Abstract
Magnetic Resonance Imaging (MRI) has been a part of radiation therapy for many years, but its role is expanding. MR provides soft tissue contrast that is superior to what can be obtained with computed tomography (CT), the modality used most often to support radiation therapy treatment simulation. There are a number of critical challenges to employing MR for simulation imaging, namely the reduced spatial fidelity, and the lack of a direct relationship between MR image values and electron density, a quantity needed for dose calculations, as well as a difference between MR image values and the attenuation of kV X-rays, used to aid in patient positioning. These challenges are being met by clinics and companies, to the extent that the exclusive use of MR for simulation is now possible in a number of treatment sites. While MR has been used for simulation, it has only recently been introduced into the treatment room. Integrating MR with patient positioning and monitoring before and during treatment, respectively, would potentially improve radiation therapy treatment accuracy, enabling tighter uncertainty margins and ultimately improving outcomes. The challenges of integrating a MRI system with radiation treatment delivery have been recently met by radiation therapy equipment manufacturers, providing the radiation oncology community with an opportunity to deliver radiation doses with unparalleled accuracy.
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References
Chen LL, Price RA, Wang L, Li JS, Qin LH, McNeeley S, Ma CMC, Freedman GM, Pollack A (2004a) MRI-based treatment planning for radiotherapy: dosimetric verification for prostate IMRT. Int J Radiat Oncol Biol Phys 60:636–647
Chen L, Price RA, Nguyen TB, Wang L, Li JS, Qin L, Ding M, Palacio E, Ma CM, Pollack A (2004b) Dosimetric evaluation of MRI-based treatment planning for prostate cancer. Phys Med Biol 49:5157–5170
Devic S (2012) MRI simulation for radiotherapy treatment planning. Med Phys 39:6701–6711
Eilertsen K, Vestad LNTA, Geier O, Skretting A (2008) A simulation of MRI based dose calculations on the basis of radiotherapy planning CT images. Acta Oncol 47:1294–1302
Fallone BG, Murray B, Rathee S, Stanescu T, Steciw S, Vidakovic S, Blosser E, Tymofichuk D (2009) First MR images obtained during megavoltage photon irradiation from a prototype integrated linac-MR system. Med Phys 36:2084–2088
Huan Y, Caldwell C, Balogh J, Mah K (2014) Toward magnetic resonance-only simulation: segmentation of bone in MR for radiation therapy verification of the head. Int J Radiat Oncol Biol Phys 89:649–657
Jaffray DA, Drake DG, Moreau M, Martinez AA, Wong JW (1999) A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. Int J Radiat Oncol Biol Phys 45:773–789
Jonsson JH, Karlsson MG, Karlsson M, Nyholm T (2010) Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions. Radiat Oncol 5:62
Kapanen M, Collan J, Beule A, Seppala T, Saarilahti K, Tenhunen M (2013) Commissioning of MRI-only based treatment planning procedure for external beam radiotherapy of prostate. Magn Reson Med 70:127–135
Karlsson M, Karlsson MG, Nyholm T, Amies C, Zackrisson B (2009) Dedicated magnetic resonance imaging in the radiotherapy clinic. Int J Radiat Oncol Biol Phys 74:644–651
Kim J, Glide-Hurst C, Doemer A, Wen N, Movsas B, Chetty IJ (2015) Implementation of a novel algorithm for generating synthetic CT images from magnetic resonance imaging data sets for prostate cancer radiation therapy. Int J Radiat Oncol Biol Phys 91:39–47
Kristensen BH, Laursen FJ, Logager V, Geertsen PF, Krarup-Hansen A (2008) Dosimetric and geometric evaluation of an open low-field magnetic resonance simulator for radiotherapy treatment planning of brain tumours. Radiother Oncol 87:100–109
