Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.
Med Phys. 2010 Feb;37(2):885-96. doi: 10.1118/1.3284541.
Coronary CT angiography (CCTA) is a high-resolution three-dimensional imaging technique for the evaluation of coronary arteries in suspected or confirmed coronary artery disease (CAD). Coregistration of serial CCTA scans would allow precise superimposition of images obtained at two different points in time, which could aid in recognition of subtle changes and precise monitoring of coronary plaque progression or regression. To this end, the authors aimed at developing a fully automatic nonlinear volume coregistration for longitudinal CCTA scan pairs.
The algorithm combines global displacement and local deformation using nonlinear volume coregistration with a volume-preserving constraint. Histogram matching of intensities between two serial scans is performed prior to nonlinear coregistration with dense nonparametric local deformation in which sum of squared differences is used as a similarity measure. The approximate segmentation of coronary arteries obtained from commercially available software provides initial anatomical landmarks for the coregistration algorithm that help localize and emphasize the structure of interest. To avoid possible bias caused by incorrect segmentation, the authors convolve the Gaussian kernel with the segmented binary coronary tree mask and define an extended weighted region of interest. A multiresolution approach is employed to represent coarse-to-fine details of both volumes and the energy function is optimized using a gradient descent method. The authors applied the algorithm in ten paired CCTA datasets (20 scans in total) obtained within 10.7 +/- 5.7 months from each other on a dual source CT scanner to monitor progression of CAD.
Serial CCTA coregistration was successful in 9/10 cases as visually confirmed. The global displacement and local deformation of target registration error obtained from four anatomical landmarks were 2.22 +/- 1.15 and 1.56 +/- 0.74 mm, respectively, and the inverse consistency error of local deformation was 0.14 +/- 0.06 mm. The observer variability between two expert observers was 1.31 +/- 0.91 mm.
The proposed coregistration algorithm demonstrates potential to accurately register serial CCTA scans, which may allow direct comparison of calcified and noncalcified atherosclerotic plaque changes between the two scans.
冠状动脉 CT 血管造影术（CCTA）是一种用于评估疑似或确诊冠心病（CAD）冠状动脉的高分辨率三维成像技术。连续 CCTA 扫描的配准可实现两次不同时间点获得的图像的精确叠加，有助于识别细微变化并精确监测冠状动脉斑块的进展或消退。为此，作者旨在开发一种用于纵向 CCTA 扫描对的全自动非线性容积配准。
该算法使用具有体积保持约束的非线性体积配准，结合全局位移和局部变形。在进行非线性配准之前，对两次连续扫描进行强度直方图匹配，使用均方差作为相似性度量进行密集非参数局部变形。从商业上可用的软件获得的冠状动脉近似分割为配准算法提供初始解剖学标记，有助于定位和强调感兴趣的结构。为避免不正确分割可能导致的偏差，作者用高斯核卷积分割的二进制冠状动脉树掩模，并定义扩展的加权感兴趣区域。采用多分辨率方法表示两个体积的粗到细细节，并使用梯度下降方法优化能量函数。作者在双源 CT 扫描仪上对 10 对 CCTA 数据集（总共 20 次扫描）进行了应用，这些数据集彼此之间的时间间隔为 10.7 ± 5.7 个月，以监测 CAD 的进展。
9/10 例的连续 CCTA 配准成功，经视觉确认。从四个解剖学标记获得的目标配准误差的全局位移和局部变形分别为 2.22 ± 1.15mm 和 1.56 ± 0.74mm，局部变形的逆一致性误差为 0.14 ± 0.06mm。两位专家观察者之间的观察者变异性为 1.31 ± 0.91mm。
所提出的配准算法具有准确配准连续 CCTA 扫描的潜力，这可能允许在两次扫描之间直接比较钙化和非钙化动脉粥样硬化斑块的变化。
