Abstract

The energy index (EI) is a measure of dose homogeneity within a target volume calculated by the integral dose divided by the product of prescription dose and tumor volume. To assess whether a higher EI is associated with greater local control for brain metastases (BMs) treated by Gamma Knife radiosurgery (GKRS). We reviewed all patients treated with GKRS for BM at our institution between January 2009 and February 2014. Data on the prescription dose, prescription isodose line, minimum dose, mean dose, integral dose, tumor volume, and EI were collected. Tumor response was assessed by reviewing follow-up brain imaging studies and classified according to the Response Evaluation Criteria in Solid Tumors. Local control per lesion and dosimetric prognostic factors for local control were assessed by univariate and multivariate Cox proportional hazards regression analyses. Of 213 patients treated, 126 had follow-up imaging available with a median follow-up of 6 months. Three hundred seventy-three individual tumors were analyzed. Of these, 133 showed a complete response, 157 showed a partial response, 46 remained stable, and 37 developed local failure. Tumors with EI ≥1.6 mJ·mL(-1)·Gy(-1) showed a higher rate of complete response. Local control rates at 6, 11, and 17 months were 95.4%, 86.5%, and 81.5%, respectively. On univariate analysis, the following factors were associated with higher rates of local failure: prescription doses of 16 and 18 Gy compared with a prescription dose of 20 Gy. The following factors were associated with a greater rate of local control: maximum dose and mean dose. On multivariate analysis, the only statistically significant factor associated with a greater rate of local failure was prescription dose of 16 Gy compared with 20 Gy. GKRS for BM results in a high rate of local control with an 11-month rate of 86.5%. A higher EI was not significantly associated with a higher rate of local control on multivariate analysis. Prescription dose was found to be the only significant predictor of local control on multivariate analysis.

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