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Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage.

Daniel Rocky Owen1, Phillip S Boonstra2, Benjamin L Viglianti3

  • 1Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.

International Journal of Radiation Oncology, Biology, Physics
|August 16, 2018
PubMed
Summary

This study models lung function changes in non-small cell lung cancer patients undergoing radiation therapy (RT). The developed models predict functional damage, aiding in personalized RT planning to minimize toxicity.

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Area of Science:

  • Radiation oncology
  • Pulmonary imaging
  • Quantitative modeling

Background:

  • Functional-guided radiation therapy (RT) aims to reduce normal tissue damage and toxicity.
  • Clinical implementation is limited by understanding radiation's functional response and personalized therapy applications.

Purpose of the Study:

  • To retrospectively model patient-specific dose-function response in non-small cell lung cancer (NSCLC) patients treated with RT.
  • To characterize expected functional lung damage in future patients for improved RT planning.

Main Methods:

  • Retrospective analysis of perfusion SPECT/CT scans at multiple time points (baseline, mid-treatment, 3 months, 1 year).
  • Utilized normalized perfusion intensity as a surrogate for local lung function.
  • Applied patient-specific logistic models to assess dose-function response and created a population-level model.

Main Results:

  • Observed significant longitudinal decrease in lung function post-RT.
  • Developed dose-function response models predict voxelwise functional reduction and uncertainty for different RT fractionation schemes.
  • Higher functioning lung voxels showed a greater rate of damage compared to lower functioning ones.

Conclusions:

  • Patient-specific dose-function response models were successfully developed for NSCLC patients undergoing RT.
  • These models can inform functional-guided RT plans by predicting expected functional lung damage.
  • The patient-specific modeling approach is broadly applicable for analyzing functional responses and personalizing damage characterization.