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Journal articles on the topic 'Treatment Planning System'

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Published: 4 June 2021
Last updated: 9 March 2023

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1

Guo, Fanqing. "3-D treatment planning system—Leksell Gamma Knife treatment planning system." Medical Dosimetry 43, no. 2 (2018): 177–83. http://dx.doi.org/10.1016/j.meddos.2018.03.001.

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2

Pellegrini, Roberto. "Plato Treatment Planning System." Tumori Journal 84, no. 2 (March 1998): 281–83. http://dx.doi.org/10.1177/030089169808400231.

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3

Sarkar, Vikren, Long Huang, Prema Rassiah-Szegedi, Hui Zhao, Jessica Huang, Martin Szegedi, and Bill J. Salter. "Planning for mARC treatments with the Eclipse treatment planning system." Journal of Applied Clinical Medical Physics 16, no. 2 (March 2015): 458–64. http://dx.doi.org/10.1120/jacmp.v16i2.5351.

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4

Xia, Ping, and Eric Murray. "3D treatment planning system—Pinnacle system." Medical Dosimetry 43, no. 2 (2018): 118–28. http://dx.doi.org/10.1016/j.meddos.2018.02.004.

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5

Abraham, David, Valdir Colussi, Donald Shina, Timothy Kinsella, and Claudio Sibata. "TBI treatment planning using the ADAC Pinnacle Treatment Planning System." Medical Dosimetry 25, no. 4 (December 2000): 219–24. http://dx.doi.org/10.1016/s0958-3947(00)00049-2.

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6

Santvoort, J. P. C. van. "Radiotherapy Treatment Planning: New System Approaches." Physics in Medicine and Biology 45, no. 12 (November 21, 2000): 3861. http://dx.doi.org/10.1088/0031-9155/45/12/702.

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7

Bodensteiner, Dayna. "RayStation: External beam treatment planning system." Medical Dosimetry 43, no. 2 (2018): 168–76. http://dx.doi.org/10.1016/j.meddos.2018.02.013.

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8

Schreuder, Andries N., Dan T. L. Jones, Julyan E. Symons, Evan A. De Kock, Jan K. Hough, Jenny Wilson, Fred J. A. Vernimmen, Wolfgang Schlegel, Angelika Höss, and Michael Lee. "The NAC proton treatment planning system." Strahlentherapie und Onkologie 175, S2 (June 1999): 10–12. http://dx.doi.org/10.1007/bf03038876.

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9

Purely, J. A., W. B. Harms, J. W. Wong, J. W. Matthews, E. D. Slessinger, and B. E. Emami. "Three-dimmsional radiation treatment planning system." International Journal of Radiation Oncology*Biology*Physics 12 (November 1986): 125–26. http://dx.doi.org/10.1016/0360-3016(86)90570-5.

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10

Lu, W., Q. Chen, M. Chen, Y. Chen, and G. Olivera. "Non-cluster TomoTherapy Treatment Planning System." International Journal of Radiation Oncology*Biology*Physics 78, no. 3 (November 2010): S741. http://dx.doi.org/10.1016/j.ijrobp.2010.07.1716.

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11

Kantor, Michael Eugene, George Starkschall, and Peter Balter. "Relational database of treatment planning system information." Journal of Radiation Oncology Informatics 5, no. 1 (October 2, 2017): 1–10. http://dx.doi.org/10.5166/jroi-5-1-15.

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The purpose of the present work was to develop a relational database and associated applications to facilitate retrospective review of data present in radiation treatment plans. The data source was a commercial radiation treatment planning system (Pinnacle3, Philips Medical Systems, Milpitas CA), which is specifically characterized by an open data storage format and internal scripting capability. The database is an open-source, relational database (PostgreSQL, PostgreSQL Global Development Group, http://www.postgresql.org). The data is presented through a web interface in addition to being fully query-accessible using standard tools. A database schema was created to organize the large collection of parameters used to generate treatment plans as well as the parameters that characterized these plans. The system was implemented through a combination of the treatment planning systems internal scripting language and externally executed code. Data is exported in a way that is transparent to the user, through integration into an existing and routinely-used process. The system has been transparently incorporated into our radiation treatment planning workflow. The website-based database interface has allowed users with minimal training to extract information from the database.
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12

Sahoo, Narayan, Falk Poenisch, Xiaodong Zhang, Yupeng Li, MingFu Lii, Heng Li, Archana S. Gautam, Richard Wu, Michael Gillin, and Xiaorong R. Zhu. "3D treatment planning system—Varian Eclipse for proton therapy planning." Medical Dosimetry 43, no. 2 (2018): 184–94. http://dx.doi.org/10.1016/j.meddos.2018.03.006.

