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Research Article

Evaluation of adaptive radiotherapy of bladder cancer by image-based tumour control probability modelling

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Pages 1045-1051 | Received 28 Apr 2010, Accepted 27 May 2010, Published online: 13 Sep 2010
 

Abstract

Clinical implementation of adaptive radiotherapy strategies could benefit from extended tools for plan evaluation and selection. For this purpose we investigated the feasibility of image-based tumour control probability (TCP) modelling using the bladder as example of a tumour site with potential benefit from adaptive strategies. Material and methods. Two bladder cancer patients that underwent planning CT and daily cone beam CT (CBCT) imaging during the treatment course were included. The bladder was outlined in every image series. Following a previously published procedure, various adaptive planning target volumes (PTVs) were generated from the inter-fractional bladder variation observed during the first four CBCT sessions. Intensity modulated treatment plans delivering 60 Gy to a given PTV were generated. In addition, simultaneous integrated boost (SIB) plans giving a 10 Gy boost to the tumour were created. Using the daily CBCT images and polynomial warping, the dose in each bladder volume element was tracked fraction by fraction. TCP calculations employing the tracked accumulated dose distributions, together with radiosensitivity parameters estimated from published data on local control of bladder cancer were performed. The dependence of TCP on the simulated clonogenic cell distribution was also explored. Results. For a uniform clonogenic cell density in the whole bladder, TCP varied between 53% and 58% for the 60 Gy plans, while it was between 51% and 64% for the SIB plans. The lowest values were found when using the smallest PTVs, as they did not geometrically enclose the clinical target volume in all fractions. When increasing the clonogenic cell density in the tumour relative to that in the remaining bladder, the TCP saturated at approximately 75% for the SIB plans. Conclusion. Dose tracking and TCP calculation provided additional information to standard criteria such as geometrical coverage for the selected cases. TCP modelling may be a useful tool in plan evaluation and for selection between multiple plans.

Acknowledgements

Christoffer Lervåg is acknowledged for help with data conversion. This work has been supported by research grants from the Danish Cancer Society, the Danish Postgraduate School for Clinical Oncology, Varian Medical Systems (Palo Alto, California), The Danish Council for Strategic Research and CIRRO, the Lundbeck Foundation Centre for Interventional Research in Radiation Oncology.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

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