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


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.


CONCLUSIONS
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.
Wright
Pauliina
P
Department of Medical Physics, Aarhus University Hospital, Denmark. paulwrig@rm.dk
Muren
Ludvig P
LP
Høyer
Morten
M
Malinen
Eirik
E
D002277:Carcinoma / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D011336:Probability; D011859:Radiography; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D020266:Radiotherapy, Conformal / Q000379:methods; D047368:Tumor Burden; D001743:Urinary Bladder / Q000000981:diagnostic imaging / Q000473:pathology; D001749:Urinary Bladder Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*