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13

Dąbrowska-Szewczyk, Edyta, Anna Zawadzka, Beata Brzozowska, Agnieszka Walewska, and Paweł Kukołowicz. "Independent verification of treatment planning system calculations." Nukleonika 66, no. 2 (June 1, 2021): 47–53. http://dx.doi.org/10.2478/nuka-2021-0006.

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Abstract Purpose According to the available international recommendations, at least one independent verification of the calculations of number of monitor unit (MU) is required for every patient treated by teleradiotherapy. The aim of this study was to estimate the differences of dose distributions calculated with two treatment planning systems: Eclipse (Varian) and Oncentra MasterPlan (Elekta). Materials and methods The analysis was performed for 280 three-dimensional conformal radiotherapy treatment (3D-CRT) plans with photon beams from Varian accelerators: CL 600C/D X6 MV (109 plans), CL 2300C/D X6 MV (43 plans), and CL 2300C/D X15 MV (128 plans). The mean doses in the planning target volume (PTV) and doses at the isocenter point obtained with Eclipse and Oncentra MasterPlan (OMP) were compared with Wilcoxon matched-pairs signed rank test. Additionally, the treatment planning system (TPS) calculations were compared with dosimetric measurements performed in the inhomogeneous phantom. Results Data were analysed for 6 MV plans and for 15 MV plans separately, independently of the treatment machine. The dose values calculated in Eclipse were significantly (p <0.001) higher compared to calculations of OMP system. The average difference of the mean dose to PTV was (1.4 ± 1.0)% for X6 MV and (2.5 ± 0.6)% for X15 MV. Average dose disparities at the isocenter point were (1.3 ± 1.9)% and (2.1 ± 1.0)% for X6 MV and X15 MV beams, respectively. The largest differences were observed in lungs, air cavities, and bone structures. Moreover the variation in dosimetric measurements was less as compared to Eclipse calculations. Conclusions OMP calculations were introduced as the independent MU verification tool with the first action level range equal to 3.5%.
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14

Stevens, Craig W., Pei-Fong Wong, David Rice, Melenda Jeeter, Kenneth Forster, and X. Ronald Zhu. "Treatment planning system evaluation for mesothelioma IMRT." Lung Cancer 49 (July 2005): S75—S81. http://dx.doi.org/10.1016/j.lungcan.2005.03.023.

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15

Flage, R., and T. Aven. "On treatment of uncertainty in system planning." Reliability Engineering & System Safety 94, no. 4 (April 2009): 884–90. http://dx.doi.org/10.1016/j.ress.2008.09.011.

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16

NAYLOR, CRAIG KIRKHAM. "Esthetic Treatment Planning: The Grid Analysis System." Journal of Esthetic and Restorative Dentistry 14, no. 2 (March 2002): 76–84. http://dx.doi.org/10.1111/j.1708-8240.2002.tb00155.x.

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17

Alakuijala, Jyrki, Ari Pekkarinen, and Harri Puurunen. "2205 Volume definition system for treatment planning." International Journal of Radiation Oncology*Biology*Physics 39, no. 2 (January 1997): 343. http://dx.doi.org/10.1016/s0360-3016(97)80971-6.

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18

Klein, Eric E. "Treatment planning for Enhanced Dynamic Wedge with the CMS focus/modulex treatment planning system." Medical Dosimetry 22, no. 3 (September 1997): 213–14. http://dx.doi.org/10.1016/s0958-3947(97)00020-4.

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19

Tateoka, K., T. Saikawa, and N. Saitou. "Construction of CT treatment planning system and image verification System." Japanese Journal of Radiological Technology 51, no. 8 (1995): 1011. http://dx.doi.org/10.6009/jjrt.kj00001352586.

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20

Steyn, J. M., F. C. P. du Plessis, and W. I. D. Rae. "O21. Verification of prostate conformal radiotherapy treatment planning done on an XiO treatment planning system." Physica Medica 32 (September 2016): 147. http://dx.doi.org/10.1016/j.ejmp.2016.07.029.

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21

Lawrence, H. P. "A public domain PC based treatment planning system." Physics in Medicine and Biology 35, no. 6 (June 1, 1990): 787–91. http://dx.doi.org/10.1088/0031-9155/35/6/008.

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22

&NA;. "Siemens TMS 3-D Radiation Treatment Planning System." Investigative Radiology 31, no. 6 (June 1996): 386. http://dx.doi.org/10.1097/00004424-199606000-00018.

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23

Kolarevic, Goran, Drazan Jaros, Goran Marosevic, Dejan Ignjatic, and Dragoljub Mirjanic. "Dosimetric verification of clinical radiotherapy treatment planning system." Vojnosanitetski pregled, no. 00 (2020): 70. http://dx.doi.org/10.2298/vsp200411070k.

