Respiratory motion compensation for CT-guided interventions in the liver

Abstract

Computed tomography (CT) guided minimally invasive procedures in the liver, such as tumor biopsy and thermal ablation therapy, require precise targeting of hepatic structures that are subject to breathing motion. To facilitate needle placement, we introduced a navigation system which uses needle-shaped optically tracked navigation aids and a real-time deformation model to continuously estimate the position of a moving target.

In this study, we assessed the target position estimation accuracy of our system in vitro with a custom-designed respiratory liver motion simulator. Several real-time compatible transformations were compared as a basis for the deformation model and were evaluated in a set of experiments using different arrangements of three navigation aids in two porcine and two human livers. Furthermore, we investigated different placement strategies for the case where only two needles are used for motion compensation.

Depending on the transformation and the placement of the navigation aids, our system yielded a root mean square (RMS) target position estimation error in the range of 0.7 mm to 2.9 mm throughout the breathing cycle generated by the motion simulator. Affine transformations and spline transformations performed comparably well (overall RMS < 2 mm) and were considerably better than rigid transformations. When two navigation aids were used for motion compensation instead of three, a diagonal arrangement of the needles yielded the best results.

This study suggests that our navigation system could significantly improve the clinical treatment standard for CT-guided interventions in the liver.

• Image-guided systems
• tracking
• respiratory motion compensation
• needle insertion
• navigation
• deformation model
• interventional radiology