The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Adaptive radiotherapy: The Elekta Unity MR-linac concept
Open accessAbstract
BACKGROUND AND PURPOSE: The promise of the MR-linac is that one can visualize all anatomical changes during the course of radiotherapy and hence adapt the treatment plan in order to always have the optimal treatment. Yet, there is a trade-off to be made between the time spent for adapting the treatment plan against the dosimetric gain. In this work, the various daily plan adaptation methods will be presented and applied on a variety of tumour sites. The aim is to provide an insight in the behavior of the state-of-the-art 1.5 T MRI guided on-line adaptive radiotherapy methods. MATERIALS AND METHODS: To explore the different available plan adaptation workflows and methods, we have simulated online plan adaptation for five cases with varying levels of inter-fraction motion, regions of interest and target sizes: prostate, rectum, esophagus and lymph node oligometastases (single and multiple target). The plans were evaluated based on the clinical dose constraints and the optimization time was measured. RESULTS: The time needed for plan adaptation ranged between 17 and 485 s. More advanced plan adaptation methods generally resulted in more plans that met the clinical dose criteria. Violations were often caused by insufficient PTV coverage or, for the multiple lymph node case, a too high dose to OAR in the vicinity of the PTV. With full online replanning it was possible to create plans that met all clinical dose constraints for all cases. CONCLUSION: Daily full online replanning is the most robust adaptive planning method for Unity. It is feasible for specific sites in clinically acceptable times. Faster methods are available, but before applying these, the specific use cases should be explored dosimetrically.
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Raaymakers, B. W., Jürgenliemk-Schulz, I. M., Bol, G. H., Glitzner, M., Kotte, A. N. T. J., van Asselen, B., de Boer, J. C. J., Bluemink, J. J., Hackett, S. L., Moerland, M. A., et al. (2017) · Physics in Medicine & Biology · doi:10.1088/1361-6560/aa9517 · Cited by 541
Self-citationThe Magnetic Resonance Imaging–Linac System
Lagendijk, J. J. W., Raaymakers, B. W., & van Vulpen, M. (2014) · Seminars in Radiation Oncology · doi:10.1016/j.semradonc.2014.02.009 · Cited by 464
Self-citationAn on-line replanning scheme for interfractional variationsa)
Ahunbay, E. E., Cheng, P., Chen, G., Narayanan, S., Yu, C., Lawton, C. A., & Li, X. A. (2008) · Medical Physics · doi:10.1118/1.2952443 · Cited by 120
Evolution of motion uncertainty in rectal cancer: implications for adaptive radiotherapy
Kleijnen, J.-P., van Asselen, B., Burbach, J. P. M., Intven, M., Philippens, M. E. P., Reerink, O., Lagendijk, J. J. W., & Raaymakers, B. W. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/1/1 · Cited by 41
Self-citationZachiu, C., de Senneville, B. D., Moonen, C., Raaymakers, B., & Ries, M. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aad109 · Cited by 25
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Cited by
Glide-Hurst, C. K., Lee, P., Yock, A. D., Olsen, J. R., Cao, M., Siddiqui, F., Parker, W., Doemer, A., Rong, Y., Kishan, A. U., et al. (2021) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2020.10.021 · Cited by 317
Artificial intelligence in radiotherapy
Li, G., Wu, X., & Ma, X. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.08.005 · Cited by 46
Metadata
- Authors
- Winkel, D., Bol, G. H., Kroon, P. S., van Asselen, B., Hackett, S. S., Werensteijn-Honingh, A. M., Intven, M. P. W., Eppinga, W. S. C., Tijssen, R. H. N., Kerkmeijer, L. G. W., de Boer, H. C. J., Mook, S., Meijer, G. J., Hes, J., Willemsen-Bosman, M., de Groot-van Breugel, E. N., Jürgenliemk-Schulz, I. M., & Raaymakers, B. W.
- Venue
- Clinical and Translational Radiation Oncology
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 18
- Pages
- 54-59
- ISSN
- 2405-6308 (ISSN-L)
- OpenAlex
- W2930910485
- Cited by
- 572
- References
- 5
- FWCI
- 57.64
- Type
- journal article
- Language
- en
- Open access
- gold
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- Winkel, D., Bol, G. H., Kroon, P. S., van Asselen, B., Hackett, S. S., Werensteijn-Honingh, A. M., Intven, M. P. W., Eppinga, W. S. C., Tijssen, R. H. N., Kerkmeijer, L. G. W., de Boer, H. C. J., Mook, S., Meijer, G. J., Hes, J., Willemsen-Bosman, M., de Groot-van Breugel, E. N., Jürgenliemk-Schulz, I. M., & Raaymakers, B. W. (2019). Adaptive radiotherapy: The Elekta Unity MR-linac concept. Clinical and Translational Radiation Oncology. https://doi.org/10.1016/j.ctro.2019.04.001
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.