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Technical note: reconstructing dose distributions from manually planned electron boosts in breast radiotherapy
Tanwiwat Jaikuna1, Isobel Dawes2, Hannah Chamberlin2
1Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Christie NHS Foundation Trust Hospital, Manchester, United Kingdom; Division of Radiation Oncology, Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Reconstructing electron boost doses in breast radiotherapy is feasible, improving retrospective analysis. This method offers acceptable accuracy for large studies, though caution is needed at tissue interfaces.
Area of Science:
- Medical Physics
- Radiation Oncology
- Radiotherapy Planning
Background:
- Manual electron boosts in breast radiotherapy lack dose distribution data, hindering retrospective analyses.
- Accurate dose distribution is crucial for understanding treatment outcomes and optimizing radiotherapy.
Purpose of the Study:
- To evaluate the feasibility of reconstructing dose distributions from manually planned electron boosts in breast radiotherapy.
- To assess the accuracy of Monte Carlo-based dose reconstruction for retrospective studies.
Main Methods:
- Developed and validated a Monte Carlo (MC)-based electron dose reconstruction method using data from 70 breast cancer patients.
- Optimized parameters including CT-calibration curve, MC-history number, and calculation grid resolution.
- Evaluated accuracy using 3D-gamma index, dosimetric parameters, and dose-location histograms.
Main Results:
- Finest calculation grid resolution (0.15 cm) significantly improved electron dose distribution accuracy (p < 0.01).
- Reconstructed doses showed < 1 Gy dosimetric difference for breast and tumor bed, with >90% gamma passing rate.
- Dose differences up to 2.5 Gy were observed at skin and tissue interfaces.
Conclusions:
- Retrospective electron boost dose reconstruction is feasible with acceptable accuracy for large cohort studies.
- The method can enhance data completeness for retrospective dose-response analyses.
- Further validation is recommended, especially for dose assessment near tissue interfaces.

