| Question 1: What are some benefits of iterative reconstruction for CBCT? |
| Reference: | J. Nuyts, B. De Man, J. a Fessler, W. Zbijewski, and F. J. Beekman, "Modelling the physics in the iterative reconstruction for transmission computed tomography." Phys. Med. Biol., vol. 58, no. 12, pp. R63-96, Jun. 2013. |
| Choice A: | Noise reduction |
| Choice B: | Reduce cone-beam artifacts |
| Choice C: | Improve HU accuracy |
| Choice D: | All of the above |
| Question 2: What are some ways to speed up iterative reconstruction? |
| Reference: | A. S. Wang, J. W. Stayman, Y. Otake, S. Vogt, G. Kleinszig, and J. H. Siewerdsen, "Accelerated statistical reconstruction for C-arm cone-beam CT using Nesterov's method," Med. Phys., vol. 42, no. 5, pp. 2699-2708, May 2015. |
| Choice A: | Implementation on GPUs |
| Choice B: | Ordered subsets |
| Choice C: | Momentum-based algorithms such as Nesterov acceleration |
| Choice D: | All of the above |
| Question 3: What is the proliferation saturation index (PSI)? |
| Reference: | Prokopiou S, Moros EG, Poleszczuk J, Caudell J, Torres-Roca JF, Latifi K, Lee JK, Myerson R, Harrison LB, Enderling H. "A proliferation saturation index to predict radiation response and personalize radiotherapy fractionation." Radiat Oncol. 2015 Jul |
| Choice A: | A measurement of the patient-specific amount of oxygen carried by a red blood cells. |
| Choice B: | A pre-treatment, non-invasive imaging derived biomarker of the proliferative subpopulation in a tumor. |
| Choice C: | A biomarker for radiation-induced cell cycle arrest. |
| Choice D: | An imaging-derived biomarker of hypoxic areas in pre-treatment radiology. |
| Question 4: How can PSI contribute to radiation personalization? |
| Reference: | Poleszczuk J, Walker R, Moros EG, Latifi K, Caudell JJ, Enderling H. "Predicting Patient-Specific Radiotherapy Protocols Based on Mathematical Model Choice for Proliferation Saturation Index." Bull Math Biol. 2018 May;80(5):1195-1206. doi: 10.1007/s11 |
| Choice A: | Simulate different treatment protocols from pre-treatment dynamics to identify best dose and dose fractionation for individual patients. |
| Choice B: | Calculate the total dose to control the tumor for individual patients. |
| Choice C: | Estimate the best treatment protocol to reduce specific toxicities in an average patient population. |
| Choice D: | Predict the synergy of radiation with the patient’s immune system. |
| Question 5: Which method can be used to solve volumetric modulated arc therapy (VMAT) optimization problem? |
| Reference: | Nguyen D, Lyu Q, Ruan D, O'Connor D, Low DA, Sheng K. "A comprehensive formulation for volumetric modulated arc therapy planning." Med Phys. 2016 Jul;43(7):4263. doi:10.1118/1.4953832. |
| Choice A: | Simulated annealing |
| Choice B: | Progressive sampling |
| Choice C: | Non-progressive sampling |
| Choice D: | All the above |
| Question 6: Which description of 4Ï€ VMAT optimization is incorrect? |
| Reference: | Lyu Q, Yu VY, Ruan D, Neph R, O'Connor D, Sheng K. "A novel optimization framework for VMAT with dynamic gantry couch rotation." Phys Med Biol. 2018 Jun 13;63(12):125013. doi: 10.1088/1361-6560/aac704. |
| Choice A: | 4Ï€ VMAT incorporates couch rotation into the VMAT optimization. |
| Choice B: | 4Ï€ VMAT improves dose compactness compared with coplanar VMAT. |
| Choice C: | 4Ï€ VMAT performs static beam 4Ï€ IMRT optimization first and then connects the static beams with arcs. |
| Choice D: | Optimized dynamic collimator rotation can be included in 4Ï€ VMAT for additional dosimetric benefits. |
