| Question 1: What automatic implementation does Phillips Pinnacle Autoplan use? |
| Reference: | 1. Hazell I, Bzdusek K, Kumar P, et al. Automatic planning of head and neck treatment plans. J Appl Clin Med Phys 2016;17(1):272-82. doi: 10.1120/jacmp.v17i1.5901
2. Hansen CR, Bertelsen A, Hazell I, et al. Automatic treatment planning improves the clinical quality of head and neck cancer treatment plans. Clinical and Translational Radiation Oncology 2016;1:2-8. doi: 10.1016/j.ctro.2016.08.001
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| Choice A: | Automatic Protocol (template) based planning. |
| Choice B: | Knowledge-based planning. |
| Choice C: | Multi-Criteria Optimisation. |
| Question 2: How does Autoplan handle overlapping target and organ at risk? |
| Reference: | 1. Hazell I, Bzdusek K, Kumar P, et al. Automatic planning of head and neck treatment plans. J Appl Clin Med Phys 2016;17(1):272-82. doi: 10.1120/jacmp.v17i1.5901
2. Hansen CR, Bertelsen A, Hazell I, et al. Automatic treatment planning improves the clinical quality of head and neck cancer treatment plans. Clinical and Translational Radiation Oncology 2016;1:2-8. doi: 10.1016/j.ctro.2016.08.001
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| Choice A: | Change priority according to overlapping fraction of target and organ at risk. |
| Choice B: | Bayesian statistics evaluation of target and organ at risk importance |
| Choice C: | Principal component analysis of geometric positioning of target and organ at risk. |
| Question 3: What statement is best: |
| Reference: | [1] Breedveld S, Storchi PRM, Voet PWJ and Heijmen BJM. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans. Med Phys 2012;39:951-63. |
| Choice A: | Automated planning always results in a Pareto-optimal plan. |
| Choice B: | A Pareto-optimal plan has the best balances between all (competing) treatment goals. |
| Choice C: | Ideally, a treatment plan is Pareto-optimal with favorable balances between all treatment goals. |
| Choice D: | There is no better plan than a Pareto-optimal plan. |
| Question 4: The main difference between a priori and a posteriori multi-criteria optimization (MCO) is: |
| Reference: | [1] Breedveld S, Storchi PRM, Voet PWJ and Heijmen BJM. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans. Med Phys 2012;39:951-63.
[5] Craft DL, Halabi TF, Shih HA, Bortfeld TR. Approximating convex pareto surfaces in multiobjective radiotherapy planning. Med Phys 2006;33:3399–407. |
| Choice A: | A priori MCO results in a Pareto-optimal plan, while this is not guaranteed in a posteriori MCO. |
| Choice B: | A posteriori MCO results in a Pareto-optimal plan, while this is not guaranteed in a priori MCO. |
| Choice C: | The use of a different optimizer. |
| Choice D: | In a priori MCO, the patient’s plan is fully automatically generated, while with a posteriori MCO the final plan selection involves human interference. |
| Question 5: In a priori multi-criteria optimization (MCO)… |
| Reference: | [1] Breedveld S, Storchi PRM, Voet PWJ and Heijmen BJM. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans. Med Phys 2012;39:951-63
[4] Della Gala treatment planning for advanced stage non-small cell lung cancer patients. Strahlenther Onkol. 2017;193(5):402-9.G, Dirkx MLP, Hoekstra N, Fransen D, Lanconelli N, van de Pol M et al. Fully automated VMAT |
| Choice A: | The treatment goal with the highest priority will always be achieved. |
| Choice B: | Objectives have assigned priorities for multi-criteria plan generation. |
| Choice C: | All goals can be obtained without exceeding the hard planning constraints. |
| Choice D: | Assigned priorities determine which hard constraints are most important. |
| Question 6: Which of the following is false. The RapidPlan™ DVH estimation model configuration uses the following information: |
| Reference: | Fogliata et al. On the pre-clinical validation of a commercial model-based optimisation engine: Application to volumetric modulated arc therapy for patients with lung or prostate cancer. Radiother Oncol. 2014,113:385-391. |
| Choice A: | Anatomical overlap of organ-at-risk (OAR) with the target volume. |
| Choice B: | Overlap of OAR with another OAR. |
| Choice C: | Part of the OAR outside the treatment field. |
| Choice D: | The distance between OAR structure and the target surface. |
| Question 7: In addition to planning, knowledge-based planning could be used as a plan quality assessment tool: |
| Reference: | Wang et al. Prospective clinical validation of independent DVH prediction for plan QA in automatic treatment planning for prostate cancer patients. Radiother Oncol 2017;125:500–6.
Berry et al. Evaluating inter-campus plan consistency using a knowledge based planning model. Radiother Oncol 2016;120:349–55.
Tol et al. Can knowledge-based DVH predictions be used for automated, individualized quality assurance of radiotherapy treatment plans? Radiat Oncol 2015;10.
Stanhope et al. Utilizing knowledge from prior plans in the evaluation of quality assurance. Phys Med Biol 2015;60:4873–91.
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| Choice A: | True. |
| Choice B: | False. |
| Question 8: How should statistically outlying treatment plans be handled in the DVH prediction model configuration? |
| Reference: | Hussein et al. Clinical validation and benchmarking of knowledge-based IMRT and VMAT treatment planning in pelvic anatomy. Radiother Oncol 2016;120:473–9.
Delaney et al. Effect of Dosimetric Outliers on the Performance of a Commercial Knowledge-Based Planning Solution. Int J Radiat Oncol 2016;94:469–77.
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| Choice A: | Do not exclude any of them. |
| Choice B: | Critically evaluate them to check if they are clinically relevant to the model. |
| Choice C: | Exclude all statistical outliers. |
| Question 9: 4p radiotherapy always utilizes the entire spherical space for treatment, true or false? |
| Reference: | Ke Sheng Response to “in regard to “Tran A, Zhang J, Woods K, Yu V, Nguyen D, Gustafson G, Rosen L, Sheng K. Treatment planning comparison of IMPT, VMAT and 4π radiotherapy for prostate cases ””, Radiation Oncology 2018 13:66 |
| Choice A: | True. |
| Choice B: | False. |
| Question 10: 4p radiotherapy treatment efficiency can be improved by the following: |
| Reference: | Victoria Yu, Angelia Tran, Kaley Woods, Minsong Cao, Robert Chin, Ke Sheng, Tania Karealian, A Prospective 4pi Radiotherapy Clinical Study in Recurrent High Grade Glioma Patients, Int. Journal of Radiation Oncology, Biology, Physics, Volume 101, Issue 1, 1 May 2018, Pages 144-151 |
| Choice A: | Automated and coordinated couch and gantry movement |
| Choice B: | Non-coplanar volumetric modulated arc therapy |
| Choice C: | Automated treatment planning |
| Choice D: | Reducing the number of MLC segments using direct aperture approach |
| Choice E: | All the above. |
