放射治疗学单次分割放射外科协议建议基于假设的放射性坏死风险设定剂量标准，可以通过12 Gy正常脑体积（V12）进行预测。在本研究中，我们展示肿瘤表面积（SA）和一个只使用术前变量的简单幂函数模型可以估计和减小放射外科毒副作用。对一组215例接受单次或分割伽马刀治疗的1217个脑转移瘤病人进行了回顾性研究。单变量和多变量线性回归模型以及幂函数模型确定了哪些建模参数最能预测V12。V12幂函数模型，由归一化剂量Rx和肿瘤最长轴尺寸LAD的乘积表示（V12∼Rxn1.5*LAD2），在一个包含63例病人和302个脑转移瘤的次要数据集中进行了独立验证。表面积是V12的最佳单变量线性预测因子（adjR2=0.770），其次是最长轴尺寸（adjR2=0.755）和体积（adjR2=0.745）。幂函数模型解释了1217个转移病灶（adjR2=0.906）和245位病人V12 90%的变异（adjR2=0.896）。预测值和实际测量值之间的V12平均差异ΔV12为每个病灶（0.28±0.55）cm3和每位病人（1.0±1.2）cm3。使用一个包含63例病人和302个脑转移瘤的次要数据集对幂函数预测能力进行了验证（adjR2=0.867）（adjR2=0.825）。表面积是脑转移病灶V12的最准确的单变量预测因子。我们开发了一个可以帮助更好地估计放射性坏死风险、确定给定目标V12的处方剂量，并提供安全的剂量递增策略的脑转移瘤术前模型，而无需使用任何规划软件。版权所有 © 2023。Elsevier B.V.出版。

Radiation oncology protocols for single fraction radiosurgery recommend setting dosing criteria based on assumed risk of radionecrosis, which can be predicted by the 12 Gy normal brain volume (V12). In this study, we show that tumor surface area (SA) and a simple power-law model using only preplan variables can estimate and minimize radiosurgical toxicity.A 245-patient cohort with 1217 brain metastases treated with single or distributed gamma knife sessions was reviewed retrospectively. Univariate and multivariable linear regression models and power-law models determined which modeling parameters best predicted V12. The V12 power-law model, represented by a product of normalized Rx dose Rxn, and tumor longest axial dimension LAD (V12∼Rxn1.5*LAD2), was independently validated using a secondary 63-patient cohort with 302 brain metastases.Surface area was the best univariate linear predictor of V12 (adjR2=0.770), followed by longest axial dimension (adjR2=0.755) and volume (adjR2=0.745). The power-law model accounted for 90% variance in V12 for 1217 metastatic lesions (adjR2=0.906) and 245 patients (adjR2=0.896). The average difference ΔV12 between predicted and measured V12s was (0.28±0.55) cm3 per lesion and (1.0±1.2) cm3 per patient. The power-law predictive capability was validated using a secondary 63-patient dataset (adjR2=0.867) with 302 brain metastases (adjR2=0.825).Surface area was the most accurate univariate predictor of V12 for metastatic lesions. We developed a preplan model for brain metastases that can help better estimate radionecrosis risk, determine prescription doses given a target V12, and provide safe dose escalation strategies without the use of any planning software.Copyright © 2023. Published by Elsevier B.V.