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On differences in radiosensitivity estimation: TCP experiments versus survival curves. A theoretical study.

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Estimating tumor radiosensitivity differs between cell-survival and tumor control probability (TCP) methods. While cell survival appears uniform, TCP data reveals resistance from small cell populations, impacting treatment dose.

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Area of Science:

  • Radiation Oncology
  • Tumor Biology
  • Mathematical Modeling

Background:

  • Tumor heterogeneity in radiosensitivity is a critical factor in radiation therapy outcomes.
  • Accurate estimation of cellular radiosensitivity is essential for effective treatment planning.
  • Existing models often assume homogeneous cell populations, potentially oversimplifying complex tumor responses.

Purpose of the Study:

  • To compare two distinct methods for estimating cellular radiosensitivity in heterogeneous tumors: cell-survival and tumor control probability (TCP) pseudo-experiments.
  • To investigate the impact of intra-tumoral radiosensitivity variability on these estimation methods.
  • To evaluate the suitability of mono-component models for describing the response of heterogeneous cell populations.

Main Methods:

  • Utilized a multi-component linear-quadratic (LQ) model to simulate cell kill in heterogeneous tumor models.
  • Generated pseudo-experimental cell-survival curves and fitted them with mono-component LQ models.
  • Simulated pseudo-experimental TCP curves considering clonogen proliferation and fitted them with mono-component TCP models.

Main Results:

  • Pseudo-experimental cell-survival curves from heterogeneous populations were well-approximated by mono-component models, suggesting uniform radiosensitivity.
  • Similarly, mono-component TCP models provided highly acceptable fits to simulated TCP curves from heterogeneous populations.
  • Despite acceptable fits, the best-fit radiosensitivity values differed significantly between cell-survival (high radiosensitivity) and TCP (dominated by resistant cells) methods.

Conclusions:

  • Cell-survival pseudo-experiments may underestimate the impact of radio-resistant subpopulations in heterogeneous tumors.
  • Tumor control probability (TCP) pseudo-experiments highlight the dominance of the most resistant cells, even in small fractions, influencing overall tumor response.
  • The choice of method significantly impacts the estimated cellular radiosensitivity, with implications for radiation dose prescription and treatment optimization.