Introduction: Flat panel angiographic C arm system has come to the fore in last decade and has revolutionized the intra-procedure imaging. However, FP-CT has limitations due to beam hardening metal artifact causing sub-optimal evaluation of blood vessels and CSF spaces around the implant. In this study we used filtered back projection based Metal Artifact reduction algorithm (MARA) to reduce the artifacts

Methods: 32 images from 8 patients were evaluated.We selected varied metal artifact images, stent-coil (n=4); coil alone (n=1), surgical clip (n-1) , carotid stent(n=1) , AVM Onyx(n=1). All C-arm CT acquisitions were performed on a flat-panel detector angiography system (Infinix-i, Toshiba, Tochigi, Japan) with LCI rotational protocols. After applying Metal-artifat-reduction-algorith(MARA) we performed Objective assessment of image analysis by measuring the ROI HU(Region of interest Hounsfield’s units) units and subjectively by analyzing the scores obtained by two senior Endovascular Neurosurgeons. The intra-rater agreements are measured by Kendall’s tau-b correlation coefficient and the inter-rater agreements are measured by kappa statistics

Results: 32 Images were analyzed. When the mean of maximum HU was compared between the two cohorts, it was significantly lower when MARA was applied to images (p=.018). After the application of MARA the image quality was improved and the difference was significant (p<0.05) when the images were assessed on the basis of amount of artifacts; Visibility around the device; Visibility of the device such as stent or coil. The intra-rater agreement was significant in both Rater 1 and 2, when MARA was applied to images. The kappa statistics showed that the inter-rater agreement was most prominent when MAR images were considered. In the case of device visibility it reached 0.57.

Conclusions: The data showed impressive results when MARA is applied to images. Maximum HU units in the ROI were reduced after the application of MARA, suggesting lesser metal artifacts. The mean score of raters was significantly higher when MARA was applied, suggesting better image quality. Also, the inter-rater agreement was good, ensuring that the images with MARA have better and uniform readability across physicians

Patient Care: 1. Our Metal reduction algorithm, considerably reduces intraprocedure imaging artifacts, thus more information can be obtained without transferring the patient to CT scanner.

Learning Objectives: 1. Application of Metal artifact reduction Algorithm reduces the artifacts considerably, thus adding valuable information to intra-procedure imaging.

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