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Dosimetric uncertainties of three-dimensional dose reconstruction from two-dimensional data in a multi-institutional
Rebecca Weinberg1, Darryl G L Kaurin, Hak Choy
1Department of Radiation Oncology, The Vanderbilt Clinic, Vanderbilt University Medical Center, Nashville, Tennessee, USA. rweinber@mdanderson.org
Journal of Applied Clinical Medical Physics
|March 2, 2005
Summary
Dosimetric uncertainties in radiation oncology clinical trials can arise from reconstructing 3D dose distributions from 2D plans. Image quality and target volume delineation significantly impact dose-value uncertainties, affecting trial conclusions.
Area of Science:
- Radiation Oncology
- Medical Physics
- Clinical Trials
Background:
- Interinstitutional radiation oncology clinical trials rely on consistent treatment planning.
- Dosimetric uncertainties can compromise the validity of trial conclusions.
Purpose of the Study:
- To assess dosimetric uncertainties from reconstructing 3D dose distributions from 2D treatment plan data in a multi-institutional clinical trial.
- To identify sources of uncertainty in the treatment planning process.
Main Methods:
- Analysis of uncertainties from computed tomography (CT) image quality, slice spacing, treatment position, target volume delineation, and beam models.
- Utilized eight cases with electronically transferred CT data from Vanderbilt University Medical Center.
- Investigated uncertainty sources using plans with ideal digital image characteristics.
Main Results:
- Target volume dose-value uncertainties depended on radiation oncologists' target volume delineation.
- Lung and heart dose-value uncertainties were influenced by image quality and treatment position.
- Esophagus dose-value uncertainties were not dependent on any analyzed sources; slice thickness and normal structure contouring did not affect dose-value uncertainties.
Conclusions:
- Reconstructing 3D dose distributions from 2D data can be useful for historical review or when digital CT data is unavailable.
- Dosimetric accuracy is contingent upon the quality of treatment planning CT data and consistent tumor volume delineation.