PURPOSE: This work investigates the use of receiver operating characteristic (ROC) methods in patient specific IMRT quality assurance (QA) in order to determine unbiased methods to set threshold criteria for γ-distance to agreement measurements. METHODS: A group of 17 prostate plans was delivered as planned while a second group of 17 prostate plans was modified with the introduction of random multileaf collimator (MLC) position errors that are normally distributed with σ ≈ ± 0.5, ± 1.0, ± 2.0, and ± 3.0 mm (a total of 68 modified plans were created). All plans were evaluated using five different γ-criteria. ROC methodology was applied by quantifying the fraction of modified plans reported as "fail" and unmodified plans reported as "pass." RESULTS: γ-based criteria were able to attain nearly 100% sensitivity/specificity in the detection of large random errors (σ > 3 mm). Sensitivity and specificity decrease rapidly for all γ-criteria as the size of error to be detected decreases below 2 mm. Predictive power is null with all criteria used in the detection of small MLC errors (σ < 0.5 mm). Optimal threshold values were established by determining which criteria maximized sensitivity and specificity. For 3%/3 mm γ-criteria, optimal threshold values range from 92% to 99%, whereas for 2%/2 mm, the range was from 77% to 94%. CONCLUSIONS: The optimal threshold values that were determined represent a maximized test sensitivity and specificity and are not subject to any user bias. When applied to the datasets that we studied, our results suggest the use of patient specific QA as a safety tool that can effectively prevent large errors (e.g., σ > 3 mm) as opposed to a tool to improve the quality of IMRT delivery.
PURPOSE: This work investigates the use of receiver operating characteristic (ROC) methods in patient specific IMRT quality assurance (QA) in order to determine unbiased methods to set threshold criteria for γ-distance to agreement measurements. METHODS: A group of 17 prostate plans was delivered as planned while a second group of 17 prostate plans was modified with the introduction of random multileaf collimator (MLC) position errors that are normally distributed with σ ≈ ± 0.5, ± 1.0, ± 2.0, and ± 3.0 mm (a total of 68 modified plans were created). All plans were evaluated using five different γ-criteria. ROC methodology was applied by quantifying the fraction of modified plans reported as "fail" and unmodified plans reported as "pass." RESULTS: γ-based criteria were able to attain nearly 100% sensitivity/specificity in the detection of large random errors (σ > 3 mm). Sensitivity and specificity decrease rapidly for all γ-criteria as the size of error to be detected decreases below 2 mm. Predictive power is null with all criteria used in the detection of small MLC errors (σ < 0.5 mm). Optimal threshold values were established by determining which criteria maximized sensitivity and specificity. For 3%/3 mm γ-criteria, optimal threshold values range from 92% to 99%, whereas for 2%/2 mm, the range was from 77% to 94%. CONCLUSIONS: The optimal threshold values that were determined represent a maximized test sensitivity and specificity and are not subject to any user bias. When applied to the datasets that we studied, our results suggest the use of patient specific QA as a safety tool that can effectively prevent large errors (e.g., σ > 3 mm) as opposed to a tool to improve the quality of IMRT delivery.
Authors: Elizabeth M McKenzie; Peter A Balter; Francesco C Stingo; Jimmy Jones; David S Followill; Stephen F Kry Journal: Med Phys Date: 2014-12 Impact factor: 4.071
Authors: Alexander Stanforth; Liyong Lin; Jonathan J Beitler; James R Janopaul-Naylor; Chih-Wei Chang; Robert H Press; Sagar A Patel; Jennifer Zhao; Bree Eaton; Eduard E Schreibmann; James Jung; Duncan Bohannon; Tian Liu; Xiaofeng Yang; Mark W McDonald; Jun Zhou Journal: J Appl Clin Med Phys Date: 2022-02-07 Impact factor: 2.243
Authors: Dewayne L Defoor; Sotirios Stathakis; Joseph E Roring; Neil A Kirby; Panayiotis Mavroidis; Mohammad Obeidat; Nikos Papanikolaou Journal: J Appl Clin Med Phys Date: 2017-06-06 Impact factor: 2.102
Authors: Eric Laugeman; Ana Heermann; Jessica Hilliard; Michael Watts; Marshia Roberson; Robert Morris; Sreekrishna Goddu; Abhishek Sethi; Imran Zoberi; Hyun Kim; Sasa Mutic; Geoffrey Hugo; Bin Cai Journal: J Appl Clin Med Phys Date: 2020-05-05 Impact factor: 2.102
Authors: Liting Yu; Timothy L S Tang; Naasiha Cassim; Alexander Livingstone; Darren Cassidy; Tanya Kairn; Scott B Crowe Journal: J Appl Clin Med Phys Date: 2019-10-15 Impact factor: 2.102
Authors: Igor Olaciregui-Ruiz; Sam Beddar; Peter Greer; Nuria Jornet; Boyd McCurdy; Gabriel Paiva-Fonseca; Ben Mijnheer; Frank Verhaegen Journal: Phys Imaging Radiat Oncol Date: 2020-08-29
Authors: Brandon Koger; Ryan Price; Da Wang; Dolla Toomeh; Sarah Geneser; Eric Ford Journal: J Appl Clin Med Phys Date: 2020-01-21 Impact factor: 2.102