O-Arm Imaging With Real-Time Control for Organ Motion Tracking: A Feasibility Study

Image-guided surgery (IGS) has become one of the most practical, safest, and fastest procedures. One of its most crucial requirements is having high-quality, high-speed CT images during operation. This achievement has been realized through the O-Arm configuration. In this regard, numerous efforts have been made to correct motion artifacts caused by respiration, with the most effective and operational solution being the autofocus method. Despite the impressive results of this method, there are still concerns about the autofocus method, including the decrease in the accuracy of results with increasing patient movement and the significant time and computing performance required for this method in cases of extensive motion. To address this issue, a 3D CBCT Imaging system was designed, focusing on selecting motion mechanisms via estimated design parameters relating to weights and dimensions. In this study, the real model was simulated using ADAMS software including the characterization of selected components, and a mathematical-dynamical model was developed, and controlled. We considered a reliable hypothetical respiration path as input to the designed system. The tracking accuracy of the applied control system can maintain errors within 1mm for the X- and Y-axis, and 1.5mm for the Z-axis after two respiration cycles for an ideal model of the respiration; such error for the Z-axis is about 2mm for actual respiration data. Tracking the rigid motion of patients may lead to a reduction of the search area in the autofocus correction method for compensating deformable motion, which can directly impact computational efforts. This dual impact approach might be observed in the computational cost of the correction algorithm and the level of error.