Department of Surgery, Amsterdam University Medical Centers, Vrije Universiteit, Room J1A-222, Postbox 22660, 1100 DD, Amsterdam, The Netherlands.
Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Int J Comput Assist Radiol Surg. 2023 Aug;18(8):1533-1541. doi: 10.1007/s11548-023-02832-2. Epub 2023 Jan 31.
Image fusion merges preoperative computed tomography angiography (CTA) with live fluoroscopy during endovascular procedures to function as an overlay 3D roadmap. However, in most current systems, the registration between imaging modalities is performed manually by vertebral column matching which can be subjective, inaccurate and time consuming depending on experience. Our objective was to evaluate feasibility and accuracy of image-based automated 2D-3D image fusion between preoperative CTA and intraoperative fluoroscopy based on vertebral column matching.
A single-center study with offline procedure data was conducted in 10 consecutive patients which had endovascular aortic repair in which we evaluated unreleased automated fusion software provided by Philips (Best, the Netherlands). Fluoroscopy and digital subtraction angiography images were collected after the procedures and the vertebral column was fused fully automatically. Primary endpoints were feasibility and accuracy of bone alignment (mm). Secondary endpoint was vascular alignment (mm) between the lowest renal artery orifices. Clinical non-inferiority was defined at a mismatch of < 1 mm.
In total, 87 automated measurements and 40 manual measurements were performed on vertebrae T12-L5 in all 10 patients. Manual correction was needed in 3 of the 10 patients due to incomplete visibility of the vertebral edges in the fluoroscopy image. Median difference between automated fusion and manual fusion was 0.1 mm for bone alignment (p = 0.94). The vascular alignment was 4.9 mm (0.7-17.5 mm) for manual and 5.5 mm (1.0-14.0 mm) for automated fusion. This did not improve, due to the presence of stiff wires and stent graft.
Automated image fusion was feasible when all vertebral edges were visible. Accuracy was non-inferior to manual image fusion regarding bone alignment. Future developments should focus on intraoperative image-based correction of vascular alignment.
影像融合将术前计算机断层血管造影（CTA）与血管内手术期间的实时透视融合，作为叠加的 3D 路标。然而，在大多数当前系统中，通过椎体匹配手动执行成像模式之间的配准，这可能是主观的、不准确的，并且取决于经验，耗时较长。我们的目的是评估基于椎体匹配的术前 CTA 与术中透视的基于影像的自动 2D-3D 影像融合的可行性和准确性。
对 10 例连续接受血管内主动脉修复术的患者进行了单中心回顾性研究，评估了飞利浦（荷兰 Best）提供的未发布的自动融合软件。在手术后收集透视和数字减影血管造影图像，并对椎体进行全自动融合。主要终点是骨对齐（mm）的可行性和准确性。次要终点是肾动脉开口之间的血管对齐（mm）。定义临床非劣效性为不匹配 < 1 mm。
在所有 10 例患者中，共对 T12-L5 椎体进行了 87 次自动测量和 40 次手动测量。由于透视图像中椎体边缘不完全可见，10 例患者中有 3 例需要手动校正。自动融合与手动融合之间的中位数差异为骨对齐（mm）0.1 mm（p = 0.94）。手动融合的血管对齐为 4.9 mm（0.7-17.5 mm），自动融合为 5.5 mm（1.0-14.0 mm）。由于存在僵硬的导丝和支架移植物，这并没有改善。
当所有椎体边缘可见时，自动图像融合是可行的。在骨对齐方面，其准确性不亚于手动图像融合。未来的发展应侧重于基于术中影像的血管对齐校正。
