Department of Neurosurgery, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, PR China.
Department of Neurosurgery, Huashan Hospital, Fudan University, 12 Wulumuqi (middle) Road, Shanghai, PR China.
Radiother Oncol. 2023 Feb;179:109451. doi: 10.1016/j.radonc.2022.109451. Epub 2022 Dec 28.
Gamma knife surgery (GKS) for brain metastases (BMs) adjacent to the pyramidal tract (PT) is still a challenge to conduct. PT visualization and biologically effective dose (BED) calculation on a voxel-by-voxel basis may provide data to establish clinically safe values. We aimed to assess the relationship of parameters extracted from the BED-volume histogram with outcomes of PT after GKS-treating target (adjacent BM of lung adenocarcinoma).
We formed BED-volume histograms for 672 BMs in a retrospective cohort, using 3-dimensional (3D) coordinate values of PT, target, and each iso-centre to calculate the 3D BED distribution in a 200 × 200 × 200 matrix. PT conservation failure (PTCF) was judged clinically and radiologically and classified as lesion progression and radionecrosis. Cox proportional hazards models were used to analyse 3D BED parameters. Internal validation of models was performed by bootstrapping.
There were 116 (17.3 %) subjects with PTCF in the cohort, of which 74 (11.0 %) and 42 (6.3 %) were caused by lesion progression and radionecrosis, respectively. Multivariate analysis showed that D BED and D BED significantly predicted lesion progression (P <.001). D BED and V significantly predicted radionecrosis (P <.001). The model predicting PTCF showed fair discrimination and calibration of D BED + D BED and D BED + V.
The conservation of PT in GKS for BMs of lung adenocarcinoma depends on the combination of PT-tolerated BED and target effective control BED. Therefore, a BED-volume histogram with a 3D BED algorithm is proposed to assess plan quality.
伽玛刀手术(GKS)治疗毗邻锥体束(PT)的脑转移瘤(BMs)仍然具有挑战性。基于体素的 PT 可视化和生物有效剂量(BED)计算可能为建立临床安全值提供数据。我们旨在评估从 BED-体积直方图中提取的参数与 GKS 治疗靶区(肺腺癌毗邻 BM)后 PT 结果之间的关系。
我们对回顾性队列中的 672 个 BMs 形成了 BED-体积直方图,使用 PT、靶区和每个等中心的三维(3D)坐标值来计算 200×200×200 矩阵中的 3D BED 分布。PT 保护失败(PTCF)通过临床和影像学判断,并分为病变进展和放射性坏死。Cox 比例风险模型用于分析 3D BED 参数。通过自举法对模型进行内部验证。
队列中有 116 名(17.3%)患者发生 PTCF,其中 74 名(11.0%)和 42 名(6.3%)分别由病变进展和放射性坏死引起。多变量分析表明,D BED 和 D BED 显著预测病变进展(P<.001)。D BED 和 V 显著预测放射性坏死(P<.001)。预测 PTCF 的模型显示 D BED+D BED 和 D BED+V 的区分度和校准度均较好。
GKS 治疗肺腺癌 BM 时 PT 的保护取决于 PT 耐受的 BED 和靶区有效控制的 BED 的组合。因此,提出了一种具有 3D BED 算法的 BED-体积直方图来评估计划质量。