Literature DB >> 28741600

Coverage-based constraints for IMRT optimization.

H Mescher1, S Ulrich, M Bangert.   

Abstract

Radiation 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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Year:  2017        PMID: 28741600     DOI: 10.1088/1361-6560/aa8132

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  2 in total

1.  Probabilistic optimization of dose coverage in radiotherapy.

Authors:  David Tilly; Åsa Holm; Erik Grusell; Anders Ahnesjö
Journal:  Phys Imaging Radiat Oncol       Date:  2019-04-13

2.  Novel adaptive beam-dependent margins for additional OAR sparing.

Authors:  H S Tsang; C P Kamerling; P Ziegenhein; S Nill; U Oelfke
Journal:  Phys Med Biol       Date:  2018-10-29       Impact factor: 3.609

  2 in total

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