Analysis of Aperture-based Complexity Metrics and Their Effect on Patient-specific Quality Assurance in...

Identifying plans at risk of patient-specific quality assurance (PSQA) failure through complexity metrics can reduce the workload while maintaining quality. This study evaluates complexity metrics as predictors of PSQA outcomes.

A retrospective analysis was conducted on 192 IMRT plans for head-and-neck cancer. Complexity metrics were calculated using an in-house Python program. PSQA was performed with 3%/2-mm gamma passing rate (GPR) criteria, with plans classified as "Pass" (GPR ≥95%) or "Fail." Statistical analyses, including Spearman's correlation and receiver operating characteristic analysis, assessed the metrics' predictive value.

Passing plans had an average GPR of 98.64 ± 1.33%, compared to 92.17 ± 2.35% for failing plans. The mean small area segment (MSAS) 5mm metric, with a threshold of 0.085, achieved a true positive rate of 38.17% and a false positive rate of 3.1%. Beam modulation and beam area indices also significantly differed between passing and failing plans.

MSAS5 and edge metrics showed strong potential for identifying high-risk plans. These metrics can guide targeted PSQA, improving workflow efficiency without compromising treatment safety.