Practical considerations in using calculated healthy-tissue complication probabilities for treatment-plan optimization.
OBJECTIVE
Healthy and neoplastic tissues are generally exposed nonuniformly to ionizing radiation. It is thus useful to develop algorithms that predict the probability of tumor control or normal tissue complication probability (NTCP) for any given spatial pattern of dose delivery. The questions addressed here concern: (a) the sensitivity of the NTCP predictions to the actual model used for extrapolation from uniform irradiation (where some clinical data exist) to nonuniform exposures, (b) its dependence on tissue type, and (c) consequences for treatment-plan optimization.


METHODS
Two (of several possible) NTCP formulations are used here: the Lyman model and a binomial equation. The effective volume-reduction scheme of Kutcher and Burman is used to obtain the NTCP for an arbitrary distribution of dose. NTCP was calculated for seven organs by postulating a dose distribution of maximum nonuniformity.


RESULTS
Both models fit available NTCP data well, but have very different extrapolations for exposures of small tissue volumes and very low values of NTCP (e.g., < 5%) where no data exist. Organs with pronounced volume effects (lung, kidneys) show substantial NTCP differences between the two models. Even in organs where the volume effect is small (e.g., spinal cord, brain), differences in NTCP due to the model selected may still have serious clinical consequences, as an actual example (for the spinal cord) indicates.


CONCLUSIONS
NTCP calculations based on extrapolations to volume fractions and/or NTCP levels for which reliable data do not exist depend on the model used to fit the data and the degree of dose nonuniformity. If NTCP is to be used in treatment-plan optimization, the prudent approach is to design plans that reproduce the conditions under which available dose-volume data were taken (e. g., uniform dose distributions).
Zaider
M
M
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Amols
H I
HI
D000465:Algorithms; D004938:Esophageal Neoplasms / Q000532:radiotherapy; D006321:Heart / Q000528:radiation effects; D006801:Humans; D008168:Lung / Q000528:radiation effects; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000532:radiotherapy*; D055585:Physical Phenomena; D010825:Physics; D011834:Radiation Monitoring / Q000379:methods*; D013116:Spinal Cord / Q000528:radiation effects