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Technical note: A modified gamma evaluation method for dose distribution comparisons
Author(s) -
Yu Liting,
Kairn Tanya,
Trapp Jamie,
Crowe Scott B.
Publication year - 2019
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.12606
Subject(s) - distribution (mathematics) , radiochemistry , mathematics , medical physics , chemistry , physics , mathematical analysis
Purpose In this work we have developed a novel method of dose distribution comparison, the inverse gamma (IG) evaluation, by modifying the commonly used gamma evaluation method. Methods The IG evaluation calculates the gamma criteria (dose difference criterion, ΔD, or distance‐to‐agreement criterion, Δd) that are needed to achieve a predefined pass rate or gamma agreement index (GAI). In‐house code for evaluating IG with a fixed ΔD of 3% was developed using Python (v3.5.2) and investigated using treatment plans and measurement data from 25 retrospective patient specific quality assurance tests (53 individual arcs). Results It was found that when the desired GAI was set to 95%, approximately three quarters of the arcs tested were able to achieve Δd within 1 mm (mean Δd: 0.7 ± 0.5 mm). The mean Δd required in order for all points to pass the gamma evaluation (i.e., GAI = 100%) was 4.5 ± 3.1 mm. The possibility of evaluating IG by fixing the Δd or ΔD/Δd, instead of fixing the ΔD at 3%, was also investigated. Conclusion The IG method and its indices have the potential to be implemented clinically to quantify the minimum dose and distance criteria based on a specified GAI. This method provides additional information to augment standard gamma evaluation results during patient specific quality assurance testing of individual treatment plans. The IG method also has the potential to be used in retrospective audits to determine an appropriate set of local gamma criteria and action levels based on a cohort of patient specific quality assurance plans.

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