Purpose Flat panel C-arm CT images acquired in the interventional suite provide valuable information regarding brain parenchyma, vasculature, and device status during the procedure. However, these images often suffer from severe streak artifacts due to the presence of metallic objects such as coils. These artifacts limit the capability to make diagnostic inferences and thus need to be reduced for better image interpretation. The main purpose of this paper is to systematically evaluate the accuracy of one such C-arm CT based metal artifact reduction (MAR) algorithm and to demonstrate its usage in both stent and flow diverter assisted coil embolization procedures. Methods C-arm CT images routinely acquired in 24 patients during coil embolization procedure (stent-assisted (12) and flow-diverter assisted (12)) were included in this study in a retrospective fashion. These images were reconstructed without and with MAR algorithm on an offline workstation and compared using quantitative image analysis metrics. This analysis was carried out to assess the improvements in both brain parenchyma and device visibility with MAR algorithm. Further, ground truth reference images from phantom experiments and clinical data were used for accurate assessment. Results Quantitative image analysis of brain parenchyma showed uniform distribution of grayscale values and reduced image noise after MAR correction. The line profile plot analysis of device profile in both phantom and clinical data demonstrated improved device visibility with MAR correction. Conclusions MAR algorithm successfully reduced streak artifacts from coil embolization in all cases, thus allowing more accurate assessment of devices and adjacent brain parenchyma.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging