Department of Radiology, Hiroshima University Hospital, Kasumi 1-2-3, Minami-ku, Hiroshima, 734-8551, Japan.
Department of Diagnostic Radiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Kasumi 1-2-3, Minami-ku, Hiroshima, 734-8551, Japan.
Eur Radiol. 2019 Jan;29(1):161-167. doi: 10.1007/s00330-018-5598-5. Epub 2018 Jun 22.
The objective of this study was to investigate the usefulness of model-based iterative reconstruction (IR) for detecting neointimal formations after carotid artery stenting.
In a cervical phantom harbouring carotid artery stents, we placed simulated neointimal formations measuring 0.40, 0.60, 0.80 and 1.00 mm along the stent wall. The thickness of in-stent neointimal formations was measured on images reconstructed with filtered-back projection (FBP), hybrid IR (AIDR 3D), and model-based IR (FIRST). The clinical study included 43 patients with carotid stents. Cervical computed tomography (CT) images obtained on a 320-slice scanner were reconstructed with AIDR 3D and FIRST. Five blinded observers visually graded the likelihood of neointimal formations on AIDR 3D and AIDR 3D plus FIRST images. Carotid ultrasound images were the reference standard. We analysed results of visual grading by using a Jack-knife type receiver observer characteristics analysis software.
In the phantom study, the difference between the measured and the true diameter of the neointimal formations was smaller on FIRST than FBP or AIDR 3D images. In the clinical study, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of AIDR 3D were 58%, 88%, 83%, 67% and 73%, respectively. For AIDR 3D plus FIRST images they were 84%, 78%, 80%, 82% and 81%, respectively. The mean area under the curve was significantly higher on AIDR 3D plus FIRST than AIDR 3D images (0.82 vs 0.72; p < 0.01).
The model-based IR algorithm helped to improve diagnostic performance for the detection of neointimal formations after carotid artery stenting.
• Neointimal formations can be visualised more accurately with model-based IR. • Model-based IR improves the detection of neointimal formations after carotid artery stenting. • Model-based IR is suitable for follow up after carotid artery stenting.
本研究旨在探讨基于模型的迭代重建（IR）在检测颈动脉支架置入后新生内膜形成中的作用。
在一个模拟颈动脉支架的颈椎模型中，我们在支架壁上放置了 0.40、0.60、0.80 和 1.00mm 大小的模拟新生内膜形成物。使用滤波反投影（FBP）、混合 IR（AIDR 3D）和基于模型的 IR（FIRST）对支架内新生内膜形成物的厚度进行测量。临床研究纳入了 43 例颈动脉支架患者。使用 320 层扫描仪获得的颈椎 CT 图像分别使用 AIDR 3D 和 FIRST 进行重建。5 位盲法观察者对 AIDR 3D 和 AIDR 3D+FIRST 图像中新内膜形成的可能性进行了视觉评分。颈动脉超声图像为参考标准。我们使用 Jack-knife 型接收者操作者特征分析软件对视觉评分结果进行了分析。
在体模研究中，FIRST 图像上测量的新生内膜形成物直径与真实直径的差异小于 FBP 或 AIDR 3D 图像。在临床研究中，AIDR 3D 的敏感性、特异性、阳性预测值、阴性预测值和准确性分别为 58%、88%、83%、67%和 73%。对于 AIDR 3D+FIRST 图像，它们分别为 84%、78%、80%、82%和 81%。AIDR 3D+FIRST 图像的曲线下面积明显高于 AIDR 3D 图像（0.82 比 0.72；p < 0.01）。
基于模型的 IR 算法有助于提高颈动脉支架置入后新生内膜形成的诊断性能。
基于模型的 IR 可更准确地显示新生内膜形成物。
基于模型的 IR 提高了颈动脉支架置入后新生内膜形成的检测能力。
基于模型的 IR 适用于颈动脉支架置入后的随访。
