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Giuseppe Magro1

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International Journal of Radiation Biology
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SDAnext is a new open-source MATLAB application for analyzing cell survival data in radiobiology. It offers intuitive tools for fitting data to various models and visualizing results, aiding radiation research.

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Area of Science:

  • Radiobiology and Radiation Oncology
  • Computational Biology and Bioinformatics

Background:

  • Cell survival curves are essential for understanding radiation effects.
  • Accurate analysis of radiobiological data is crucial for radiation therapy and research.
  • Existing tools may lack comprehensive features or user-friendliness.

Purpose of the Study:

  • To introduce SDAnext, an open-source MATLAB application for comprehensive cell survival data analysis.
  • To provide researchers with an intuitive graphical user interface for fitting and visualizing radiobiological data.
  • To facilitate the calculation of key radiobiological parameters and comparative analyses.

Main Methods:

  • Development of an open-source MATLAB application with a graphical user interface.
  • Implementation of weighted least squares fitting with robust estimators and uncertainty handling.
  • Support for multiple analytical models (Linear, Quadratic, Linear-Quadratic, etc.) and automated model selection.
  • Inclusion of visualization tools and a multi-session viewer for comparative analysis.

Main Results:

  • SDAnext provides validated data import, fitting to standard radiobiological models, and publication-ready visualizations.
  • The software incorporates automated model scanning, goodness-of-fit ranking, and dose-survival evaluation.
  • It enables calculation of radiobiological quantities like α/β ratios with uncertainty propagation.
  • A multi-session viewer facilitates cross-dataset comparisons and relative biological effectiveness analysis.

Conclusions:

  • SDAnext offers a powerful, user-friendly, and versatile platform for cell survival data analysis in radiobiology.
  • The application enhances the accuracy and efficiency of radiobiological research and radiation therapy planning.
  • Its open-source nature and standalone executability promote accessibility and adoption within the scientific community.