Elena et al. Evaluation of a commercial automatic treatment planning system for liver stereotactic body radiation therapy treatments. Physica Medica: European Journal of Medical Physics , Volume 46 , 153 - 159 |
| Choice A: | Decrease planning efficiency. |
| Choice B: | Reduce target coverage. |
| Choice C: | Increase monitor units. |
| Choice D: | Reduce plan quality dependency on planner experience. |
| Question 6: How can automated planning routines be tested? |
| Reference: | • K. L. Moore, R. S. Brame, D.A. Low, and S. Mutic, Experience-based Quality Control of Clinical IMRT Planning, Int. J. Radiat. Oncol. Biol. Phys., 81(2), pp. 545-551 (2011).
• B. Ziemer, S. Shiraishi, J. Hattangadi-Gluth, P. Sanghvi, and K. L. Moorey, Fully-automated, comprehensive knowledge-based planning for stereotactic radiosurgery: pre-clinical validation through blinded physician review, Prac. Rad. Onc., 7, e569-e578, (2017).
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| Choice A: | Re-planning a large sample of previous cases and comparing to clinically approved plans |
| Choice B: | Clinically implementing side-by-side to manual planning and making dosimetric comparisons |
| Choice C: | Blinding physicians to manual vs. automated plans at the time of review |
| Choice D: | All of the Above |
| Question 7: Accurate knowledge-based dose predictions are sufficient to guarantee knowledge-based automated planning routines. |
| Reference: | • N. Li, S. S. Noticewala, C. W. Williamson, H. Shen, I. Sirak, R. Tarnawski, U. Mahantshetty, C. K. Hoh, K. L. Moore, and L. K. Mell, Feasibility of atlas-based active bone marrow sparing intensity modulated radiation therapy for cervical cancer, Radiotherapy and Oncology, 123, 325-330, (2017). |
| Choice A: | True. |
| Choice B: | False. |
| Question 8: When blinded comparison studies compared automated vs. manual stereotactic radiosugery plans, which was chosen more frequently? |
| Reference: | • B. Ziemer, S. Shiraishi, J. Hattangadi-Gluth, P. Sanghvi, and K. L. Moorey, Fully-automated, comprehensive knowledge-based planning for stereotactic radiosurgery: pre-clinical validation through blinded physician review, Prac. Rad. Onc., 7, e569-e578, (2017). |
| Choice A: | Chosen less frequently than manual planning. |
| Choice B: | Chosen more frequently than manual planning. |
| Choice C: | Chosen at the same rate as manual planning. |
| Question 9: Knowledge-based automated planning models can be transferred between institutions: |
| Reference: | • Evaluation of a Knowledge-Based Planning Solution for Head and Neck Cancer, Jim P. Tol, Alexander R. Delaney, Max Dahele, Ben J. Slotman, Wilko F.A.R. Verbakel, IJROBP, March 1, 2015, Volume 91, Issue 3, Pages 612–620 |
| Choice A: | True. |
| Choice B: | False. |
| Question 10: Knowledge-based planning models can highlight clinical planning differences between institutions: |
| Reference: | • Evaluating inter-campus plan consistency using a knowledge-based planning model, Sean L. Berry, Rongtao Ma, Amanda Boczkowski, Andrew Jackson, Pengpeng Zhang, Margie Hunt, Radiotherapy and Oncology, August 2016, Volume 120, Issue 2, Pages 349–355 |
| Choice A: | True. |
| Choice B: | False. |
