Cunliffe Alexandra R, White Bradley, Justusson Julia, Straus Christopher, Malik Renuka, Al-Hallaq Hania A, Armato Samuel G
Department of Radiology, The University of Chicago, 5841 S. Maryland Ave., MC 2026, Chicago, IL, 60637, USA.
Department of Radiation & Cellular Oncology, The University of Chicago, 5758 S. Maryland Ave., Chicago, IL, 60637, USA.
J Digit Imaging. 2015 Dec;28(6):755-60. doi: 10.1007/s10278-015-9789-1.
We evaluated the image registration accuracy achieved using two deformable registration algorithms when radiation-induced normal tissue changes were present between serial computed tomography (CT) scans. Two thoracic CT scans were collected for each of 24 patients who underwent radiation therapy (RT) treatment for lung cancer, eight of whom experienced radiologically evident normal tissue damage between pre- and post-RT scan acquisition. For each patient, 100 landmark point pairs were manually placed in anatomically corresponding locations between each pre- and post-RT scan. Each post-RT scan was then registered to the pre-RT scan using (1) the Plastimatch demons algorithm and (2) the Fraunhofer MEVIS algorithm. The registration accuracy for each scan pair was evaluated by comparing the distance between landmark points that were manually placed in the post-RT scans and points that were automatically mapped from pre- to post-RT scans using the displacement vector fields output by the two registration algorithms. For both algorithms, the registration accuracy was significantly decreased when normal tissue damage was present in the post-RT scan. Using the Plastimatch algorithm, registration accuracy was 2.4 mm, on average, in the absence of radiation-induced damage and 4.6 mm, on average, in the presence of damage. When the Fraunhofer MEVIS algorithm was instead used, registration errors decreased to 1.3 mm, on average, in the absence of damage and 2.5 mm, on average, when damage was present. This work demonstrated that the presence of lung tissue changes introduced following RT treatment for lung cancer can significantly decrease the registration accuracy achieved using deformable registration.
我们评估了在连续计算机断层扫描(CT)之间存在辐射诱导的正常组织变化时,使用两种可变形配准算法所实现的图像配准精度。对24例接受肺癌放射治疗(RT)的患者,每人收集了两次胸部CT扫描图像,其中8例在放疗前后扫描期间出现了影像学可见的正常组织损伤。对于每位患者,在放疗前后扫描图像的解剖学对应位置手动放置100对地标点。然后使用(1)Plastimatch demons算法和(2)Fraunhofer MEVIS算法将每次放疗后的扫描图像与放疗前的扫描图像进行配准。通过比较在放疗后扫描图像中手动放置的地标点与使用两种配准算法输出的位移矢量场从放疗前扫描图像自动映射到放疗后扫描图像的点之间的距离,评估每对扫描图像的配准精度。对于这两种算法,当放疗后扫描图像中存在正常组织损伤时,配准精度均显著降低。使用Plastimatch算法时,在无辐射诱导损伤的情况下,配准精度平均为2.4毫米,在有损伤的情况下,平均为4.6毫米。相反,当使用Fraunhofer MEVIS算法时,在无损伤的情况下,配准误差平均降至1.3毫米,在有损伤的情况下,平均为2.5毫米。这项研究表明,肺癌放疗后肺部组织变化的存在会显著降低使用可变形配准所实现的配准精度。