(Sunday, 7/29/2018) 4:00 PM - 5:00 PM
Room: Exhibit Hall | Forum 2
Purpose: To put forward a new approach that deals with delineation uncertainties of the clinical target volume (CTV). Instead of a contour-based binary CTV we introduce and test a continuum distribution of probability to find tumorous cells at a certain distance from the surface of the gross tumor volume (GTV) and call it the clinical target distribution (CTD).
Methods: The CTD was incorporated in treatment plan optimization algorithms through tumor control probability (TCP) model by considering the probabilities of voxels being tumorous and adapting the model to define the objective optimization function though the weighted sum approach. Voxel probabilities were derived through the series of shells around the GTV, with certain probabilities that there is tumor outside the shell. For the outermost shell with the probability 0%, it is absolutely certain that there are no tumorous voxels at further distances.
Results: We implemented the CTD in a commercial treatment planning system and tested it in two synthetic and two clinical cases, a sarcoma and a glioblastoma. The CTD-based plans were compared with the plans optimized to deliver the same dose to traditionally defined CTV. For both synthetic and clinical cases, the CTD-based plans were superior in terms of a tradeoff between coverage of the radiation target and sparing of critical organs. We showed that CTD allows the treatment planner to find the most suitable expansion of the high dose region beyond the visible GTV.
Conclusion: A concept of continuum clinical target distribution increases flexibility of definition of the microscopic disease extension that is reflected in superior treatment plans. CTD allows to find the most suitable tradeoff between target coverage and sparing of healthy organs, without modifying or redrawing the CTV. Owing to the variable probabilities afforded by the CTD, a more clinically meaningful sparing of critical structure becomes possible.
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