000069748 001__ 69748
000069748 005__ 20190709135546.0
000069748 0247_ $$2doi$$a10.1259/bjr.20170400
000069748 0248_ $$2sideral$$a104854
000069748 037__ $$aART-2017-104854
000069748 041__ $$aeng
000069748 100__ $$aPizarro, F.
000069748 245__ $$aOptimization of radiotherapy fractionation schedules based on radiobiological functions
000069748 260__ $$c2017
000069748 5060_ $$aAccess copy available to the general public$$fUnrestricted
000069748 5203_ $$aObjective: To present a method for optimizing radiotherapy fractionation schedules using radiobiological tools and taking into account the patients dose-volume histograms (DVH). Methods: This method uses a figure of merit based on the uncomplicated tumour control probability (P+) and the generalized equivalent uniform dose (gEUD). A set of doses per fraction is selected in order to find the dose per fraction and the total dose, thus maximizing the figure of merit and leading to a biologically effective dose that is similar to the prescribed schedule. Results: As a clinical example, a fractionation schedule for a prostate treatment plan is optimized and presented herein. From a prescription schedule of 70 Gy/35 × 2 Gy, the resulting optimal schema, using a figure of merit which only takes into account P+, is 54.4 Gy/16 × 3.4 Gy. If the gEUD is included in that figure of merit, the result is 65 Gy/26 × 2.5 Gy. Alternative schedules, which include tumour control probability (TCP) and the normal tissue complication probability (NTCP) values are likewise shown. This allows us to compare different schedules instead of solely finding the optimal value, as other possible clinical factors must be taken into account to make the best decision for treatment. Conclusion: The treatment schedule can be optimized for each patient through radiobiological analysis. The optimization process shown below offers physicians alternative schedules that meet the objectives of the prescribed radiotherapy. Advances in knowledge: This article provides a simple, radiobiological-function-based method to take advantage of a patient''s dose-volume histograms in order to better select the most suitable treatment schedule.
000069748 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000069748 590__ $$a1.814$$b2017
000069748 591__ $$aRADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING$$b76 / 127 = 0.598$$c2017$$dQ3$$eT2
000069748 592__ $$a0.729$$b2017
000069748 593__ $$aRadiology, Nuclear Medicine and Imaging$$c2017$$dQ2
000069748 593__ $$aMedicine (miscellaneous)$$c2017$$dQ2
000069748 655_4 $$ainfo:eu-repo/semantics/conferenceObject$$vinfo:eu-repo/semantics/publishedVersion
000069748 700__ $$0(orcid)0000-0002-4188-4151$$aHernández, A.$$uUniversidad de Zaragoza
000069748 7102_ $$11010$$2770$$aUniversidad de Zaragoza$$bDpto. Pediatría Radiol.Med.Fís$$cÁrea Radiol. y Medicina Física
000069748 773__ $$g90, 1079 (2017), 20170400 [5 pp]$$pBr. j. radiol.$$tBRITISH JOURNAL OF RADIOLOGY$$x0007-1285
000069748 8564_ $$s313705$$uhttps://zaguan.unizar.es/record/69748/files/texto_completo.pdf$$yVersión publicada
000069748 8564_ $$s103250$$uhttps://zaguan.unizar.es/record/69748/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000069748 909CO $$ooai:zaguan.unizar.es:69748$$particulos$$pdriver
000069748 951__ $$a2019-07-09-12:09:27
000069748 980__ $$aARTICLE