Neointimal formation after carotid artery stenting: phantom and clinical evaluation of model-based iterative reconstruction (MBIR).

Abstract

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.