Deformable planning CT to cone-beam CT image registration in head-and-neck cancer
Deformable planning CT to cone-beam CT image registration in head-and-neck cancer
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DOI：
10.1118/1.3554647
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发表时间：
2011-04-01
期刊：
影响因子：
3.8
通讯作者：
D'Souza, Warren D.
中科院分区：
文献类型：
--
作者：
Hou, Jidong;Guerrero, Mariana;D'Souza, Warren D.
目的：本工作的目的是实现和验证一种可变形CT与锥束计算机断层扫描（CBCT）图像在头颈癌中的配准方法，最终实现CBCT上目标的自动描绘。方法：12例头颈癌患者在5 ~ 7周的治疗期内分别行计划CT和每周CBCT检查。将这些患者的12张计划CT图像（运动图像）通过对称力Demons算法并采用多分辨率方案注册到他们的每周CBCT图像（固定图像）中。直方图匹配用于补偿两类图像之间的强度差异。利用已知的9个解剖点作为配准目标，利用目标配准误差（TRE）评价配准的准确性。此外，将规划CT上绘制的感兴趣区域（ROI）轮廓变形为CBCT图像，并评估配准轮廓与人工圈定轮廓之间的体积重叠指数（VOI）。结果：9个目标点的平均TRE值均小于规划CT的层厚3.0 mm。在评估配准精度的369个目标点中，平均TRE值为2.6 +/- 0.6 mm。骨组织靶的平均TRE为2.4 +/- 0.2 mm，软组织靶的平均TRE为2.8 +/- 0.2 mm。注册和手动绘制的ROI等高线之间的平均VOI为76.2 +/- 4.6%，这与之前的研究报告一致。结论：作者实现并验证了一种可变形图像配准方法，用于头颈癌病例的规划CT图像与每周CBCT图像的配准。TRE值的准确性表明，它们可以作为CBCT上目标自动圈定的一个有前途的工具。(C) 2011年美国医学物理学家协会。(DOI: 10.1118/1.3554647)
Purpose: The purpose of this work was to implement and validate a deformable CT to cone-beam computed tomography (CBCT) image registration method in head-and-neck cancer to eventually facilitate automatic target delineation on CBCT.Methods: Twelve head-and-neck cancer patients underwent a planning CT and weekly CBCT during the 5-7 week treatment period. The 12 planning CT images (moving images) of these patients were registered to their weekly CBCT images (fixed images) via the symmetric force Demons algorithm and using a multiresolution scheme. Histogram matching was used to compensate for the intensity difference between the two types of images. Using nine known anatomic points as registration targets, the accuracy of the registration was evaluated using the target registration error (TRE). In addition, region-of-interest (ROI) contours drawn on the planning CT were morphed to the CBCT images and the volume overlap index (VOI) between registered contours and manually delineated contours was evaluated.Results: The mean TRE value of the nine target points was less than 3.0 mm, the slice thickness of the planning CT. Of the 369 target points evaluated for registration accuracy, the average TRE value was 2.6 +/- 0.6 mm. The mean TRE for bony tissue targets was 2.4 +/- 0.2 mm, while the mean TRE for soft tissue targets was 2.8 +/- 0.2 mm. The average VOI between the registered and manually delineated ROI contours was 76.2 +/- 4.6%, which is consistent with that reported in previous studies.Conclusions: The authors have implemented and validated a deformable image registration method to register planning CT images to weekly CBCT images in head-and-neck cancer cases. The accuracy of the TRE values suggests that they can be used as a promising tool for automatic target delineation on CBCT. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3554647]