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000128101 0247_ $$2doi$$a10.1088/1361-6560/aa8132
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000128101 0247_ $$2ISSN$$a1361-6560
000128101 037__ $$aDKFZ-2017-04123
000128101 041__ $$aeng
000128101 082__ $$a570
000128101 1001_ $$0P:(DE-He78)c2ae1305c3f54907b473d564b973e424$$aMescher, Henning$$b0$$eFirst author$$udkfz
000128101 245__ $$aCoverage-based constraints for IMRT optimization.
000128101 260__ $$aBristol$$bIOP Publ.$$c2017
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000128101 520__ $$aRadiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities [Formula: see text] of covering a specific target volume fraction [Formula: see text] with a certain dose [Formula: see text]. Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.
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000128101 7001_ $$0P:(DE-He78)84f1e7432f32ce7df9064fa665afc191$$aUlrich, S.$$b1$$udkfz
000128101 7001_ $$0P:(DE-He78)fec480a99b1869ec73688e95c2f0a43b$$aBangert, Mark$$b2$$eLast author$$udkfz
000128101 773__ $$0PERI:(DE-600)1473501-5$$a10.1088/1361-6560/aa8132$$gVol. 62, no. 18, p. N460 - N473$$n18$$pN460 - N473$$tPhysics in medicine and biology$$v62$$x1361-6560$$y2017
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000128101 9141_ $$y2017
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