Proton range shift analysis on brain pseudo-CT generated from T1 and T2 MR

References

• Schmidt MA, Payne GS. Radiotherapy planning using MRI. Phys Med Biol. 2015;60:323–361.
   PubMed Web of Science ®Google Scholar
• Dean CJ, Sykes JR, Cooper RA, et al. An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients. Br J Radiol. 2012;85:61–68.
   PubMed Web of Science ®Google Scholar
• Djan I, Petrovic B, Erak M, et al. Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation. Vojnosanit Pregl. 2013;70:735–739.
   PubMed Web of Science ®Google Scholar
• Edmund JM, Nyholm T. A review of substitute CT generation for MRI-only radiation therapy. Radiat Oncol. 2017;12:28.
   PubMed Web of Science ®Google Scholar
• Izquierdo-Garcia D, Catana C. MR imaging-guided attenuation correction of PET data in PET/MR imaging. PET Clin. 2016;11:129–149.
   PubMed Web of Science ®Google Scholar
• Oborn BM, Dowdell S, Metcalfe PE. Future of medical physics: real-time MRI-guided proton therapy. Med Phys. 2017;26:05.
   Google Scholar
• Korhonen J, Kapanen M, Keyrilainen J, et al. A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer. Med Phys. 2014;41:011704.
   PubMed Web of Science ®Google Scholar
• Johansson A, Karlsson M, Nyholm T. CT substitute derived from MRI sequences with ultrashort echo time. Med Phys. 2011;38:2708–2714.
   PubMed Web of Science ®Google Scholar
• Catana C, van der Kouwe A, Benner T, et al. Toward implementing an MRI-based PET attenuation–correction method for neurologic studies on the MR-PET brain prototype. J Nucl Med. 2010;51:1431–1438.
   PubMed Web of Science ®Google Scholar
• Edmund JM, Kjer HM, Leemput KV, et al. A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times. Phys Med Biol. 2014;59:7501–7519.
   PubMed Web of Science ®Google Scholar
• Sjolund J, Forsberg D, Andersson M, et al. Generating patient specific pseudo-CT of the head from MR using atlas-based regression. Bull Am Meteor Soc. 2015;60:825–839.
   Google Scholar
• Dowling JA, Lambert J, Parker J, et al. An atlas-based electron density mapping method for magnetic resonance imaging (MRI)-alone treatment planning and adaptive MRI-based prostate radiation therapy. Int J Radiat Oncol Biol Phys. 2012;83:E5–E11.
   PubMed Web of Science ®Google Scholar
• Izquierdo-Garcia D, Hansen AE, Förster S, et al. An SPM8-based approach for attenuation correction combining segmentation and nonrigid template formation: application to simultaneous PET/MR brain imaging. J Nucl Med. 2014;55:1825–1830.
   PubMed Web of Science ®Google Scholar
• Hofmann M, Pichler B, Scholkopf B, et al. Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques. Eur J Nucl Med Mol Imaging. 2009;36:93–104.
   Web of Science ®Google Scholar
• Wagenknecht G, Kaiser HJ, Mottaghy FM, et al. MRI for attenuation correction in PET: methods and challenges. Magn Reson Mater Phy. 2013;26:99–113.
   Web of Science ®Google Scholar
• Chen KT, Izquierdo-Garcia D, Poynton CB. On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners. Eur J Nucl Med Mol Imaging. 2017;44:398–407.
   PubMed Web of Science ®Google Scholar
• Johnstone H, Wyatt JJ, Henry AM, et al. Systematic review of synthetic computed tomography generation methodologies for use in magnetic resonance imaging – only radiation therapy. Int J Radiat Oncol Biol Physi. 2018;100:199–217.
   PubMed Web of Science ®Google Scholar
• Bae WC, Chen PC, Chung CB, et al. Quantitative ultrashort echo time (UTE) MRI of human cortical bone: correlation with porosity and biomechanical properties. J Bone Miner Res. 2012;4:848–857.
