Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia 30322, USA.
J Appl Clin Med Phys. 2012 Sep 6;13(5):3829. doi: 10.1120/jacmp.v13i5.3829.
Deformable registration has migrated from a research topic to a widely used clinical tool that can improve radiotherapeutic treatment accuracy by tracking anatomical changes. Although various mathematical formulations have been reported in the literature and implemented in commercial software, we lack a straightforward method to verify a given solution in routine clinical use. We propose a metric using concepts derived from vector analysis that complements the standard evaluation tools to identify unrealistic wrappings in a displacement field. At the heart of the proposed procedure is identification of vortexes in the displacement field that do not correspond to underlying anatomical changes. Vortexes are detected and their intensity quantified using the CURL operator and presented as a vortex map overlaid on the original anatomy for rapid identification of problematic regions. We show application of the proposed metric on clinical scenarios of adaptive radiotherapy and treatment response assessment, where the CURL operator quantitatively detected errors in the displacement field and identified problematic regions that were invisible to classical voxel-based evaluation methods. Unrealistic warping not visible to standard voxel-based solution assessment can produce erroneous results when the deformable solution is applied on a secondary dataset, such as dose matrix in adaptive therapy or PET data for treatment response assessment. The proposed metric for evaluating deformable registration provides increased usability and accuracy of detecting unrealistic deformable registration solutions when compared to standard intensity-based approaches. It is computationally efficient and provides a valuable platform for the clinical acceptance of image-guided radiotherapy.
变形配准已经从一个研究课题发展成为一种广泛使用的临床工具,可以通过跟踪解剖结构的变化来提高放射治疗的准确性。尽管文献中已经报道了各种数学公式,并在商业软件中实现,但我们缺乏一种直接的方法来验证常规临床应用中给定的解决方案。我们提出了一种使用向量分析概念的度量标准,补充了标准评估工具,以识别位移场中的不切实际的包裹。所提出的方法的核心是识别位移场中的涡旋,这些涡旋与潜在的解剖变化不对应。涡旋是通过 CURL 算子检测到的,并使用该算子量化其强度,并以涡旋图的形式叠加在原始解剖结构上,以便快速识别有问题的区域。我们展示了该度量标准在自适应放射治疗和治疗反应评估的临床场景中的应用,其中 CURL 算子定量检测到位移场中的错误,并识别出经典基于体素的评估方法无法识别的有问题的区域。当在二次数据集(例如自适应治疗中的剂量矩阵或用于治疗反应评估的 PET 数据)上应用变形解决方案时,变形解决方案中不可见的不切实际的扭曲可能会产生错误的结果。与基于标准强度的方法相比,用于评估变形配准的新度量标准在检测不切实际的变形配准解决方案方面提供了更高的可用性和准确性。它具有计算效率,并为图像引导放射治疗的临床接受提供了有价值的平台。