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24

Mohan, Radhe, Glenn Barest, Linda J. Brewster, Chen S. Chui, Gerald J. Kutcher, John S. Laughlin, and Zvi Fuks. "A comprehensive three-dimensional radiation treatment planning system." International Journal of Radiation Oncology*Biology*Physics 15, no. 2 (August 1988): 481–95. http://dx.doi.org/10.1016/s0360-3016(98)90033-5.

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25

Oliveira, A., S. Germano, P. Pereira, V. Batel, F. Marques, and P. Almeida. "451 Independent Verification for XiO Treatment Planning System." Radiotherapy and Oncology 76 (September 2005): S195—S196. http://dx.doi.org/10.1016/s0167-8140(05)81427-6.

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26

Cufflin, R., E. Spezi, A. Millin, and D. G. Lewis. "522 oral TREATMENT PLANNING SYSTEM BASED EXIT DOSIMETRY." Radiotherapy and Oncology 99 (May 2011): S212. http://dx.doi.org/10.1016/s0167-8140(11)70644-2.

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27

Yin, F., Y. Hui, H. Guan, and J. Kim. "An artificial intelligence-guided inverse treatment planning system." International Journal of Radiation Oncology*Biology*Physics 51, no. 3 (November 2001): 405. http://dx.doi.org/10.1016/s0360-3016(01)02569-x.

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28

Clements, Mac, Nicholas Schupp, Megan Tattersall, Anthony Brown, and Randy Larson. "Monaco treatment planning system tools and optimization processes." Medical Dosimetry 43, no. 2 (2018): 106–17. http://dx.doi.org/10.1016/j.meddos.2018.02.005.

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29

Saw, Cheng B., Leah Katz, Carol Gillette, and Lawrence Koutcher. "3D treatment planning on helical tomotherapy delivery system." Medical Dosimetry 43, no. 2 (2018): 159–67. http://dx.doi.org/10.1016/j.meddos.2018.02.012.

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30

Gershkevitsh, E., C. Pesznyak, B. Petrovic, J. Grezdo, K. Chelminski, M. C. Lopes, and J. Izewska. "IAEA sponsored treatment planning system audits in Europe." Physica Medica 30 (2014): e13-e14. http://dx.doi.org/10.1016/j.ejmp.2014.07.055.

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31

Epstein, D., E. Shekel, R. M. Pfeffer, Y. Lipsky, R. Spiegelmann, and D. Levin. "Treating Benign Cranial Lesions - Treatment Planning System Comparison." International Journal of Radiation Oncology*Biology*Physics 102, no. 3 (November 2018): e509-e510. http://dx.doi.org/10.1016/j.ijrobp.2018.07.1442.

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32

Potrebko, P. S., J. Fiege, H. Champion, A. Cull, B. McCurdy, M. West, E. Lyn, J. Butler, and D. Fewer. "PARETO: A New Multiobjective IMRT Treatment Planning System." International Journal of Radiation Oncology*Biology*Physics 81, no. 2 (October 2011): S197—S198. http://dx.doi.org/10.1016/j.ijrobp.2011.06.356.

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33

Van De Kamer, J. B., A. A. C. De Leeuw, S. N. Hornsleth, H. Kroeze, A. N. T. J. Kotte, and J. J. W. Lagendijk. "Development of a regional hyperthermia treatment planning system." International Journal of Hyperthermia 17, no. 3 (May 1, 2001): 207–20. http://dx.doi.org/10.1080/02656730010017903.

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34

J. B. Van De Kamer, A. A. C. De Lee. "Development of a regional hyperthermia treatment planning system." International Journal of Hyperthermia 17, no. 3 (January 2001): 207–20. http://dx.doi.org/10.1080/02656730120302.

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35

NAGASAWA, Takeshi. "The planning of sludge treatment system in Yokohama." Journal of Environmental Conservation Engineering 14, no. 3 (1985): 245–48. http://dx.doi.org/10.5956/jriet.14.245.

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36

Sumida, Iori. "QA/QC for Treatment Planning System: Practical Approach." Japanese Journal of Radiological Technology 67, no. 10 (2011): 1342–48. http://dx.doi.org/10.6009/jjrt.67.1342.

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37

Wemple, C. A., D. E. Wessol, D. W. Nigg, J. J. Cogliati, M. L. Milvich, C. Frederickson, M. Perkins, and G. J. Harkin. "MINERVA—a multi-modal radiation treatment planning system." Applied Radiation and Isotopes 61, no. 5 (November 2004): 745–52. http://dx.doi.org/10.1016/j.apradiso.2004.05.049.

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38

Denardo, Gerald L., Antolin Raventos, Horace H. Hines, Paul O. Scheibe, Daniel J. Macey, Marguerite T. Hays, and Sally J. Denardo. "Requirements for a treatment planning system for radioimmunotherapy." International Journal of Radiation Oncology*Biology*Physics 11, no. 2 (February 1985): 335–48. http://dx.doi.org/10.1016/0360-3016(85)90156-7.

