<> "The repository administrator has not yet configured an RDF license."^^ . <> . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy"^^ . "The sensitivity of intensity-modulated proton therapy to uncertainties requires case-specific uncertainty\r\nassessment and mitigation. As an alternative to scenario-based methods, this thesis describes\r\nthe implementation, application and conceptual extension of the Analytical Probabilistic\r\nModeling (APM) framework introduced by Bangert, Hennig, and Oelfke (2013). APM represents\r\nmoments of the probability distribution over dose in closed-form, providing a probabilistic analog\r\nto nominal pencil-beam dose calculation subject to range and setup uncertainties that further\r\nenables probabilistic optimization.\r\nFirst, APM was implemented in MITKrad, a treatment planning plugin for MITK built completely\r\nfrom scratch. APM’s computations were validated against sample statistics, showing nearly perfect\r\nagreement. Run-times within minutes could be realized for uncertainty assessment and probabilistic\r\noptimization on patient data.\r\nReformulation of APM enabled linear separation of the computations into random and systematic\r\nuncertainty components. Uncertainty over the full fractionation spectrum could then be\r\nmodeled and optimized with a single pre-computation. It could be shown that fractionation is\r\nexploited in optimization with APM for additional organ at risk sparing.\r\nAPM was then extended to propagation of uncertainties from dose to clinically relevant plan\r\nquality metrics. Expectation and variance could be modeled accurately for organ mean dose and\r\ndose-volume histograms. However, approximations for equivalent uniform dose and minimum\r\nand maximum dose values did not provide reliable results.\r\nFinally, the closed-form plan metrics were used to conceptualize constrained probabilistic optimization.\r\nBesides novel probabilistic objectives, confidence constraints could be established.\r\nDue to increased computational complexity of the new models, the proof-of-concept was provided\r\nthrough evaluations on a one-dimensional prototype anatomy.\r\nIn conclusion, the herein extended APM framework is able to provide probabilistic analogs\r\nto established nominal concepts of dose calculation, plan quality metrics, and constrained optimization.\r\nIf computational hurdles can be overcome in the future, clinical application would be\r\nwithin reach."^^ . "2018" . . . . . . . "Niklas"^^ . "Wahl"^^ . "Niklas Wahl"^^ . . . . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (PDF)"^^ . . . "WahlN_dissertation_public.pdf"^^ . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (Other)"^^ . . . . . . "lightbox.jpg"^^ . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (Other)"^^ . . . . . . "preview.jpg"^^ . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (Other)"^^ . . . . . . "medium.jpg"^^ . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (Other)"^^ . . . . . . "small.jpg"^^ . . . "Analytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy (Other)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #25127 \n\nAnalytical Models for Probabilistic Inverse Treatment Planning in Intensity-modulated Proton Therapy\n\n" . "text/html" . . . "500 Naturwissenschaften und Mathematik"@de . "500 Natural sciences and mathematics"@en . . . "530 Physik"@de . "530 Physics"@en . .