방사선의학 웹진

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Abstract

Purpose: 

To demonstrate that a mathematical model can be used to quantitatively understand tumor cellular dynamics during a course of radiotherapy and to predict the likelihood of local control as a function of dose and treatment fractions.

Experimental Design: 

We model outcomes for early-stage, localized non-small cell lung cancer (NSCLC), by fitting a mechanistic, cellular dynamics-based tumor control probability that assumes a constant local supply of oxygen and glucose. In addition to standard radiobiological effects such as repair of sub-lethal damage and the impact of hypoxia, we also accounted for proliferation as well as radiosensitivity variability within the cell cycle. We applied the model to 36 published and two unpublished early-stage patient cohorts, totaling 2,701 patients.

Results: 

Precise likelihood best-fit values were derived for the radiobiological parameters: α [0.305 Gy-1; 95% confidence interval (CI), 0.120-0.365], the α/β ratio (2.80 Gy; 95% CI, 0.40-4.40), and the oxygen enhancement ratio (OER) value for intermediately hypoxic cells receiving glucose but not oxygen (1.70; 95% CI, 1.55-2.25). All fractionation groups are well fitted by a single dose-response curve with a high χ2 P value, indicating consistency with the fitted model. The analysis was further validated with an additional 23 patient cohorts (n = 1,628). The model indicates that hypofractionation regimens overcome hypoxia (and cell-cycle radiosensitivity variations) by the sheer impact of high doses per fraction, whereas lower dose-per-fraction regimens allow for reoxygenation and corresponding sensitization, but lose effectiveness for prolonged treatments due to proliferation.

Conclusions:

This proposed mechanistic tumor-response model can accurately predict overtreatment or undertreatment for various treatment regimens.

Figure 5.

Validation dataset with 23 patient cohorts (n = 1,628) overlaid with the dose–response curve derived from the original dataset for the best-fit parameter values (α = 0.305 Gy−1, α/β = 2.8 Gy, and OERI = 1.7). The χ2 test shows the validation datasets are in great agreement with the dose–response curve derived from the original dataset (P = 1.0).​ 

Author information​

Jeong J1, Oh JH2, Sonke JJ3, Belderbos J3, Bradley JD4, Fontanella AN2, Rao SS5, Deasy JO1.

1 Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. jeongj@mskcc.org deasyj@mskcc.org.

2 Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.

3 Department of Radiation Oncology, The Netherlands Cancer Institute, Postbus, Amsterdam, the Netherlands.

4 Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri.

5 Department of Radiation Oncology, University of California, Davis Comprehensive Cancer Center, Sacramento, California.