The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
New developments in MRI for target volume delineation in radiotherapy
Abstract
MRI is being increasingly used in oncology for staging, assessing tumour response and also for treatment planning in radiotherapy. Both conformal and intensity-modulated radiotherapy requires improved means of defining target volumes for treatment planning in order to achieve its intended benefits. MRI can add to the radiotherapy treatment planning (RTP) process by providing excellent and improved characterization of soft tissues compared with CT. Together with its multiplanar capability and increased imaging functionality, these advantages for target volume delineation outweigh its drawbacks of lacking electron density information and potential image distortion. Efficient MR distortion assessment and correction algorithms together with image co-registration and fusion programs can overcome these limitations and permit its use for RTP. MRI developments using new contrast media, such as ultrasmall superparamagnetic iron oxide particles for abnormal lymph node identification, techniques such as dynamic contrast enhanced MRI and diffusion MRI to better characterize tissue and tumour regions as well as ultrafast volumetric or cine MR sequences to define temporal patterns of target and organ at risk deformity and variations in spatial location have all increased the scope and utility of MRI for RTP. Information from these MR developments may permit treatment individualization, strategies of dose escalation and image-guided radiotherapy. These developments will be reviewed to assess their current and potential use for RTP and precision high dose radiotherapy.
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Cites
Mazzara, G. P., Velthuizen, R. P., Pearlman, J. L., Greenberg, H. M., & Wagner, H. (2004) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2004.01.026 · Cited by 216
Diffusion-weighted MRI of soft tissue tumours
Einarsd�ttir, H., Karlsson, M., Wejde, J., & Bauer, H. C. F. (2004) · European Radiology · doi:10.1007/s00330-004-2237-0 · Cited by 199
Cited by
Weinstein, J. S., Varallyay, C. G., Dosa, E., Gahramanov, S., Hamilton, B., Rooney, W. D., Muldoon, L. L., & Neuwelt, E. A. (2010) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2009.192 · Cited by 500
Dimopoulos, J. C. A., Petrow, P., Tanderup, K., Petric, P., Berger, D., Kirisits, C., Pedersen, E. M., van Limbergen, E., Haie-Meder, C., & Pötter, R. (2012) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2011.12.024 · Cited by 440
Generating synthetic CTs from magnetic resonance images using generative adversarial networks
Emami, H., Dong, M., Nejad‐Davarani, S. P., & Glide‐Hurst, C. K. (2018) · Medical Physics · doi:10.1002/mp.13047 · Cited by 300
Nyholm, T., Svensson, S., Andersson, S., Jonsson, J., Sohlin, M., Gustafsson, C., Kjellén, E., Söderström, K., Albertsson, P., Blomqvist, L., et al. (2018) · Medical Physics · doi:10.1002/mp.12748 · Cited by 104
Metadata
- Authors
- Khoo, V. S., & Joon, D. L.
- Venue
- The British Journal of Radiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-09
- Volume
- 79
- Issue
- special_issue_1
- Pages
- S2-S15
- ISSN
- 0007-1285 (ISSN-L)
- 1748-880X
- OpenAlex
- W2081420220
- Cited by
- 207
- References
- 2
- FWCI
- 6.85
- Type
- journal article
- Language
- en
- Open access
- closed
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