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Sci‐Sat AM (1) General‐06: Theoretical estimation of dose volume constraints and their impact on DVH selection
Author(s) -
Schinkel C,
Stavrev P,
Stavreva N,
Fallone B
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2244693
Subject(s) - dosimetry , volume (thermodynamics) , mathematical optimization , constraint (computer aided design) , radiation treatment planning , population , mathematics , dose volume histogram , selection (genetic algorithm) , nuclear medicine , range (aeronautics) , computer science , radiation therapy , medicine , physics , radiology , artificial intelligence , geometry , environmental health , materials science , quantum mechanics , composite material
Dose‐volume constraints are essential for treatment planning optimization using physical objective functions. A theoretical approach to the problem of choosing dose‐volume constraints based on the reverse normal tissue complication probability (NTCP) mapping into dose‐volume space is developed. Dose‐volume histograms (DVHs) are randomly simulated and those resulting in clinically acceptable levels of complication, e.g. NTCP of 5±0.5%, are selected and averaged producing a mean DVH which is proven to result in the same level of NTCP. The points from the averaged DVH are proposed to serve as dose‐volume constraints for treatment planning optimization using physical objective functions. The population based Critical Volume and the Lyman NTCP models with parameter sets taken from literature were used for the NTCP estimation. Constraint points for 16 organs are calculated. These dose‐volume constraints are not unique and depend on the range in which the maximum dose to the organ at risk, D max , is allowed to vary. It is theoretically proven that the radiation treatment optimization based on physical objective functions can sufficiently well restrict the dose to the organs at risk resulting in sufficiently low NTCP values through the employment of several appropriate dose‐volume constraints. At the same time, the pure physical approach to optimization is self‐restrictive due to the pre‐assignment of acceptable NTCP levels thus excluding possible better solutions to the problem.