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Three-dimensional dosimetry for intralesional radionuclide therapy using mathematical modeling and multimodality
1Joint Department of Physics, Institute of Cancer Research, Sutton, Surrey, United Kingdom.
Summary
This study introduces a novel dosimetry method to quantify 3D radiation dose distribution from radiolabeled antibody infusions in tumors. It accounts for dose heterogeneity without calibration scans, enabling personalized treatment planning.
Area of Science:
- Medical Physics
- Radiotherapy
- Nuclear Medicine
Background:
- Intralesional administration of radiolabeled monoclonal antibodies is used in cancer therapy.
- Accurate dosimetry is crucial for optimizing treatment efficacy and minimizing toxicity.
- Existing dosimetry methods may not fully capture the complex dose distributions in heterogeneous tumor environments.
Purpose of the Study:
- To develop and validate a novel dosimetry method for quantifying 3D absorbed dose distribution.
- To assess the spatial and temporal heterogeneity of radionuclide distribution after intralesional infusion.
- To enable personalized treatment planning in radionuclide therapy.
Main Methods:
- A mathematical model was developed to describe radionuclide activity distribution over time post-infusion.
- Parameters were derived from Single-Photon Emission Computed Tomography (SPECT) and Computed Tomography (CT) imaging.
- Convolution of activity distribution with a point-source dose kernel calculated the 3D absorbed dose.
Main Results:
- The method was applied to patient data from a clinical study.
- Dose profiles and dose-volume histograms were generated, demonstrating significant dose non-uniformity.
- The 3D absorbed dose distribution was successfully quantified.
Conclusions:
- The developed dosimetry method accurately determines absorbed dose distribution from intralesional radiolabeled antibody infusions.
- This approach overcomes limitations of traditional methods like Medical Internal Radiation Dose (MIRD) calculations.
- It facilitates individualized patient treatment planning and optimization of therapeutic parameters.