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Optimization of radiation therapy planning using physical and biological objective functions
Stockholm University, Faculty of Science, Medical Radiation Physics (together with KI).
1992 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of radiation therapy is to eradicate all clonogenic tumour cells without causing severeinjury in normal tissues. Optimization of treatment planning means finding the most preferabletreatment prescription. During the recent years new methods for optimization that aim at solving theinverse problem in radiation therapy have been developed. In contrast to classical optimization,where only a limited number of degrees of freedom are considered, such as beam weights andangles of incidence, the recently developed techniques work with a larger number of degrees offreedom. In radiation therapy the objective function subject to optimization can be either physical orbiological. In this work optimization is performed using both physical and biological objectivefunctions. Biological models that describe the response of tumours and normal tissues toheterogeneous dose delivery have been developed. Optimization is performed by maximizing theprobability of achieving complication free tumour control. The accuracy and applicability ofbiological optimization are dependent on accurate radiation response data. Clinical data is alreadyavailable for many organs and tumours. Biological optimization is a promising line of development,and will probably dominate treatment planning in the future.

Place, publisher, year, edition, pages
Stockholm: Stockholm University, 1992. , p. 40
National Category
Medical and Health Sciences
Research subject
Radiation Physics
Identifiers
URN: urn:nbn:se:su:diva-163289Libris ID: 7610759ISBN: 91-7153-011-8 (print)OAI: oai:DiVA.org:su-163289DiVA, id: diva2:1273101
Public defence
1992-05-11, Radiumhemmets föreläsningssal, Karolinska sjukhuset, Stockholm, 09:15
Note

Härtill 7 uppsatser

Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2018-12-20Bibliographically approved

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