Fledelius W, Worm E, Høyer M, Grau C, Poulsen P R
Department of Oncology, Aarhus University Hospital, Aarhus, Denmark. Department of Medical Physics, Aarhus University Hospital, Aarhus, Denmark.
Phys Med Biol. 2014 Jun 7;59(11):2787-800. doi: 10.1088/0031-9155/59/11/2787. Epub 2014 May 7.
Gold markers implanted in or near a tumor can be used as x-ray visible landmarks for image based tumor localization. The aim of this study was to develop and demonstrate fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in cone-beam CT (CBCT) projections, for real-time motion management. Thirteen patients treated with conformal stereotactic body radiation therapy in three fractions had 2-3 cylindrical gold markers implanted in the liver prior to treatment. At each fraction, the projection images of a pre-treatment CBCT scan were used for automatic generation of a 3D marker model that consisted of the size, orientation, and estimated 3D trajectory of each marker during the CBCT scan. The 3D marker model was used for real-time template based segmentation in subsequent x-ray images by projecting each marker's 3D shape and likely 3D motion range onto the imager plane. The segmentation was performed in intra-treatment kV images (526 marker traces, 92,097 marker projections) and MV images (88 marker traces, 22,382 marker projections), and in post-treatment CBCT projections (42 CBCT scans, 71,381 marker projections). 227 kV marker traces with low mean contrast-to-noise ratio were excluded as markers were not visible due to MV scatter. Online segmentation times measured for a limited dataset were used for estimating real-time segmentation times for all images. The percentage of detected markers was 94.8% (kV), 96.1% (MV), and 98.6% (CBCT). For the detected markers, the real-time segmentation was erroneous in 0.2-0.31% of the cases. The mean segmentation time per marker was 5.6 ms [2.1-12 ms] (kV), 5.5 ms [1.6-13 ms] (MV), and 6.5 ms [1.8-15 ms] (CBCT). Fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in CBCT projections was demonstrated for a large dataset.
植入肿瘤内或肿瘤附近的金标记物可作为基于图像的肿瘤定位的X射线可见标志物。本研究的目的是开发并展示在治疗过程中的千伏(kV)和兆伏(MV)图像以及锥形束CT(CBCT)投影中对多个肝脏肿瘤标记物进行快速可靠的实时分割,以实现实时运动管理。13例接受三维适形立体定向体部放射治疗、分三次进行治疗的患者在治疗前于肝脏中植入了2 - 3个圆柱形金标记物。在每次治疗时,利用治疗前CBCT扫描的投影图像自动生成一个三维标记物模型,该模型包含每个标记物在CBCT扫描期间的大小、方向和估计的三维轨迹。通过将每个标记物的三维形状和可能的三维运动范围投影到成像平面上,将三维标记物模型用于后续X射线图像中基于模板的实时分割。分割在治疗过程中的kV图像(526条标记物轨迹,92,097个标记物投影)、MV图像(88条标记物轨迹,22,382个标记物投影)以及治疗后的CBCT投影(42次CBCT扫描,71,381个标记物投影)中进行。由于MV散射导致标记物不可见,227条平均对比度噪声比低的kV标记物轨迹被排除。针对有限数据集测量的在线分割时间用于估计所有图像的实时分割时间。检测到的标记物百分比分别为94.8%(kV)、96.1%(MV)和98.6%(CBCT)。对于检测到的标记物,实时分割在0.2 - 0.31% 的情况下出现错误。每个标记物的平均分割时间为5.6毫秒[2.1 - 12毫秒](kV)、5.5毫秒[1.6 - 13毫秒](MV)和6.5毫秒[1.8 - 15毫秒](CBCT)。对于一个大型数据集,已证明在治疗过程中的kV和MV图像以及CBCT投影中对多个肝脏肿瘤标记物进行快速可靠的实时分割是可行的。