Radioimmunotherapy consists in the use of beta radioactive labeled monoclonal antibodies as selective carriers of radiation to tumors. Internal spatially distributed sources created at the disease sites would deliver high radiation doses to tumors while the normal tissues would not be exposed to the intense radiation as in conventional forms of cancer treatments. A rapid and accurate estimation of the spatial dose distribution from nonuniform sources is essential for the optimization of this form of cancer therapy. The method used for such calculations is based on the knowledge of dose distributions around a unit source, quantities referred to as dose kernels. Thus far, the Monte Carlo technique is the most accurate way of the dose kernel determinations. However, for routine dosimetry simpler and less time consuming methods of adequate accuracy may appear more preferable. The "scaling factor" method is used to determine the depth dose distribution in a medium based on data about the dose distribution in an arbitrary reference medium (e.g. air, water). The transformation of the dose distribution curves from the reference medium to the desired new medium is done using a constant, known as scaling factor or relative dose attenuation, and a closely related renormalization factor imposed by the energy conservation. This work investigates the accuracy of the scaling factor method using a statistical approach (generalized chi-squared test), focusing on a particular case of potential practical interest, the scaling factor water to bone. The work also investigates a procedure for extending the applicability of the scaling factor method to dosimetry in dissimilar media, as a first step, a planar interface. / Thesis / Master of Science (MS)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24181 |
| Date | 09 1900 |
| Creators | Marcu, Silviu-Marcel |
| Contributors | Prestwich, W. V., Physics |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0043 seconds