Gong Lixin, Pathak Sayan, Alessio Adam, Kinahan Paul
Insightful Corporation, 1700 Westlake Ave., Suite 500, Seattle, WA 98109, United States.
Comput Med Imaging Graph. 2006 Dec;30(8):469-77. doi: 10.1016/j.compmedimag.2006.09.013. Epub 2006 Nov 2.
Positron emission tomography (PET) imaging is rapidly expanding its role in clinical practice for cancer management. The high sensitivity of PET for functional abnormalities associated with cancer can be confounded by the minimal anatomical information it provides for cancer localization. Computed tomography (CT) provides detailed anatomical information but is less sensitive to pathologies than PET. Thus, combining (i.e., registering) PET and CT images would enable both accurate and sensitive cancer localization with respect to detailed patient anatomy. An additional application area of registration is to align CT-CT scans from serial studies on a patient on a PET/CT scanner to facilitate accurate assessment of therapeutic response from the co-aligned PET images. To facilitate image fusion, we are developing a deformable registration software system using mutual information and a B-spline model of the deformation. When applying deformable registration to whole body images, one of the obstacles is that the arms are present in PET images but not in CT images or are in different positions in serial CT images. This feature mismatch requires a preprocessing step to remove the arms where present and thus adds a manual step in an otherwise automatic algorithm. In this paper, we present a simple yet effective method for automatic arm removal. We demonstrate the efficiency and robustness of this algorithm on both clinical PET and CT images. By streamlining the entire registration process, we expect that the fusion technology will soon find its way into clinics, greatly benefiting cancer diagnosis, staging, therapy planning and treatment monitoring.
正电子发射断层扫描（PET）成像在癌症治疗的临床实践中的作用正在迅速扩大。PET对与癌症相关的功能异常具有高灵敏度，但它为癌症定位提供的解剖学信息极少，这可能会混淆诊断结果。计算机断层扫描（CT）提供详细的解剖学信息，但对病变的敏感度低于PET。因此，将PET和CT图像结合（即配准）能够在详细的患者解剖结构基础上实现准确且灵敏的癌症定位。配准的另一个应用领域是在PET/CT扫描仪上对患者的系列研究中的CT-CT扫描进行对齐，以便从配准后的PET图像中准确评估治疗反应。为了便于图像融合，我们正在开发一种使用互信息和变形B样条模型的可变形配准软件系统。在将可变形配准应用于全身图像时，一个障碍是PET图像中有手臂，但CT图像中没有，或者在系列CT图像中手臂处于不同位置。这种特征不匹配需要一个预处理步骤来去除存在的手臂，从而在原本自动的算法中增加了一个手动步骤。在本文中，我们提出了一种简单而有效的自动去除手臂的方法。我们在临床PET和CT图像上展示了该算法的效率和鲁棒性。通过简化整个配准过程，我们预计融合技术将很快进入临床，极大地有益于癌症诊断、分期、治疗规划和治疗监测。
