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SU‐E‐T‐245: Survival Fractions for Head‐And‐Neck Cancer Derived from Tumor‐Volume Variation Curves Using a 2‐Level Cell Population Model
Author(s) -
Chvetsov A,
Stewart R
Publication year - 2012
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 - 10.1118/1.4735309
Subject(s) - head and neck cancer , population , volume (thermodynamics) , head and neck , nuclear medicine , cancer , medicine , physics , surgery , quantum mechanics , environmental health
Purpose: Volumetric tumor response to radiotherapy is an integrated process which includes several radiobiological mechanisms, such as cell killing, cell proliferation, dead‐cell removal and tumor reoxygenation. Our goal is to reconstruct the information about these underlying radiobiological processes and specifically the cell survival fractions by fitting a 2‐level cell‐population tumor‐volume model to imaging‐derived tumor‐volume variation curves obtained during radiotherapy for head‐and‐neck cancer. Methods: Modeling tumor‐volume during radiotherapy is a challenging problem because it is described by a sum of exponentials; therefore, the problem of accurately fitting a model to measured data is ill‐posed. As an initial point of this research, we utilize a simplest 2‐level cell‐population tumor‐volume model which separates the entire tumor‐cell population into oxygenated viable cells and oxygenated lethally damaged cells. The 2‐level cell population tumor model has the advantage of being conditionally well‐posed. We integrated this parameterized radiobiological model with a least squares objective function and a simulated annealing optimization algorithm to characterize individual patients' time‐dependent tumor‐volume regression rates. The measured tumor‐volume variation curves were taken from a clinical study on tumor‐volume variation during radiotherapy for 14 head‐and‐neck cancer patients in which an integrated CT/linac system was used for tumor‐volume measurements. Results: The 2‐level tumor volume modeling is able to predict tumor behavior throughout an entire treatment for 8 of 14 patients. The average survival fraction 0.44 agrees very well with the published survival fraction of 0.45 for the head‐and‐neck squamous cell carcinoma. However, the 2‐level model cannot describe the variation of the cell disintegration rate which is observed at the end of treatment for some of the head‐and‐neck cancer patients. Conclusions: The 2‐level cell population model is an acceptable approximation for the tumor‐volume for some clinical cases, but it cannot describe all tumor‐volume regression cases. This may be explained by omitting hypoxia in the 2‐level model.