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A comparison of four indices for combining distance and dose differences
1Department of Medical Physics, Addenbrooke's Hospital, Cambridge, England. simon.thomas@addenbrookes.nhs.uk
Comparing dose distribution indices like gamma, kappa, and box, this study found the kappa index is best for clinical tolerances, while the box index excels when measurement uncertainties are high. Both help evaluate dose delivery accuracy.
Area of Science:
- Medical Physics
- Radiation Oncology
- Dosimetry
Background:
- Comparing radiation dose distributions is crucial for treatment plan quality assurance.
- Existing methods combine dose difference and distance to agreement into single measures.
- These measures are often presented as pass/fail or numeric indices.
Purpose of the Study:
- To compare various indices for evaluating one-dimensional (1D) and three-dimensional (3D) dose distributions.
- To determine the most appropriate index for different clinical and measurement scenarios.
- To analyze the derivation of numeric indices from pass/fail metrics.
Main Methods:
- Comparison of gamma, kappa, International Commission on Radiation Units & Measurements (ICRU) Report 83, and box indices.
- Evaluation using 1D distributions with varying dose gradients and a 3D clinical treatment plan.
- Analysis of the impact of dose and distance offsets on index performance.
Main Results:
- The ICRU Report 83 index shows discontinuities unless specific gradient cutoffs are applied, then matching kappa index results.
- All indices yield similar outcomes at very high or low dose gradients.
- For moderate gradients, the box index is least strict, followed by gamma, then kappa.
Conclusions:
- The kappa index is recommended when clinical tolerances exceed measurement uncertainties, using clinical tolerances for setting parameters.
- The box index is preferred when measurement system uncertainties are dominant, aiding in identifying delivery errors.
- The choice of index depends on the relative magnitudes of clinical tolerances and measurement uncertainties.
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