Lagendijk JJW, Raaymakers BW, Raaijmakers AJE, Overweg J, Brown KJ, Kerkhof EM, van der Put RW, Hardemark B, van Vutpen M, van der Heide UA (2008) MRI/linac integration. Radiother Oncol 86:25–29
Lagendijk JJW, Raaymakers BW, Van den Berg CAT, Moerland MA, Philippens ME, van Vulpen M (2014) MR guidance in radiotherapy. Phys Med Biol 59:R349–R369
Lambert J, Greer PB, Menk F, Patterson J, Parker J, Dahl K, Gupta S, Capp A, Wratten C, Tang C, Kumar M, Dowling J, Hauville S, Hughes C, Fisher K, Lau P, Denham JW, Salvado O (2011) MRI-guided prostate radiation therapy planning: investigation of dosimetric accuracy of MRI-based dose planning. Radiother Oncol 98:330–334
Lee YK, Bollet M, Charles-Edwards G, Flower MA, Leach MO, McNair H, Moore E, Rowbottom C, Webb S (2003) Radiotherapy treatment planning of prostate cancer using magnetic resonance imaging alone. Radiother Oncol 66:203–216
Liu L, Cao Y, Fessler JA, Jolly S, Balter JM (2016) A female pelvic bone shape model for air/bone separation in support of synthetic CT generation for radiation therapy. Phys Med Biol 61:169–182
Paulson ES, Erickson B, Schultz C, Li XA (2015) Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning. Med Phys 42:28–39
Petersch B, Bogner J, Fransson A, Lorang T, Potter R (2004) Effects of geometric distortion in 0.2 T MRI on radiotherapy treatment planning of prostate cancer. Radiother Oncol 71:55–64
Prabhakar R, Julka PK, Ganesh T, Munshi A, Joshi RC, Rath GK (2007) Feasibility of using MRI alone for 3D radiation treatment planning in brain tumors. Jpn J Clin Oncol 37:405–411
Price RG, Kim JP, Zheng W, Chetty IJ, Glide-Hurst C (2016) Image guided radiation therapy using synthetic computed tomography images in brain cancer. Int J Radiat Oncol Biol Phys 95:1281–1289
Prior P, Chen X, Botros M, Paulson ES, Lawton C, Erickson B, Li XA (2016) MRI-based IMRT planning for MR-linac: comparison between CT- and MRI-based plans for pancreatic and prostate cancers. Phys Med Biol 61:3819–3842
Ramsey CR, Oliver AL (1998) Magnetic resonance imaging based digitally reconstructed radiographs, virtual simulation, and three-dimensional treatment planning for brain neoplasms. Med Phys 25:1928–1934
Robson MD, Gatehouse PD, Bydder M, Bydder GM (2003) Magnetic resonance: an introduction to ultrashort TE (UTE) imaging. J Comput Assist Tomogr 27:825–846
Schmidt MA, Payne GS (2015) Radiotherapy planning using MRI. Phys Med Biol 60:R323–R361
Yang YM, Geurts M, Smilowitz JB, Sterpin E, Bednarz BP (2015) Monte Carlo simulations of patient dose perturbations in rotational-type radiotherapy due to a transverse magnetic field: a tomotherapy investigation. Med Phys 42:715–725
Yang Y, Cao M, Kaprealian T, Sheng K, Gao Y, Han F, Gomez C, Santhanam A, Tenn S, Agazaryan N, Low DA, Hu P (2016) Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy. Med Phys 43:262–267
Yin FF, Wang Z, Yoo S, Wu QJ, Kirkpatrick J, Larrier N, Meyer J, Willett CG, Marks LB (2008) Integration of cone-beam CT in stereotactic body radiation therapy. Technol Cancer Res Treat 7:133–139
Zheng W, Kim JP, Kadbi M, Movsas B, Chetty IJ, Glide-Hurst CK (2015) magnetic resonance-based automatic air segmentation for generation of synthetic computed tomography scans in the head region. Int J Radiat Oncol Biol Phys 93:497–506
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Low, D.A. (2017). MRI Guided Radiotherapy. In: Wong, J., Schultheiss, T., Radany, E. (eds) Advances in Radiation Oncology. Cancer Treatment and Research. Springer, Cham. https://doi.org/10.1007/978-3-319-53235-6_3
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DOI: https://doi.org/10.1007/978-3-319-53235-6_3
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