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39

Pla, C. "A high speed interstitial/intracavitary treatment planning system." International Journal of Radiation Oncology*Biology*Physics 17 (January 1989): 237–38. http://dx.doi.org/10.1016/0360-3016(89)90861-4.

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40

Wu, B., G. Sanguineti, M. Kazhdan, P. Simari, R. Taylor, and T. Mcnutt. "An OVH-driven Automated IMRT Treatment Planning System." International Journal of Radiation Oncology*Biology*Physics 78, no. 3 (November 2010): S187. http://dx.doi.org/10.1016/j.ijrobp.2010.07.455.

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41

Purdy, J. A., W. B. Harms, J. W. Matthews, R. E. Drzymala, J. Manolis, and B. Emami. "Adbances in a 3D radiation treatment planning system." International Journal of Radiation Oncology*Biology*Physics 21 (January 1991): 143–44. http://dx.doi.org/10.1016/0360-3016(91)90485-m.

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42

Huertas, C., C. Ferrer, C. Huerga, I. Mas, and A. Serrada. "PO-0824: Treatment couch modeling in Elekta Monaco treatment planning system." Radiotherapy and Oncology 119 (April 2016): S389—S390. http://dx.doi.org/10.1016/s0167-8140(16)32074-6.

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43

Shu, Huazhong, Yulong Yan, Limin Luo, and Xudong Bao. "Three-dimensional optimization of treatment planning for gamma unit treatment system." Medical Physics 25, no. 12 (December 1998): 2352–57. http://dx.doi.org/10.1118/1.598445.

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44

Li, Taoran, Qiuwen Wu, You Zhang, Irina Vergalasova, W. Robert Lee, Fang-Fang Yin, and Q. Jackie Wu. "Strategies for automatic online treatment plan reoptimization using clinical treatment planning system: A planning parameters study." Medical Physics 40, no. 11 (October 10, 2013): 111711. http://dx.doi.org/10.1118/1.4823473.

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45

Athiyaman, Hemalatha, Athiyaman Mayilvaganan, and Daleep Singh. "A simple planning technique of craniospinal irradiation in the eclipse treatment planning system." Journal of Medical Physics 39, no. 4 (2014): 251. http://dx.doi.org/10.4103/0971-6203.144495.

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46

McDermott, Patrick N. "Dose calculation accuracy of lung planning with a commercial IMRT treatment planning system." Journal of Applied Clinical Medical Physics 4, no. 4 (2003): 341. http://dx.doi.org/10.1120/1.1623172.

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47

McDermott, Patrick N., Tongming He, and A. DeYoung. "Dose calculation accuracy of lung planning with a commercial IMRT treatment planning system." Journal of Applied Clinical Medical Physics 4, no. 4 (September 2003): 341–51. http://dx.doi.org/10.1120/jacmp.v4i4.2505.

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48

McCallum, H., N. Richmond, C. Walker, S. Andersson, and S. Svensson. "EP-2061 Feasibility of MR-only planning in a commercial treatment planning system." Radiotherapy and Oncology 133 (April 2019): S1134—S1135. http://dx.doi.org/10.1016/s0167-8140(19)32481-8.

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49

Boylan, C. J., C. Golby, and C. G. Rowbottom. "A VMAT planning solution for prostate patients using a commercial treatment planning system." Physics in Medicine and Biology 55, no. 14 (July 5, 2010): N395—N404. http://dx.doi.org/10.1088/0031-9155/55/14/n01.

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50

Novario, Raffaele, Paola Stucchi, Lucia Perna, and Leopoldo Conte. "Radiotherapy Treatment Verification." Tumori Journal 84, no. 2 (March 1998): 144–49. http://dx.doi.org/10.1177/030089169808400209.

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During a radiotherapy treatment, a dosimetric verification or a geometric localization can be done, in order to assess the quality of the treatment. The dosimetric verification is generally performed measuring the dose at some points inside (natural cavities) or outside the patient, and comparing it to the dose at the same points calculated and predicted by the treatment planning system. This can be done either with thermoluminescent or diodes dosimeters or with ionization chambers. The geometric localization can be done acquiring a portal image of the patient. Portal imaging can be performed either with films placed between metallic screens, or with an electronic portal imaging device such as fluoroscopic systems, solid state devices or matrix ionization chamber systems. In order to assess possible field placement errors, the portal images have to be compared with images obtained with the simulator in the same geometric conditions and/or with the digitally reconstructed radiograph (DRR) obtained with the treatment planning system. In particular, when using matrix ionization chamber systems, the portal images contain also information regarding the exit dose. This means that this kind of imaging device can be used both for geometric localization and for dosimetric verification. In this case, the exit dose measured by the portal image can be compared with the exit dose calculated and predicted by the treatment planning system. Some “in-vivo” applications of this methodology are presented.
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