   Google Scholar
• Arabi H, Koutsovelis N, Rouzaud M, et al. Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning. Phys Med Biol. 2016; 61:6531–6552.
   PubMed Web of Science ®Google Scholar
• Andreasen D, Van Leemput K, Hansen RH, et al. Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain. Med Phys. 2015;42:1596–1605.
   PubMed Web of Science ®Google Scholar
• Rank CM, Hunemohr N, Nagel AM, et al. MRI-based simulation of treatment plans for ion radiotherapy in the brain region. Radiother Oncol. 2013;109:414–418.
   PubMed Web of Science ®Google Scholar
• Rank CM, Tremmel C, Hunemohr N, et al. MRI-based treatment plan simulation and adaptation for ion radiotherapy using a classification-based approach. Radiat Oncol. 2013;8:51.
   PubMed Web of Science ®Google Scholar
• Zheng W, Kim JP, Kadbi M, et al. Magnetic resonance-based automatic air segmentation for generation of synthetic computed tomography scans in the head region. Int J Radiat Oncol Biol Phys. 2015;93:497–506.
   PubMed Web of Science ®Google Scholar
• Koivula L, Wee L, Korhonen Feasibility of MRI-only treatment planning for proton therapy in brain and prostate cancers: dose calculation accuracy in substitute CT images. Med Phys. 2016;43:4634–4642.
   PubMed Web of Science ®Google Scholar
• Knopf AC, Lomax A. In vivo proton range verification: a review. Phys Med Biol. 2013;58:R131–R160.
   PubMed Web of Science ®Google Scholar
• Seco J, Panahandeh HR, Westover K, et al. Treatment of non-small cell lung cancer patients with proton beam-based stereotactic body radiotherapy: dosimetric comparison with photon plans highlights importance of range uncertainty. Int J Radiat Oncol Biol Phys. 2012;83:354–361.
   PubMed Web of Science ®Google Scholar
• Sharp G, Li R, Wolfgang J, et al. Plastimatch-an open source software suite for radiotherapy image processing. Proceedings of XVIth International Conference on the Use of Computers in Radiotherapy (ICCR). Amsterdam, Netherlands; 2010. p. 7.
   Google Scholar
• Shickleford J, Shusharina N, Verberg J, et al. Plastimatch 1.6: current capabilities and future directions. Proceedings of MICCAI 2012 Image-Guidance and Multimodal Dose Planning in Radiation Therapy Workshop. Nice, France 2012.
   Google Scholar
• Paganetti H. Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol. 2012;57:R99–R117.
   PubMed Web of Science ®Google Scholar
• Mackin D, Zhu XR, Poenisch F, et al. Spot-scanning proton therapy patient specific quality assurance: results from 309 treatment plans. Int J Particle Therapy. 2014;1:711–720.
   Google Scholar
• Raaymakers BW, Jürgenliemk-Schulz IM, Bol GH, et al. First patients treated with a 1.5 T MRI-Linac: clinical proof of concept of a high-precision, high-field MRI guided radiotherapy treatment. Phys Med Biol. 2017;62:23L41–23L50.
   Web of Science ®Google Scholar
• Acharya S, Fischer-Valuck BW, Kashani R, et al. Online magnetic resonance image guided adaptive radiation therapy: first clinical applications. Int J Radiat Oncol Biol Phys. 94:394–403.
   PubMed Web of Science ®Google Scholar
• Huang Y, Parra LC. Fully automated whole-head segmentation with improved smoothness and continuity, with theory reviewed. PLoS One. 2015;10:e0125477.
   Web of Science ®Google Scholar
• Penny W, Friston K, Ashburner J, et al. Statistical Parametric Mapping: the analysis of functional brain images. 1st ed. Oxford (UK): Academic Press; 2006. p. 696.
   Google Scholar
• Halle M, Talos IF, Jakab M, et al. Multi-modality MRI-based Atlas of the brain. SPL 2017 Jan.
   Google Scholar