Suzuki M, Nishimura Y, Nakamatsu K, et al. Analysis of interfractional set-up errors and intrafractional organmotions during IMRT for head and neck tumors to define an appropriate planning target volume (PTV)- and planning organs at risk volume (PRV)-margins. Radiother Oncol. 2006;78:283–90.
Oehler C, Lang S, Dimmerling P, et al. PTV margin definition in hypofractionated IGRT of localized prostate cancer using cone beam CT and orthogonal image pairs with fiducial markers. Radiat Oncol. 2014;9:229.
Van Herk M. Errors and margins in radiotherapy. Semin Radiat Oncol. 2004;14:52–64.
Stroom JC, de Boer HC, Huizenga H, et al. Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability. Int J Radiat Oncol Biol Phys. 1999;43:905–19.
Huang K, Palma DA, Scott D, et al. Inter- and intrafraction uncertainty in prostate bed image-guided radiotherapy. Int J Radiat Oncol Biol Phys. 2011;84(2):402–7.
Ost P, De Meerleer G, De Gersem W, et al. Analysis of prostate bed motion using daily cone-beam computed tomography during postprostatectomy radiotherapy. Int J Radiat Oncol Biol Phys. 2011;79(1):188–94.
Mayyas E, Chetty IJ, Chetvertkov M, Wen N, et al. Evaluation of multiple image-based modalities for image-guided radiation therapy (IGRT) of prostate carcinoma: a prospective study. Med Phys. 2013;40:041707.
Piotrowski T, Kaczmarek K, Bajon T, et al. Evaluation of image-guidance strategies for prostate cancer. Technol Cancer Res Treat. 2014;13(6):583–91.
Fast MF, Krauss A, Oelfke U, Nill S. Position detection accuracy of a novel linac-mounted intrafractional x-ray imaging system. Med Phys. 2012a; 39:109–118.
Faddegon BA, Wu V, Pouliot J, et al. Low dose megavoltage cone beam computed tomography with an unflattened 4MV beam from a carbon target. Med Phys. 2008;35(12):5777–86.
Ostapiak OZ, O’Brien PF, Faddegon BA. Megavoltage imaging with low Z targets: Implementation and characterization of an investigational system. Med Phys. 1998;25:1910–8.
Akino Y, Koizumi M, Sumida I, et al. Megavoltage cone beam computed tomography dose and the necessity of reoptimization for imaging dose-integrated intensity-modulated radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys. 2012;82:1715–22.
Amer A, Marchant T, Sykes J, et al. Imaging doses from the Elekta Synergy X-ray cone beam CT system. Brit J Radiol. 2007;80:476–82.
Beltran C, Lukose R, Gangadharan B, et al. Image quality & dosimetric property of an investigational imaging beam line MV-CBCT. J App Clin Med Phys. 2009;10:3023.
Ariyante H, Chesham H, Pettingell J, et al. Image-guided radiotherapy for prostate cancer with cone beam CT: dosimetric effects of imaging frequency and PTV margin. Radiother Oncol. 2016;121(1):103–8.
Schneider U, Hälg R, Besserer J. Concept for quantifying the dose from image guided radiotherapy. Radiat Oncol. 2015;10:188.
Dzierma Y, Ames E, Nuesken F, et al. Image quality and dose distributions of three linac-based imaging modalities. Strahlenther Onkol. 2015;191:365–74.
Alaei P, Spezi E. Commissioning kilovoltage cone-beam CT beams in a radiation therapy treatment planning system. J App Clin Med Phys. 2012;13:19–33.
Alaei P, Ding G, Guan H. Inclusion of the dose from kilovoltage cone beam CT in the radiation therapy treatment plans. Med Phys. 2012;37:244–8.
Alaei P, Spezi E, Reynolds M. Dose calculation and treatment plan optimization including imaging dose from kilovoltage cone beam computed tomography. Acta Oncol. 2014;53(6):839–44.
Alaei P, Spezi E. Imaging dose from cone beam computed tomography in radiation therapy. Phys Med. 2015;31(7):647–58.
Dzierma Y, Beys M, Palm J, et al. Set-up errors and planning margins in planar and CBCT image-guided radiotherapy using three different imaging systems: a clinical study for prostate and head-and-neck cancer. Phys Med. 2015;31(8):1055–9.
Dzierma Y, Nuesken F, Licht NP, Ruebe C. Dosimetric properties and commissioning of cone-beam CT image beam line with a carbon target. Strahlenther Onkol. 2013;189:566–72.
Dzierma Y, Nuesken F, Otto W, et al. Dosimetry of an in-line kilovoltage imaging system and implementation in treatment planning. Int J Radiat Oncol Biol Phys. 2014;88(4):913–9.
Källman P, Agren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol. 1992;62(2):249–62.
Löf J. Development of a general framework for optimization of radiation therapy. PhD thesis. Stockholm: Stockholm University; 2000.
Gulliford S, Partridge M, Sydes M, et al. Parameters for the Lyman Kutcher Burman (LKB) model of normal tissue complication probability (NTCP for specific rectal complications observed in clinical pratise. Radiother Oncol. 2012;102:347–51.
Philips Medical Systems. Pinnacle3 version 9.2. Treatment planning system, Plan evaluation tools. 2015. p. 40.
Schaake W, Van der Schaaf A, van Dijk L, et al. Normal tissue complication probability (NTCP) models for late rectal bleeding, stool frequency and fecal incontinence after radiotherapy in prostate cancer patients. Radiother Oncol. 2016;119:381–7.
Rancati T, Fiori C, Fellin G, et al. Inclusion of clinical risk factors into NTCP modelling of late rectal toxicity after high dose radiotherapy for prostate cancer. Radiother Oncol. 2011;100:124–30.
Defranene G, van den Bergh L, Al-Mamgani A, et al. The benefits of including clinical factors in rectal normal tissue complication probability modeling after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys. 2012;82(3):1233–42.
Kumar AS, Singh IR, Sharma SD, et al. Radiation dose measurements during kilovoltage-cone beam computed tomography imaging in radiotherapy. J Cancer Res Ther. 2016;12(2):858–63.