Multimodal US-gamma imaging using collaborative robotics for cancer staging biopsies.

Area of Science:

• Medical Imaging
• Robotics
• Oncology

Background:

• Accurate staging of female breast cancer relies on assessing lymphatic system spread.
• Sentinel lymph node (SLN) biopsy is standard for early-stage cancer, but punch needle biopsy lacks combined anatomical and nuclear data.

Purpose of the Study:

• To present and evaluate a novel system integrating live collaborative robotic 2D gamma imaging with 2D ultrasound for enhanced SLN identification.
• To improve the accuracy and efficiency of SLN biopsy by providing multimodal visualization.

Main Methods:

• A robotic arm equipped with a gamma camera and tracking system was developed to work with a physician-operated ultrasound probe.
• The system provides live multimodal visualization by aligning the gamma camera with the ultrasound imaging plane.
• Validation involved evaluating registration errors in a phantom and qualitative/quantitative assessment by medical experts on agar-gelatine phantoms.

Main Results:

• The average point registration error for image overlay was [Formula: see text] mm.
• Procedure time decreased by 36%, with an 80% success rate for biopsies.
• User feedback was highly positive, noting the system's intuitiveness and similarity to standard ultrasound-guided procedures.

Conclusions:

• The developed system represents the first medical collaborative robotic imaging system for SLN biopsy.
• User feedback indicates strong potential for application in SLN punch needle biopsy.
• Further research is underway to assess clinical feasibility using more complex phantoms.