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Clinical practice is increasingly replacing traditional open surgical procedures with minimally invasive techniques for cancer diagnosis and therapy. These procedures typically require placement of a surgical instrument into the organ of interest with a high degree of accuracy. In general, the success of a treatment or of a diagnosis is highly dependent on the accuracy of instrument insertion and thus depends crucially on the skills and experience of the physician. While intra-operative navigation has been proven to be highly effective in interventions on bony or sufficiently rigid structures, such as the spine and the brain, computer aided soft tissue procedures are still limited to non-invasive diagnostics and surgical planning. This can primarily be attributed to the lack of robust methods for compensation of intra-interventional organ motion caused by respiration, heartbeat, patient movement and manipulation by surgical instruments. To address these issues, we developed and evaluated a clinically applicable concept for computer-assisted percutaneous needle insertion into soft tissue featuring high accuracy and an efficient guidance concept. This paper summarizes our research activities related to the project.

We assessed the targeting precision of a previously reported needle-based soft tissue navigation system in-vivo. Eight 2 ml agar nodules were implanted into the livers of two swine as tumor models. One medical expert with experience in punctures and one non-expert used the navigation system to target each nodule twice. The targeting error, which includes the system error and the user error, was defined as the distance between the applicator tip and the center of gravity of the lesions in computed tomography (CT) control scans and was 5.3 ± 2.2 mm (n = 16) for the expert, 3.2 ± 1.3 mm (n = 16) for the non-expert, and 4.2 ± 2.1 mm (n = 32) averaged over both subjects. A robust targeting precision of the order of magnitude of 4 mm could improve the treatment standard for CT-guided minimally invasive interventions in the liver dramatically.

In this study, we assessed the targeting precision of a previously reported needle-based soft tissue navigation system. For this purpose, we implanted 10 2-ml agar nodules into three pig livers as tumor models, and two of the authors used the navigation system to target the center of gravity of each nodule. In order to obtain a realistic setting, we mounted the livers onto a respiratory liver motion simulator that models the human body. For each targeting procedure, we simulated the liver biopsy workflow, consisting of four steps: preparation, trajectory planning, registration, and navigation. The lesions were successfully hit in all 20 trials. The final distance between the applicator tip and the center of gravity of the lesion was determined from control computed tomography (CT) scans and was 3.5 ± 1.1 mm on average. Robust targeting precision of this order of magnitude would significantly improve the clinical treatment standard for various CT-guided minimally invasive interventions in the liver.