Evaluating which plan quality metrics are appropriate for use in lung SBRT.

OBJECTIVE

Several dose metrics in the categories-homogeneity, coverage, conformity and gradient have been proposed in literature for evaluating treatment plan quality. In this study, we applied these metrics to characterize and identify the plan quality metrics that would merit plan quality assessment in lung stereotactic body radiation therapy (SBRT) dose distributions.

METHODS

Treatment plans of 90 lung SBRT patients, comprising 91 targets, treated in our institution were retrospectively reviewed. Dose calculations were performed using anisotropic analytical algorithm (AAA) with heterogeneity correction. A literature review on published plan quality metrics in the categories-coverage, homogeneity, conformity and gradient was performed. For each patient, using dose-volume histogram data, plan quality metric values were quantified and analysed.

RESULTS

For the study, the radiation therapy oncology group (RTOG) defined plan quality metrics were: coverage (0.90 ± 0.08); homogeneity (1.27 ± 0.07); conformity (1.03 ± 0.07) and gradient (4.40 ± 0.80). Geometric conformity strongly correlated with conformity index (p < 0.0001). Gradient measures strongly correlated with target volume (p < 0.0001). The RTOG lung SBRT protocol advocated conformity guidelines for prescribed dose in all categories were met in ≥94% of cases. The proportion of total lung volume receiving doses of 20 Gy and 5 Gy (V and V) were mean 4.8% (±3.2) and 16.4% (±9.2), respectively.

CONCLUSION

Based on our study analyses, we recommend the following metrics as appropriate surrogates for establishing SBRT lung plan quality guidelines-coverage % (ICRU 62), conformity (CN or CI) and gradient (R). Furthermore, we strongly recommend that RTOG lung SBRT protocols adopt either CN or CI in place of prescription isodose to target volume ratio for conformity index evaluation. Advances in knowledge: Our study metrics are valuable tools for establishing lung SBRT plan quality guidelines.