Optimisation in radiotherapy I: defining the problem.
Optimisation in radiotherapy should incorporate a very wide set of variables, including the combinations of dose due to external beam radiotherapy, brachytherapy, internally administered radionuclides and the effects of chemotherapy, surgery, hyperthermia, other biological and chemical defences, alternative treatment techniques, lifestyle and mental state of the patient, the economics of cancer treatment, and consideration of tolerable levels of adverse effects and palliation. A full treatment optimisation would consider the influence and covariance of all these variables and any future techniques, as well as the complex constraints imposed by the biological systems being irradiated. This series of reviews concentrates on optimisation of radiotherapy through the treatment planning component of the treatment process--an area of radiotherapy research that has received a great deal of attention as the attached lists of references will testify. It hopes to provide the medical physics and engineering community (and hopefully the clinical community) with a background into the mathematical bases for the manipulation of radiation for clinical benefit. It also examines the potential benefits of research into these techniques in the light of recent approaches to optimisation in radiotherapy, and provides pointers to more concise accounts in the literature. In this first article, the incentive for radiotherapy optimisation research is established, and the actual radiotherapy optimisation problem (in terms of the manipulation of degrees of freedom in radiation delivery) is defined. The degrees of freedom associated with radiotherapy treatment are identified, and it is shown how these degrees of freedom translate into the mathematical parameters of the problem, including the dose distributions they produce. The constraints and objectives of the problem are also discussed from both physical and radiobiological perspectives. Subsequent articles will consider algorithms for performing the optimisation, their relative utility, and their application in clinical practice.
Ebert
M A
MA
Department of Medical Physics, Royal Perth Hospital, Western Australia. martin.ebert@nero.rph.health.wa.gov.au
D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000532:radiotherapy; D011853:Radiobiology; D011878:Radiotherapy / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted