Morris Eric D, Ghanem Ahmed I, Zhu Simeng, Dong Ming, Pantelic Milan V, Glide-Hurst Carri K
Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, CA 90095, United States.
Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, MI 48202, United States.
Phys Imaging Radiat Oncol. 2021 Apr 16;18:34-40. doi: 10.1016/j.phro.2021.03.005. eCollection 2021 Apr.
Emerging evidence suggests cardiac substructures are highly radiosensitive during radiation therapy for cancer treatment. However, variability in substructure position after tumor localization has not been well characterized. This study quantifies inter-fraction displacement and planning organ at risk volumes (PRVs) of substructures by leveraging the excellent soft tissue contrast of magnetic resonance imaging (MRI).
Eighteen retrospectively evaluated patients underwent radiotherapy for intrathoracic tumors with a 0.35 T MRI-guided linear accelerator. Imaging was acquired at a 17-25 s breath-hold (resolution 1.5 × 1.5 × 3 mm). Three to four daily MRIs per patient (n = 71) were rigidly registered to the planning MRI-simulation based on tumor matching. Deep learning or atlas-based segmentation propagated 13 substructures (e.g., chambers, coronary arteries, great vessels) to daily MRIs and were verified by two radiation oncologists. Daily centroid displacements from MRI-simulation were quantified and PRVs were calculated.
Across substructures, inter-fraction displacements for 14% in the left-right, 18% in the anterior-posterior, and 21% of fractions in the superior-inferior were > 5 mm. Due to lack of breath-hold compliance, ~4% of all structures shifted > 10 mm in any axis. For the chambers, median displacements were 1.8, 1.9, and 2.2 mm in the left-right, anterior-posterior, and superior-inferior axis, respectively. Great vessels demonstrated larger displacements (> 3 mm) in the superior-inferior axis (43% of shifts) and were only 25% (left-right) and 29% (anterior-posterior) elsewhere. PRVs from 3 to 5 mm were determined as anisotropic substructure-specific margins.
This exploratory work derived substructure-specific safety margins to ensure highly effective cardiac sparing. Findings require validation in a larger cohort for robust margin derivation and for applications in prospective clinical trials.
新出现的证据表明,在癌症治疗的放射治疗过程中,心脏亚结构对辐射高度敏感。然而,肿瘤定位后亚结构位置的变异性尚未得到很好的表征。本研究通过利用磁共振成像(MRI)出色的软组织对比度,对亚结构的分次间位移和危及器官计划体积(PRV)进行量化。
18例接受回顾性评估的患者使用0.35T MRI引导的直线加速器对胸内肿瘤进行放射治疗。在17 - 25秒屏气状态下采集图像(分辨率1.5×1.5×3mm)。基于肿瘤匹配,将每位患者每天3至4次的MRI(n = 71)与计划MRI模拟图像进行刚性配准。通过深度学习或基于图谱的分割方法,将13个亚结构(如腔室、冠状动脉、大血管)传播到每日MRI图像上,并由两名放射肿瘤学家进行验证。对MRI模拟图像的每日质心位移进行量化,并计算PRV。
在所有亚结构中,左右方向14%、前后方向18%以及上下方向21%的分次间位移>5mm。由于屏气依从性不足,所有结构中约4%在任何轴向上的位移>10mm。对于腔室,左右、前后和上下轴的中位位移分别为1.8、1.9和2.2mm。大血管在上下轴上的位移较大(>3mm,占移位的43%),在其他方向(左右占25%,前后占29%)位移较小。3至5mm的PRV被确定为各向异性的亚结构特异性边界。
这项探索性工作得出了亚结构特异性安全边界,以确保有效地保护心脏。研究结果需要在更大的队列中进行验证,以得出可靠的边界并应用于前瞻性临床试验。