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TH-AB-304-04: Tumor Control Probability Modeling for Stereotactic Body Radiation Therapy of Early-Stage Lung Cancer Using Multiple Bio-Physical Models. Med Phys 2015 Jun;42(6):3701

Date

07/02/2015

Pubmed ID

26129419

Abstract

PURPOSE: To analyze pooled clinical data using six radiobiological models and to understand the relationship between BED and TCP for SBRT of early-stage NSCLC.

METHODS: The clinical data of 1- , 2-, 3-, and 5-year actuarial or Kaplan-Meier TCP data from 46 studies were collected for SBRT of early stage (T1 and T2) NSCLC. The TCP data were separated for Stage T1 and T2 tumors if possible. BED was calculated at isocenters using six radiobiological models. Model parameters were determined from a fit to the TCP data using the least chi-square (χ2) method with one set of parameters regardless of tumor stages or two sets for T1 and T2 tumors separately.

RESULTS: The fits to the clinic data yield consistent results of large α/β ratios of about 23 Gy for all models. The regrowth model that accounts for the tumor repopulation and heterogeneity leads to a better fit to the data, compared to other 5 models where the fits were indistinguishable between the models. The models based on the fitting parameters predict that the T2 tumors require about additional 1 Gy physical dose at isocenters per fraction (≤5 fractions) to achieve the optimal TCP when compared to the T1 tumors. Sample fractionation schemes were estimated based the determined model parameters for the regrowth model.

CONCLUSION: A systematic analysis of a large set clinical data using six radiobiological models shows that local TCP for SBRT of early stage NSCLC has strong dependence on BED with large α/β ratios of about 23 Gy. The six models considered predict that a BED of 80 Gy is sufficient to achieve a 95% TCP. The regrowth model leads to better fit to the clinical data, the LQ model is the simplest and indistinguishable with remaining models. Sample fractionation regimens that can yield TCPs larger than 95% were estimated.

Author List

Liu F, Tai A, Lee P, Biswas T, Ding G, El Naqa I, Grimm J, Jackson A, Kong F, LaCouture T, Loo B, Miften M, Solberg T, Li X

Author

An Tai PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin




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