IEEE Trans Med Imaging. 2018 Sep;37(9):1999-2009. doi: 10.1109/TMI.2018.2806310. Epub 2018 Feb 14.
Rotational coronary angiography using C-arm angiography systems enables intra-procedural 3-D imaging that is considered beneficial for diagnostic assessment and interventional guidance. Despite previous efforts, rotational angiography was not yet successfully established in clinical practice for coronary artery procedures due to challenges associated with substantial intra-scan respiratory and cardiac motion. While gating handles cardiac motion during reconstruction, respiratory motion requires compensation. State-of-the-art algorithms rely on 3-D / 2-D registration that requires an uncompensated reconstruction of sufficient quality. To overcome this limitation, we investigate two prior-free respiratory motion estimation methods based on the optimization of: 1) epipolar consistency conditions (ECCs) and 2) a task-based auto-focus measure (AFM). The methods assess redundancies in projection images or impose favorable properties of 3-D space, respectively, and are used to estimate the respiratory motion of the coronary arteries within rotational angiograms. We evaluate our algorithms on the publicly available CAVAREV benchmark and on clinical data. We quantify reductions in error due to respiratory motion compensation using a dedicated reconstruction domain metric. Moreover, we study the improvements in image quality when using an analytic and a novel temporal total variation regularized algebraic reconstruction algorithm. We observed substantial improvement in all figures of merit compared with the uncompensated case. Improvements in image quality presented as a reduction of double edges, blurring, and noise. Benefits of the proposed corrections were notable even in cases suffering little corruption from respiratory motion, translating to an improvement in the vessel sharpness of (6.08 ± 4.46)% and (14.7 ± 8.80)% when the ECC-based and the AFM-based compensation were applied. On the CAVAREV data, our motion compensation approach exhibits an improvement of (27.6 ± 7.5)% and (97.0 ± 17.7)% when the ECC and AFM were used, respectively. At the time of writing, our method based on AFM is leading the CAVAREV scoreboard. Both motion estimation strategies are purely image-based and accurately estimate the displacements of the coronary arteries due to respiration. While current evidence suggests the superior performance of AFM, future work will further investigate the use of ECC in the context of angiography as they solely rely on geometric calibration and projection-domain images.
使用 C 臂血管造影系统进行旋转冠状动脉造影可实现术中 3D 成像，这被认为有利于诊断评估和介入指导。尽管此前已经做了很多努力，但由于与扫描过程中呼吸和心脏运动相关的挑战，旋转血管造影术尚未成功应用于冠状动脉手术。门控技术可在重建过程中处理心脏运动，但需要对呼吸运动进行补偿。最先进的算法依赖于 3D/2D 配准，这需要足够质量的未补偿重建。为了克服这一限制，我们研究了两种基于优化的无先验呼吸运动估计方法：1）对极一致性条件（ECC）和 2）基于任务的自动对焦度量（AFM）。这些方法分别评估投影图像中的冗余或施加 3D 空间的有利特性，并用于估计旋转血管造影中冠状动脉的呼吸运动。我们在公开的 CAVAREV 基准和临床数据上评估了我们的算法。我们使用专门的重建域度量来量化由于呼吸运动补偿而导致的误差减少。此外，我们还研究了使用解析和新颖的时间全变分正则化代数重建算法时图像质量的提高。与未补偿的情况相比，我们在所有的性能指标上都观察到了显著的改善。图像质量的改善表现为减少了双边缘、模糊和噪声。即使在呼吸运动干扰较小的情况下，所提出的校正方法也具有明显的优势，可使血管锐度分别提高（6.08±4.46）%和（14.7±8.80）%。在 CAVAREV 数据上，我们的运动补偿方法在使用 ECC 和 AFM 时分别提高了（27.6±7.5）%和（97.0±17.7）%。在撰写本文时，我们基于 AFM 的方法在 CAVAREV 排行榜上领先。这两种运动估计策略都是纯基于图像的，并且可以准确估计冠状动脉因呼吸而产生的位移。虽然目前的证据表明 AFM 的性能更好，但未来的工作将进一步研究在血管造影术中使用 ECC 的情况，因为它们仅依赖于几何校准和投影域图像。
