Generation of prescriptions robust against geometric uncertainties in dose painting by numbers

References

• Bentzen SM. Theragnostic imaging for radiation oncology: Dose-painting by numbers. Lancet Oncol 2005;6:112–7.
   PubMed Web of Science ®Google Scholar
• Vanderstraeten B, Duthoy W, De Gersem W, De Neve W, Thierens H.[18F]fluoro-deoxy-glucose positron emission tomography ([18F]FDG-PET) voxel intensity-based intensity-modulated radiation therapy (IMRT) for head-and-neck cancer. Radiother Oncol 2006;79:249–58.
   PubMed Web of Science ®Google Scholar
• Christian N, Lee JA, Bol A, De Bast M, Jordan B, Grégoire V. The limitation of PET imaging for biological adaptive-IMRT assessed in animal models. Radiother Oncol 2009;91:101–6.
   PubMed Web of Science ®Google Scholar
• Tanderup K, Olsen DR, Grau C. Dose painting: Art or science?Radiother Oncol 2006;79:245–8.
   PubMed Web of Science ®Google Scholar
• Aerts HJWL, Lambin P, Ruysscher DD. FDG for dose painting: A rational choice. Radiother Oncol 2010;97:163–4.
   PubMed Web of Science ®Google Scholar
• Witte M, Shakirin G, Houweling A, Peulen H, van Herk M. Dealing with geometric uncertainties in dose painting by numbers: Introducing the ΔVH. Radiother Oncol 2011; 100:402–6.
   PubMed Web of Science ®Google Scholar
• Deveau MA, Bowen SR, Westerly DC, Jeraj R. Feasibility and sensitivity study of helical tomotherapy for dose painting plans. Acta Oncol 2010;49:991–6.
   PubMed Web of Science ®Google Scholar
• Korreman SS, Ulrich S, Bowen S, Deveau M, Bentzen SM, Jeraj R. Feasibility of dose painting using volumetric modulated arc optimization and delivery. Acta Oncol 2010;49: 964–71.
   PubMed Web of Science ®Google Scholar
• van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: Dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys 2000;47:1121–35.
   PubMed Web of Science ®Google Scholar
• Unkelbach J, Oelfke U. Inclusion of organ movements in IMRT treatment planning via inverse planning based on probability distributions. Phys Med Biol 2004;49:4005–29.
   PubMed Web of Science ®Google Scholar
• McShan DL, Kessler ML, Vineberg K, Fraass BA. Inverse plan optimization accounting for random geometric uncertainties with a multiple instance geometry approximation (MIGA). Med Phys 2006;33:1510–21.
   PubMed Web of Science ®Google Scholar
• Witte MG, van der Geer J, Schneider C, Lebesque JV, Alber M, van Herk M. IMRT optimization including random and systematic geometric errors based on the expectation of TCP and NTCP. Med Phys 2007;34:3544–55.
   PubMed Web of Science ®Google Scholar
• Gordon JJ, Sayah N, Weiss E, Siebers JV. Coverage optimized planning: Probabilistic treatment planning based on dose coverage histogram criteria. Med Phys 2010;37:550–63.
   PubMed Web of Science ®Google Scholar
• Mexner V, Wolthaus JWH, van Herk M, Damen EMF, Sonke J-J. Effects of respiration-induced density variations on dose distributions in radiotherapy of lung cancer. Int J Radiat Oncol Biol Phys 2009;74:1266–75.
   PubMed Web of Science ®Google Scholar
• Grégoire V, Coche E, Cosnard G, Hamoir M, Reychler H. Selection and delineation of lymph node target volumes in head and neck conformal radiotherapy. Proposal for standardizing terminology and procedure based on the surgical experience. Radiother Oncol 2000;56:135–50.
   PubMed Web of Science ®Google Scholar
• Grégoire V, Levendag P, Ang KK, Bernier J, Braaksma M, Budach V, et al. CT-based delineation of lymph node levels and related CTVs in the node-negative neck: DAHANCA, EORTC, GORTEC, NCIC, RTOG consensus guidelines. Radiother Oncol 2003;69:227–36.
   PubMed Web of Science ®Google Scholar
• Grégoire V, Eisbruch A, Hamoir M, Levendag P. Proposal for the delineation of the nodal CTV in the node-positive and the post-operative neck. Radiother Oncol 2006;79: 15–20.
   PubMed Web of Science ®Google Scholar
• Geets X, Lee J a, Bol A, Lonneux M, Grégoire V. A gradient-based method for segmenting FDG-PET images: Methodology and validation. Eur J Nucl Med 2007;34: 1427–38.
   Google Scholar
• Chen Q, Lu W, Chen Y, Chen M, Henderson D, Sterpin E. Validation of GPU based TomoTherapy dose calculation engine. Med Phys 2012;39:1877–86.
   PubMed Web of Science ®Google Scholar
• Sterpin E, Salvat F, Olivera GH, Vynckier S. Monte Carlo evaluation of the convolution/superposition algorithm of Hi-ArtTM Tomotherapy in heterogeneous phantoms and clinical cases. Med Phys 2009;36:1566–75
   PubMed Web of Science ®Google Scholar
• Sterpin E, Tomsej M, Cravens B, Salvat F, Ruchala K, Olivera GH, et al. Monte Carlo simulation of the Tomotherapy treatment unit in the static mode using MC HAMMER, a Monte Carlo tool dedicated to Tomotherapy. J Phys: Confer Ser 2007;74:021019.
   Google Scholar
• Boswell S, Tome W, Jeraj R, Jaradat H, Mackie TR. Automatic registration of megavoltage to kilovoltage CT images in helical tomotherapy: An evaluation of the setup verification process for the special case of a rigid head phantom. Med Phys 2006;33:4395–404.
   PubMed Web of Science ®Google Scholar
• Wolthaus JWH, Sonke J-J, van Herk M, Belderbos JS, Rossi MMG, Lebesque JV, et al. Comparison of different strategies to use four-dimensional computed tomography in treatment planning for lung cancer patients. Int J Radiat Oncol Biol Phys 2008;70:1229–38.
   PubMed Web of Science ®Google Scholar
• Sterpin E, Chen Y, Lu W, Mackie TR, Olivera GH, Vynckier S. On the relationships between electron spot size, focal spot size, and virtual source position in Monte Carlo simulations. Med Phys 2011;38:1579–86.
   PubMed Web of Science ®Google Scholar
• McShan DL, Kessler ML, Vineberg K, Fraass B. Inverse plan optimization accounting for random geometric uncertainties with a multiple instance geometry approximation (MIGA). Med Phys 2006;33:1510–21.
   PubMed Web of Science ®Google Scholar