Interrater reliability of the categorization of late radiographic changes after lung stereotactic body radiation therapy.

PURPOSE

Radiographic changes after lung stereotactic body radiation therapy (SBRT) have been categorized into 4 groups: modified conventional pattern (A), mass-like fibrosis; (B), scar-like fibrosis (C), and no evidence of increased density (D). The purpose of this study was to assess the interrater reliability of this categorization system in patients with early-stage non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

Seventy-seven patients were included in this study, all treated with SBRT for early-stage (T1/2) NSCLC at a single institution, with a minimum follow-up of 6 months. Six experienced clinicians familiar with post-SBRT radiographic changes scored the serial posttreatment CT images independently in a blinded fashion. The proportion of patients categorized as A, B, C, or D at each interval was determined. Krippendorff's alpha (KA), Multirater kappa (M-kappa), and Gwet's AC1 (AC1) scores were used to establish interrater reliability. A leave-one-out analysis was performed to demonstrate the variability among raters. Interrater agreement of the first and last 20 patients scored was calculated to explore whether a training effect existed.

RESULTS

The number of ratings ranged from 450 at 6 months to 84 at 48 months of follow-up. The proportion of patients in each category was as follows: A, 45%; B, 16%; C, 13%; and D, 26%. KA and M-kappa ranged from 0.17 to 0.34. AC1 measure range was 0.22 to 0.48. KA increased from 0.24 to 0.36 at 12 months with training. The percent agreement for pattern A peaked at 12 month with a 54% chance of having >50% raters in agreement and decreased over time, whereas that for patterns B and C increased over time to a maximum of 20% and 22%, respectively.

CONCLUSION

This post-SBRT radiographic change categorization system has modest interrater agreement, and there is a suggestion of a training effect. Patterns of fibrosis evolve after SBRT and alternative categorization systems should be evaluated.