WE-A-134-11: Registration of Clinical Volumes to Beams-Eye-View Images for Real-Time Tracking.
WE-A-134-11: Registration of Clinical Volumes to Beams-Eye-View Images for Real-Time Tracking.
复制标题
WE-A-134-11：将临床体积注册到光束眼视图图像以进行实时跟踪。
DOI：
10.1118/1.4815517
复制
发表时间：
2013
期刊：
影响因子：
3.8
通讯作者：
R. Berbeco
中科院分区：
文献类型：
--
作者：
J. Bryant;J. Rottmann;J. Lewis;P. Keall;R. Berbeco
目的
开发将放疗期间获取的电影模式电子射野成像设备 (EPID) 图像与计划计算机断层扫描 (CT) 图像进行 2D/3D 配准，并将其与相对的无标记 EPID 肿瘤跟踪相结合。这些方法将共同提供医生定义的体积（例如治疗区域的总肿瘤体积（GTV））之间的自动绝对跟踪。
方法
在肺部 SBRT 病例的治疗过程中，连续获取 EPID 图像。使用无标记多模板算法跟踪相对运动，该算法的准确性先前已通过手动跟踪进行确认和评估。然后，每张图像都经过基于强度的 2D/3D 配准到计划 CT。为了最大限度地减少运动模糊的影响，使用了四维计算机断层扫描 (4DCT) 的呼气末阶段。通过校准曲线将体积从亨斯菲尔德单位转换为电子密度，并为束流几何形状生成 DRR。使用 DRR 和 EPID 图像之间的归一化互相关 (NCC)，找到了最佳的平面刚性变换。然后将其应用于计划 CT 中的轮廓，将其映射到 EPID 图像域中。通过大量患者数据找到了登记的最佳呼吸阶段。
结果
事实证明，2D/3D 配准的成功仅在呼吸周期的某些阶段是准确的。通过此时注册并使用相对跟踪，我们在整个治疗过程中成功跟踪 EPID 图像中的目标体积。
结论
通过相对跟踪和相位相关 EPID/4DCT 配准的结合，可以跟踪 EPID 图像上的临床体积。肿瘤体积相对于治疗区域的了解为运动管理、自适应放射治疗和输送剂量计算等未来应用提供了强大的信息。
PURPOSE
To develop the 2D/3D registration of cine mode electronic portal imaging device (EPID) images acquired during radiotherapy treatment to the planning computed tomography (CT) images and combine it with relative, markerless EPID tumor tracking. Together the methods will provide an automatic absolute tracking between physician defined volumes such as the gross tumor volume (GTV) the treatment field.
METHODS
During treatment of lung SBRT cases, EPID images were continuously acquired. The relative motion was tracked using a markerless multitemplate algorithm whose accuracy was previously confirmed and assessed with manual tracking. Each image then underwent an intensity based 2D/3D registration to the planning CT. In order to minimize the effect of motion blur, the end-of-exhale phase of the four dimensional computed tomography (4DCT) was used. The volume was converted from Hounsfield units into electron density by a calibration curve and DRRs were generated for the beam geometry. Using normalized cross correlation (NCC) between the DRR and EPID image, the best in plane rigid transformation was found. It was then applied to contours in the planning CT, mapping them into the EPID image domain. The best breathing phase for the registration was found with a large set of patient data.
RESULTS
The success of 2D/3D registration proved accurate only over certain phases of the breathing cycle. By registering at this time and using relative tracking, we successfully track target volumes in the EPID images throughout the entire treatment delivery.
CONCLUSIONS
Through the combination of relative tracking and phase dependent EPID/4DCT registration, it is possible to track clinical volumes on EPID images. This knowledge of tumor volumes relative to the treatment field provides powerful information for future applications like motion management, adaptive radiotherapy and delivered dose calculations.