WE‐G‐217BCD‐06: Fully Incorporated Scanning Geometry for Improved Accuracy in C‐Arm CBCT Image Reconstruction

Abstract

The adoption of C-arm cone-beam CT (CBCT) can minimize interruption to the interventional workflow. However, C-arm gantry rotation can be susceptible to gravity and mechanical instability, therefore resulting images with contamination of tilting and wobbling motion. The purpose of this work is to investigate and demonstrate potential improvement of C-arm CBCT images by tailoring and applying an innovative iterative algorithm that can fully incorporate accurate scanning geometry. A clinical C-arm CBCT system (Toshiba Infinix-i, Japan) was used for collecting projection data of a patient's brain with aneurysm. A mask scan was performed before contrast was injected, and a contrast scan was performed during continuous contrast feeding. During each scan, 108 projections were acquired over a range of approximately 200 degrees within about 4.6 seconds. Logarithm subtraction was then carried out view by view to obtain 108 projections of virtually only the vasculature. An iterative algorithm, referred to as the ASD-POCS algorithm, was modified to fully incorporate calibration data characterizing the actual scan geometry that deviates from a circular trajectory due to gantry tilting and wobbling. We then applied both FDK and ASD-POCS algorithms to reconstructing image from the acquired patient data. In FDK reconstructions without considering C-arm tilting and wobbling motion, artifacts can be observed, which break vessel continuity and compromise image's clinical utility. We then performed FDK reconstructions by incorporating the system geometry in the back-projection step and obtained improved vessel continuity. Finally we applied the ASD- POCS algorithm by incorporating calibration data in the forward- and back- projector, and obtained reconstructions with further improvement on the recovery of small, secondary vascular branches. Appropriately developed iterative algorithms can improve C-arm CBCT image quality by fully incorporating scanning geometry, and can potentially enable spatial-resolution demanding applications which can be challenging to achieve with the FDK algorithm.