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September 17, 2025Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition0 citations

Predicting the trajectory of radiotherapy response in patients with head and neck cancer using mathematical modeling of MRI-based habitats

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DHDavid A. HormuthMDMichael J. DubecALAmaya Lanz Lozano

Key Points

  • Mathematical modeling forecasts radiotherapy response within four weeks for head and neck tumors, enhancing treatment accuracy.
  • The model incorporates MRI-based habitats to evaluate intratumoral hypoxia, aiding predictions for individual patient responses.
  • Patients were split into training and test sets, optimizing model parameters for better accuracy in response predictions.
  • Results suggest potential for MRI-guided strategies to tailor radiotherapy based on patient-specific tumor characteristics.

Abstract

Motivation: Intratumor hypoxia in head and neck cancer influences response to radiotherapy. Goal(s): To characterize intratumoral heterogeneity of hypoxia distribution via predictive, MRI-based mathematical modeling. Approach: MRI-based habitats identified in 20 patients informed a mathematical model of tumor response to radiotherapy. Patients were divided into training (75%) and test (25%) sets to optimize model parameters. The optimized parameters and initial habitat conditions from the test-set were then used to predict response during radiotherapy. Results: The biologically-based mathematical model accurately forecasts anticipated treatment response up to week 4 of radiotherapy for both primary and nodal lesions. Impact: MRI-based modeling of intratumoral heterogeneity in hypoxic, perfusion, and cellular status can predict changes in tumor biology in response due to radiotherapy. Patient-specific predictions based on dynamic changes in imaging parameters could be used to identify optimal radiotherapy strategies.

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Cite This Study

Hormuth et al. (2025) studied this question.

synapsesocial.com/papers/68d4597031b076d99fa5c4cehttps://doi.org/10.58530/2025/2200
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