An open electromagnetic tracking framework applied to targeted liver tumour ablation

Area of Science:

• Medical Imaging and Image-Guided Interventions
• Biomedical Engineering
• Surgical Navigation Technologies

Background:

• Electromagnetic tracking (EMT) is crucial for navigating image-guided procedures, offering high accuracy in non-line-of-sight environments where optical tracking fails.
• EMT is particularly valuable for interventions like percutaneous radiofrequency ablation of liver lesions, where instrument visibility can be challenging.
• Current EMT systems face limitations due to the "blackbox" nature of commercial algorithms, hindering the integration of novel accuracy and error compensation improvements.

Purpose of the Study:

• To introduce a software framework facilitating the integration of novel electromagnetic tracking (EMT) designs into image-guided interventions.
• To enable advancements in EMT system accuracy, precision, and error compensation through an open-source approach.
• To demonstrate the framework's utility in a preclinical setting for targeted liver ablation therapy.

Main Methods:

• Development of an open-source software framework for EMT systems, implemented in Python.
• Demonstration of the framework using the Anser EMT system and the CustusX navigation platform.
• Application of the framework in a preclinical study involving targeted liver ablation in an animal model using electromagnetically tracked needles.

Main Results:

• The developed framework was successfully tested with the Anser EMT platform for liver tumor targeting.
• Commercial electromagnetically tracked needles and ablation systems were utilized in the preclinical liver ablation procedure.
• Post-procedure necropsy confirmed that ablations were performed within 5 mm of the target tumors.

Conclusions:

• An open-source framework for electromagnetic tracking has been presented and validated in a preclinical setting.
• The framework provides a structure for future advancements in EMT systems and customized instrument design.
• This work facilitates broader innovation and adoption of improved EMT technologies in image-guided interventions.