One of the largest geometric uncertainties in designing radiotherapy treatment plans for squamous cell cancers of the head and neck is contouring the gross tumor volume. We have previously described a method of projecting mucosal disease contours, visible on endoscopy, to volumetrically reconstructed planning computed tomography (CT) datasets, using electromagnetic (EM) tracking of a flexible endoscope, enabling rigid registration between endoscopic and CT images.

However, to achieve better accuracy for radiotherapy planning, we propose refining this initial registration with image-based registration methods. In this paper, several types of cost functions are evaluated based on accuracy and robustness. Three phantoms and eight clinical cases are used to test each cost function, with initial registration of endoscopy to CT provided by the pose of the flexible endoscope recovered from EM tracking. Cost function classes include: cross correlation, mutual information and gradient methods. For each test case, a ground truth virtual camera pose was first defined by manual registration of anatomical features visible in both real and virtual endoscope images. A new set of evenly spaced fiducial points and a sample contour were created and projected onto the CT image to be used in assessing image registration quality. A new set of 5000 displaced poses was generated by random sampling displacements along each translational and rotational dimension. At each pose, fiducial and contour points in the real image were again projected on the CT image. The cost function, fiducial registration error and contouring error values were then calculated.

While all cost functions performed well in select cases, only the normalized gradient field function consistently had registration errors less than 2 mm, which is the accuracy needed if this application of registering mucosal disease identified on optical image to CT images is to be used in the clinical practice of radiation treatment planning.

(Registration: ClinicalTrials.gov NCT02704169)

在设计头颈部鳞状细胞癌的放射治疗计划时，最大的几何不确定性之一是确定肿瘤的总体积。我们之前已经描述了一种使用柔性内窥镜的电磁（EM）跟踪，将在内窥镜上可见的粘膜疾病轮廓投影到体积重建的计划计算机断层扫描（CT）数据集的方法，从而实现内窥镜和CT图像之间的刚性配准。

但是，为了获得更好的放射治疗计划准确性，我们建议使用基于图像的注册方法来完善此初始注册。在本文中，基于准确性和鲁棒性对几种类型的成本函数进行了评估。使用三个人体模型和八个临床案例来测试每个成本函数，并通过从EM跟踪中恢复的柔性内窥镜的姿态提供内窥镜到CT的初始配准。成本函数类包括：互相关，互信息和梯度法。对于每个测试用例，首先通过手动注册在真实和虚拟内窥镜图像中可见的解剖特征来定义地面真实虚拟相机的姿势。创建了一组新的均匀间隔的基准点和样本轮廓，并将其投影到CT图像上，以用于评估图像配准质量。通过沿每个平移和旋转维度的随机采样位移生成了一组新的5000个位移姿势。在每个姿势下，真实图像中的基准点和轮廓点都再次投影到CT图像上。然后计算成本函数，基准配准误差和轮廓误差值。

尽管所有成本函数在特定情况下均能很好地执行，但只有归一化梯度场函数始终具有小于2 mm的配准误差，如果将在光学图像上识别的粘膜疾病配准到CT图像的这种应用要用于成像，则这是精度放射治疗计划的临床实践。

（注册：ClinicalTrials.gov NCT02704169）