Image Guided Surgery
Successful surgery depends on having the best possible information at the right moment. Our research combines advanced imaging, artificial intelligence, and optical technologies to improve surgical decision-making, enhance education, and increase the precision of lung cancer surgery.
5-ALA Fluorescence Imaging and Optical Therapeutics
Cancer cells naturally accumulate protoporphyrin IX (PpIX) after administration of 5-aminolevulinic acid (5-ALA), causing tumors to glow bright red under blue light.
Our research explores two powerful applications of this technology:
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Fluorescence-guided surgery, allowing surgeons to better identify tumors while preserving healthy tissue.
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Photodynamic therapy, using light activation to selectively destroy early-stage lung cancers and precancerous lesions.
Together, these approaches improve both cancer detection and treatment through minimally invasive optical technologies.
Why it matters: Making tumors easier to see helps surgeons remove them more completely while protecting healthy lung tissue.
Improving Surgical Margins
Removing every cancer cell is one of the most important goals of lung cancer surgery. Our team is developing CT-based approaches that provide surgeons with more timely and reliable assessment of surgical margins during an operation.
Why it matters: More accurate margin assessment may reduce the risk of cancer recurrence and improve long-term outcomes.
Eye-Tracking Technology for Surgical Education
Eye tracking technology provides a unique window into how surgeons perceive anatomy and make decisions during complex procedures.
Our research explores two key applications of this technology:
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Real-time visual guidance, allowing instructors to highlight critical anatomy and areas of interest during surgical training.
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Objective assessment of surgical expertise, using eye movement patterns to measure technical proficiency and improve education.
Together, these approaches aim to advance thoracic surgery training through innovative, data-driven educational tools.
Why it matters: Understanding how expert surgeons see and navigate anatomy can improve training, accelerate skill development, and ultimately enhance patient care.
Intraoperative Guidance and Automated Image Analysis (AI)
Artificial intelligence is transforming how surgeons interpret anatomy during minimally invasive procedures. Our laboratory is developing AI-powered tools that automatically recognize anatomical structures and identify critical areas during thoracic surgery.
Our research focuses on two key applications:
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Automated anatomical segmentation, helping surgeons identify important structures in real time.
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AI-guided surgical navigation, including our Go/No-Go Zone model, which highlights areas that should be avoided to reduce the risk of injury during robotic surgery.
Together, these technologies support safer, more precise surgery by providing intelligent, real-time guidance in the operating room.
Why it matters: Better visualization and decision support can improve surgical precision, reduce complications, and enhance patient safety.