Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.617475
Title: Modelling the effect of geometric uncertainties, clonogen distribution and IMRT interplay effect on tumour control probability
Author: Kalyankuppam Selvaraj, Jothybasu
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2013
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Abstract:
Geometric uncertainties are inevitable in radiotherapy. These uncertainties in tumour position are classified as systematic (Ε) and random (δ) errors. To account for these uncertainties, a margin is added to the clinical target volume (CTV) to create the planning target volume (PTV). The size of the PTV is critical for obtaining an optimal treatment plan. Dose-based (i.e., physical) margin recipes as a function of systematic and random errors based on coverage probability of a certain level of dose (90% or 95% of the prescription dose) have been published and widely used. However, with a TCP-based margin it is possible to consider fractionation and the radiobiological characteristics, especially the dose-response slope (50) of the tumour. Studies have shown that the density of the clonogens decrease from the boundary of the gross tumour volume (GTV). In such a scenario, dose that is lower than in the GTV should be sufficient to eradicate these clonogens. Thus a smaller PTV margin with a gradual dose fall off can be used if the clonogen density in the GTV-CTV region is found to be lower than in GTV. Studies have reported tiny tumour islets outside the CTV region. These tiny tumour islets can be eradicated in some cases by the incidental dose outside the PTV due to the nature of the photon beam irradiation, but if they are not in the beam path the treatment outcome is compromised. In this thesis, a Monte Carlo approach is used to simulate the effect of geometric uncertainties, number of fractions and dose-response slope (gamma50) using the 'enhanced Marsden' TCP model on the treatment outcome. Systematic and random errors were drawn from a pseudo-random number generator. The dose variations caused by tumour displacements due to geometric uncertainties in the CTV are accumulated each fraction on a voxel-by-voxel basis. Required margins for ≤ 1% mean population TCP (TCPpop) for four-field (4F) brick and a highly conformal spherical dose distribution for varying number of fractions, different γ50 and different combinations of Ε and δ are investigated. It is found that TCP-based margins are considerably smaller than dose-based recipes in most cases except for tumours with a steep dose-response slope (high γ50) and a small number of fractions for both 4F and spherical dose distributions. For smaller geometric uncertainties (Ε = δ = 1 mm) margins can be close to zero for the 4F technique due to high incidental dose outside the PTV. It is evident from the analyses that margins depend on the number of fractions, γ50, the degree of dose conformality in addition to Ε and δ. Ideally margins should be anisotropic and individualized, taking into account γ50, number of fractions, and the dose distribution, as well as estimates of Ε and γ. No single 'recipe' can adequately account for all these variables. Using an exponential clonogen distribution in the GTV-CTV region, possible PTV margin reduction is demonstrated. Moreover, the effect of extra-CTV tumour islets is studied using a prostate IMRT plan. The islets were randomly distributed around the CTV with in a radius of 3 cm to represent different patients. The doses were rescaled up to 102 Gy to obtain the dose-response curve (DRC). Interestingly, the obtained DRC showed a biphasic response where 100% TCP could not be achieved just by escalating the dose. Another potential problem encountered in intensity-modulated radiotherapy (IMRT) is the problems caused by the 'interplay' effect between the respiration-induced tumour motion and the multileaf collimator (MLC) leaves movement during treatment. Several dosimetric studies in the literature have shown that 'interplay' effects blur the dose distribution by producing 'hot' and 'cold' dose inside the tumour. Most of these studies were done in a phantom with ion chambers or films, which provide only 1D or 2D dose information. If 3D dose information is available, a TCP based analysis would provide a direct estimate of interplay on the clinical outcome. In this thesis, an in-house developed dose model enabled us to calculate the 3D time-resolved dose contribution to each voxel in the target volume considering the change in segment shapes and position of the target volume. Using the model, delivered dose is accumulated in a voxel-by-voxel basis inclusive of tumour motion over the course of treatment. The effect of interplay on dose and TCP is studied for conventionally and hypofractionated treatments using DICOM datasets. Moreover, the effect of dose rate on interplay is also studied for single-fraction treatments. Simulations were repeated several times to obtain mean population TCP (TCPpop) for each plan. The average variation observed in mean dose to the target volumes were -0.76 ± 0.36% for the 20 fraction treatment and -0.26 ± 0.68%, -1.05 ± 0.98% for the 3- and single-fraction treatments respectively. For the 20-fraction treatment, the drop in TCPpop was -1.05 ± 0.39%, whereas for the 3 and single fraction treatments it was -2.8 ± 1.68% and -4.0 ± 2.84% respectively. By reducing the dose rate from 600 to 300 MU/min for the single-fraction treatments, the drop in TCPpop was reduced by ~ 1:5%. In summary, the effect of interplay on treatment outcome is negligible for conventionally fractionated treatments, whereas a considerable drop in TCP is observed for the 3- and single-fraction treatments. Where no motion management techniques such as tracking or gating are available for hypo-fractionated treatments, reduced dose rate could be used to reduce the interplay effect.
Supervisor: Nahum, Alan; Baker, Colin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.617475  DOI: Not available
Keywords: RC0254 Neoplasms. Tumors. Oncology (including Cancer)
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