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000168316 1001_ $$0P:(DE-He78)5c8b2018cd142f209c828d91e37a3e1a$$aNiebuhr, Nina Isabelle$$b0$$eFirst author$$udkfz
000168316 245__ $$aBiologically consistent dose accumulation using daily patient imaging.
000168316 260__ $$aLondon$$bBioMed Central$$c2021
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000168316 520__ $$aThis work addresses a basic inconsistency in the way dose is accumulated in radiotherapy when predicting the biological effect based on the linear quadratic model (LQM). To overcome this inconsistency, we introduce and evaluate the concept of the total biological dose, bEQDd.Daily computed tomography imaging of nine patients treated for prostate carcinoma with intensity-modulated radiotherapy was used to compute the delivered deformed dose on the basis of deformable image registration (DIR). We compared conventional dose accumulation (DA) with the newly introduced bEQDd, a new method of accumulating biological dose that considers each fraction dose and tissue radiobiology. We investigated the impact of the applied fractionation scheme (conventional/hypofractionated), uncertainties induced by the DIR and by the assigned α/β-value.bEQDd was systematically higher than the conventionally accumulated dose with difference hot spots of 3.3-4.9 Gy detected in six out of nine patients in regions of high dose gradient in the bladder and rectum. For hypofractionation, differences are up to 8.4 Gy. The difference amplitude was found to be in a similar range to worst-case uncertainties induced by DIR and was higher than that induced by α/β.Using bEQDd for dose accumulation overcomes a potential systematic inaccuracy in biological effect prediction based on accumulated dose. Highest impact is found for serial-type late responding organs at risk in dose gradient regions and for hypofractionation. Although hot spot differences are in the order of several Gray, in dose-volume parameters there is little difference compared with using conventional or biological DA. However, when local dose information is used, e.g. dose surface maps, difference hot spots can potentially change outcomes of dose-response modelling and adaptive treatment strategies.
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000168316 650_7 $$2Other$$aDelivered dose
000168316 650_7 $$2Other$$aDose accumulation
000168316 650_7 $$2Other$$aImage guidance
000168316 650_7 $$2Other$$aLinear quadratic model
000168316 650_7 $$2Other$$aNormal tissue response
000168316 650_7 $$2Other$$aRadiobiology
000168316 7001_ $$0P:(DE-He78)1f74df58d1c0f7b55b5caa01e6c7f806$$aSplinter, Mona$$b1$$udkfz
000168316 7001_ $$0P:(DE-He78)a9a6232a4fccf84da58752c9cc24be23$$aBostel, Tilman$$b2$$udkfz
000168316 7001_ $$0P:(DE-He78)102624aca75cfe987c05343d5fdcf2fe$$aSeco, Joao$$b3$$udkfz
000168316 7001_ $$aHentschke, Clemens M$$b4
000168316 7001_ $$0P:(DE-He78)f0ab09cfecf353f363bab4cc983de95d$$aFloca, Ralf O$$b5$$udkfz
000168316 7001_ $$0P:(DE-He78)c59ff25b48c192ed3fd4ad3a4bc9b9c0$$aHörner-Rieber, Juliane$$b6$$udkfz
000168316 7001_ $$aAlber, Markus$$b7
000168316 7001_ $$0P:(DE-He78)3291aaac20f3d603d96744c1f0890028$$aHuber, Peter$$b8$$udkfz
000168316 7001_ $$0P:(DE-He78)8d52e7ff1ccaac7dbf0232fdcb0168bd$$aNicolay, Nils H$$b9$$udkfz
000168316 7001_ $$0P:(DE-He78)435853c50cec6666e13c237685053577$$aPfaffenberger, Asja$$b10$$eLast author$$udkfz
000168316 773__ $$0PERI:(DE-600)2224965-5$$a10.1186/s13014-021-01789-3$$gVol. 16, no. 1, p. 65$$n1$$p65$$tRadiation oncology$$v16$$x1748-717X$$y2021
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