Toward improved 3D carotid artery imaging with Adaptive CaRdiac cOne BEAm computed Tomography (ACROBEAT)

Purpose Interventional treatments of aneurysms in the carotid artery are increasingly being supplemented with three‐dimensional (3D) x‐ray imaging. The 3D imaging provides additional information on device sizing and stent malapposition during the procedure. Standard 3D x‐ray image acquisition is a one‐size fits all model, exposing patients to additional radiation and results in images that may have cardiac‐induced motion blur around the artery. Here, we investigate the potential of a novel dynamic imaging technique Adaptive CaRdiac cOne BEAm computed Tomography (ACROBEAT) to personalize image acquisition by adapting the gantry velocity and projection rate in real‐time to changes in the patient’s electrocardiogram (ECG) trace. Methods We compared the total number of projections acquired, estimated carotid artery widths and image quality between ACROBEAT and conventional (single rotation fixed gantry velocity and acquisition rate, no ECG‐gating) scans in a simulation study and a proof‐of‐concept physical phantom experimental study. The simulation study dataset consisted of an XCAT digital software phantom programmed with five patient‐measured ECG traces and artery motion curves. The ECG traces had average heart rates of 56, 64, 76, 86, and 100 bpm. To validate the concept experimentally, we designed and manufactured the physical phantom from an 8‐mm diameter silicon rubber tubing cast into Phytagel. An artery motion curve and the ECG trace with an average heart rate of 56 bpm was passed through the phantom. To implement ACROBEAT on the Siemens ARTIS pheno angiography system for the proof‐of‐concept experimental study, the Siemens Test Automation Control System was used. The total number of projections acquired and estimated carotid artery widths were compared between the ACROBEAT and conventional scans. As the ground truth was available for the simulation studies, the image quality metrics of Root Mean Square Error (RMSE) and Structural Similarity Index (SSIM) were also utilized to assess image quality. Results In the simulation study, on average, ACROBEAT reduced the number of projections acquired by 63%, reduced carotid width estimation error by 65%, reduced RMSE by 11% and improved SSIM by 27% compared to conventional scans. In the proof‐of‐concept experimental study, ACROBEAT enabled a 60% reduction in the number of projections acquired and reduced carotid width estimation error by 69% compared to a conventional scan. Conclusion A simulation and proof‐of‐concept experimental study was completed applying a novel dynamic imaging protocol, ACROBEAT, to imaging the carotid artery. The ACROBEAT results showed significantly improved image quality with fewer projections, offering potential applications to intracranial interventional procedures negatively affected by cardiac motion.