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- Olsson, Caroline, 1970
(författare)
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Radiation Oncology Data and Modelling Side Effects after Radiation Therapy
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Although modern radiation therapy techniques have the ability to conform the dose distribution of ionizing radiation tightly around the volume to be treated, unwanted irradiation to surrounding organs remains a problem. The probability of a side effect arising in the normal tissue of a patient after radiation therapy can be modelled by sigmoid mathematical functions known as normal tissue complication probability (NTCP) models. Using statistical methods, these are fitted to input data representing the absence or presence of a studied symptom associated with the side effect in question and the dose distribution for potentially injured organs. NTCP models are increasingly being used in the clinic both for treatment evaluation and to guide optimization algorithms for inverse treatment planning although their predictions are associated with uncertainties to varying degrees. The purpose of this thesis is to investigate how different means to represent dose and ways to grade side effects contribute to uncertainties in radiation therapy side effect modelling. Using concepts from the literature and results from two recent Swedish studies including data on parotid gland complications in head and neck cancer patients and pubic bone pain in gynaecological cancer patients, respectively, current generations and representations of dose and side effect data and how these are used in modelling side effects are surveyed. Using similarities and differences in the data by the literature and these two studies, it is concluded that dose data for modelling purposes today is described by dose-volume histograms but can be made more detailed using a three-dimensional format like the structure-specific dose matrix as introduced in this thesis with additional information on dose representation. Side effect data are described by different scales to grade the same or similar symptoms, but also need to include information on factors which may influence modelling results such as effect-modifying factors as well as baseline symptom frequencies in non-irradiated individuals. Altogether, 15 items that capture the essential information needed for radiation therapy side effect modelling are identified, and the outlook for data integration and interoperability in radiation oncology would be improved by using these to form a semantic basis for this domain.
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- Olsson, Caroline, 1970
(författare)
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Predicting Normal Tissue Complications after External Beam Radiation Therapy
- 2010
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Although modern external beam radiation (EBRT) therapy has the ability to conform the dose tightly around the volume to be treated, unwanted irradiation to surrounding normal tissue is still a problem. The probability of a side effect arising in normal tissue after EBRT is commonly modelled by an s-shaped dose-volume response curve where dose or volume are plotted against response (i.e. the frequency with which the side effect occurs). The models are based on sigmoid mathematical functions and are fitted to input data representing the outcome (absence or presence of the studied symptom associated with the side effect) and the dose distribution for potentially injured organs using statistical methods. The purpose of this thesis is to give an overview of the current forms of outcome and dose data, how they are generated and used to model side effects today, some of their limitations, and potential future directions. The results are based on concepts from the literature as well as from the three appended papers. The first two present questionnaire-collected outcome data and 2D dose-volume histogram data of the pubic bone for 650 long-term gynecological cancer survivors treated with pelvic radiation therapy between 1991 and 2003 where one in every ten women reported pubic bone pain. The mean dose to the pubic bone proved critical for pain occurrence and the risk to experience pubic bone pain two or more years after pelvic radiation therapy is expected to be 5 % for a mean absorbed dose of 25 Gy. The third paper presents dose differences between non-corrected and fractionation-corrected combined doses in sequential two-phase treatments using 16 combined dose distributions over a model organ at risk (OAR) “irradiated” with a conventional fractionation schedule (2 Gy per fraction; 46 Gy + 22 Gy). Dose differences up to 6 Gy (50 % of a reference total dose
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- Gurjar, Mrugaja, 1997, et al.
(författare)
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Automated data extraction tool (DET) for external applications in radiotherapy.
- 2023
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Ingår i: Technical innovations & patient support in radiation oncology. - : Elsevier BV. - 2405-6324. ; 25
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Tidskriftsartikel (refereegranskat)abstract
- Oncological Information Systems (OIS) manage information in radiotherapy (RT) departments. Due to database structure limitations, stored information can rarely be directly used except for vendor-specific purposes. Our aim is to enable the use of such data in various external applications by creating a tool for automatic data extraction, cleaning and formatting.We used OIS data from a nine-linac RT department in Sweden (70weeks, 2015-16). Extracted data included patients' referrals and appointments with details for RT sub-tasks. The data extraction tool to prepare the data for external use was built in C# programming language. It used excel-automation queries to remove unassigned/duplicated values, substitute missing data and perform application-specific calculations. Descriptive statistics were used to verify the output with the manually prepared dataset from the corresponding time period.From the initial raw data, 2030 (51%)/907 (23%) patients had known curative and palliative treatment intent for 84 different cancer diagnoses. After removal of incomplete entries, 373 (10%) patients had unknown treatment intents which were substituted based on the known curative/palliative ratio. Automatically- and manuallyprepared datasets differed<1% for Mould, Treatment planning, Quality assurance and±5% for Fractions and Magnetic resonance imaging with overestimations in 80/140 (57%) entries by the tool.We successfully implemented a software tool to prepare ready-to-use OIS datasets for external applications. Our evaluations showed overall results close to the manually-prepared dataset. The time taken to prepare the dataset using our automated strategy can reduce the time for manual preparation from weeks to seconds.
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- Larsson, Torbjörn, et al.
(författare)
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Convergent Lagrangian heuristics for nonlinear minimum cost network flows
- 2008
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Ingår i: European Journal of Operational Research. - : Elsevier BV. - 0377-2217 .- 1872-6860. ; 189:2, s. 324-346
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Tidskriftsartikel (refereegranskat)abstract
- We consider the separable nonlinear and strictly convex single-commodity network flow problem (SSCNFP). We develop a computational scheme for generating a primal feasible solution from any Lagrangian dual vector, this is referred to as "early primal recovery". It is motivated by the desire to obtain a primal feasible vector before convergence of a Lagrangian scheme, such a vector is not available from a Lagrangian dual vector unless it is optimal. The scheme is constructed such that if we apply it from a sequence of Lagrangian dual vectors that converge to an optimal one, then the resulting primal (feasible) vectors converge to the unique optimal primal flow vector. It is therefore also a convergent Lagrangian heuristic, akin to those primarily devised within the field of combinatorial optimization but with the contrasting and striking advantage that it is guaranteed to yield a primal optimal solution in the limit. Thereby we also gain access to a new stopping criterion for any Lagrangian dual algorithm for the problem, which is of interest in particular if the SSCNFP arises as a subproblem in a more complex model. We construct instances of convergent Lagrangian heuristics that are based on graph searches within the residual graph, and therefore are efficiently implementable, in particular we consider two shortest path based heuristics that are based on the optimality conditions of the original problem. Numerical experiments report on the relative efficiency and accuracy of the various schemes. © 2007 Elsevier B.V. All rights reserved.
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