3D Position Tracking Using On-Chip Magnetic Sensing in Image-Guided Navigation Bronchoscopy.

Area of Science:

• Biomedical Engineering
• Microsystems and Nanotechnology
• Medical Imaging

Background:

• Image-guided surgery often relies on ionizing radiation like X-rays, posing risks to patients and staff.
• Existing tracking systems can be bulky, expensive, or lack the required precision for delicate surgical procedures.
• There is a need for compact, cost-effective, and accurate navigation tools in minimally invasive surgery.

Purpose of the Study:

• To develop and characterize a novel on-chip sensor and readout circuit for high-resolution instrument tracking.
• To evaluate the sensor's performance for both 5-degrees-of-freedom (DoF) and 6-DoF tracking applications.
• To demonstrate the potential of magnetic field-based tracking as an alternative to X-ray imaging in surgical navigation.

Main Methods:

• Designed and fabricated a miniaturized on-chip magnetic sensor using 65 nm CMOS technology, integrating essential components like an analog-front end and an analog-to-digital converter (ADC).
• Implemented a 5-DoF tracking system and a 6-DoF system using an external wire-wound sensor.
• Characterized system performance using benchtop measurements and validated accuracy in pre-clinical in-vivo porcine lung models.

Main Results:

• The microchip occupies a minimal area of 1.06 mm², the smallest reported for similar designs.
• Achieved high-resolution tracking: 5-DoF with 1.1 mm precision and 6-DoF with 0.8 mm position accuracy and 1.1° angular accuracy within a 15 cm³ volume at 20 Hz.
• Demonstrated successful real-time tracking in pre-clinical in-vivo settings with a worst-case registration accuracy of 5.8 mm.

Conclusions:

• The developed on-chip magnetic sensor provides a compact, low-cost, and high-precision solution for instrument tracking in image-guided surgery.
• The system offers a viable, non-ionizing alternative to X-ray-based navigation, enhancing safety in surgical procedures.
• The demonstrated in-vivo performance validates the sensor's potential for clinical translation in minimally invasive interventions.