Wan Hanlin, Bertholet Jenny, Ge Jiajia, Poulsen Per, Parikh Parag
Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.
Phys Med Biol. 2016 Mar 21;61(6):2552-61. doi: 10.1088/0031-9155/61/6/2552. Epub 2016 Mar 8.
In radiation therapy, fiducial markers are often implanted near tumors and used for patient positioning and respiratory gating purposes. These markers are then used to manually align the patients by matching the markers in the cone beam computed tomography (CBCT) reconstruction to those in the planning CT. This step is time-intensive and user-dependent, and often results in a suboptimal patient setup. We propose a fully automated, robust method based on dynamic programming (DP) for segmenting radiopaque fiducial markers in CBCT projection images, which are then used to automatically optimize the treatment couch position and/or gating window bounds. The mean of the absolute 2D segmentation error of our DP algorithm is 1.3 ± 1.0 mm for 87 markers on 39 patients. Intrafraction images were acquired every 3 s during treatment at two different institutions. For gated patients from Institution A (8 patients, 40 fractions), the DP algorithm increased the delivery accuracy (96 ± 6% versus 91 ± 11%, p < 0.01) compared to the manual setup using kV fluoroscopy. For non-gated patients from Institution B (6 patients, 16 fractions), the DP algorithm performed similarly (1.5 ± 0.8 mm versus 1.6 ± 0.9 mm, p = 0.48) compared to the manual setup matching the fiducial markers in the CBCT to the mean position. Our proposed automated patient setup algorithm only takes 1-2 s to run, requires no user intervention, and performs as well as or better than the current clinical setup.
在放射治疗中,基准标记物通常植入肿瘤附近,用于患者定位和呼吸门控。然后通过将锥形束计算机断层扫描(CBCT)重建图像中的标记物与计划CT中的标记物进行匹配,来手动对齐患者。这一步骤耗时且依赖用户,往往导致患者摆位欠佳。我们提出一种基于动态规划(DP)的全自动、稳健方法,用于在CBCT投影图像中分割不透射线的基准标记物,然后用于自动优化治疗床位置和/或门控窗口边界。对于39例患者的87个标记物,我们的DP算法的二维分割绝对误差均值为1.3±1.0毫米。在两个不同机构的治疗过程中,每隔3秒采集一次分次内图像。对于机构A的门控患者(8例患者,40次分次),与使用千伏透视的手动摆位相比,DP算法提高了投照精度(96±6%对91±11%,p<0.01)。对于机构B的非门控患者(6例患者,16次分次),与将CBCT中的基准标记物与平均位置进行匹配的手动摆位相比,DP算法表现相似(1.5±0.8毫米对1.6±0.9毫米,p=0.48)。我们提出的自动患者摆位算法运行仅需1 - 2秒,无需用户干预,且性能与当前临床摆位相当或更优。