000131073 001__ 131073
000131073 005__ 20240228145602.0
000131073 0247_ $$2doi$$a10.1088/1361-6560/aa915d
000131073 0247_ $$2pmid$$apmid:28980974
000131073 0247_ $$2ISSN$$a0031-9155
000131073 0247_ $$2ISSN$$a1361-6560
000131073 037__ $$aDKFZ-2017-06140
000131073 041__ $$aeng
000131073 082__ $$a570
000131073 1001_ $$0P:(DE-He78)59c02b7b30ad8972cf422bb1c955956c$$aWieser, Hans-Peter$$b0$$eFirst author$$udkfz
000131073 245__ $$aAnalytical probabilistic modeling of RBE-weighted dose for ion therapy.
000131073 260__ $$aBristol$$bIOP Publ.$$c2017
000131073 3367_ $$2DRIVER$$aarticle
000131073 3367_ $$2DataCite$$aOutput Types/Journal article
000131073 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1525772885_20626
000131073 3367_ $$2BibTeX$$aARTICLE
000131073 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000131073 3367_ $$00$$2EndNote$$aJournal Article
000131073 520__ $$aParticle therapy is especially prone to uncertainties. This issue is usually addressed with uncertainty quantification and minimization techniques based on scenario sampling. For proton therapy, however, it was recently shown that it is also possible to use closed-form computations based on analytical probabilistic modeling (APM) for this purpose. APM yields unique features compared to sampling-based approaches, motivating further research in this context. This paper demonstrates the application of APM for intensity-modulated carbon ion therapy to quantify the influence of setup and range uncertainties on the RBE-weighted dose. In particular, we derive analytical forms for the nonlinear computations of the expectation value and variance of the RBE-weighted dose by propagating linearly correlated Gaussian input uncertainties through a pencil beam dose calculation algorithm. Both exact and approximation formulas are presented for the expectation value and variance of the RBE-weighted dose and are subsequently studied in-depth for a one-dimensional carbon ion spread-out Bragg peak. With V and B being the number of voxels and pencil beams, respectively, the proposed approximations induce only a marginal loss of accuracy while lowering the computational complexity from order [Formula: see text] to [Formula: see text] for the expectation value and from [Formula: see text] to [Formula: see text] for the variance of the RBE-weighted dose. Moreover, we evaluated the approximated calculation of the expectation value and standard deviation of the RBE-weighted dose in combination with a probabilistic effect-based optimization on three patient cases considering carbon ions as radiation modality against sampled references. The resulting global γ-pass rates (2 mm,2%) are [Formula: see text]99.15% for the expectation value and [Formula: see text]94.95% for the standard deviation of the RBE-weighted dose, respectively. We applied the derived analytical model to carbon ion treatment planning, although the concept is in general applicable to other ion species considering a variable RBE.
000131073 536__ $$0G:(DE-HGF)POF3-315$$a315 - Imaging and radiooncology (POF3-315)$$cPOF3-315$$fPOF III$$x0
000131073 588__ $$aDataset connected to CrossRef, PubMed,
000131073 7001_ $$aHennig, P.$$b1
000131073 7001_ $$0P:(DE-He78)dfd5aaf608015baaaed0a15b473f1336$$aWahl, N.$$b2$$udkfz
000131073 7001_ $$0P:(DE-He78)fec480a99b1869ec73688e95c2f0a43b$$aBangert, Mark$$b3$$eLast author$$udkfz
000131073 773__ $$0PERI:(DE-600)1473501-5$$a10.1088/1361-6560/aa915d$$gVol. 62, no. 23$$n23$$p8959-8982$$tPhysics in medicine and biology$$v62$$x1361-6560$$y2017
000131073 909CO $$ooai:inrepo02.dkfz.de:131073$$pVDB
000131073 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)59c02b7b30ad8972cf422bb1c955956c$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000131073 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)dfd5aaf608015baaaed0a15b473f1336$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000131073 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)fec480a99b1869ec73688e95c2f0a43b$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000131073 9131_ $$0G:(DE-HGF)POF3-315$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vImaging and radiooncology$$x0
000131073 9141_ $$y2017
000131073 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000131073 915__ $$0StatID:(DE-HGF)0430$$2StatID$$aNational-Konsortium
000131073 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPHYS MED BIOL : 2015
000131073 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000131073 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000131073 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000131073 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000131073 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000131073 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000131073 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000131073 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000131073 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences
000131073 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000131073 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000131073 9201_ $$0I:(DE-He78)E040-20160331$$kE040$$lMedizinische Physik in der Strahlentherapie$$x0
000131073 980__ $$ajournal
000131073 980__ $$aVDB
000131073 980__ $$aI:(DE-He78)E040-20160331
000131073 980__ $$aUNRESTRICTED