Deformable Tissue Modelling and Augmented Reality Based Guidance for Head and Neck Tumor Re-Resection Task
Purpose
Head and neck cancers have one of the highest recurrence rates among solid malignancies, and recurrence is strongly correlated with overall survival. Reducing recurrence rates depends, in part, on the surgeon's ability to accurately re-resect areas of positive or close margins during surgery. Currently, margin status is communicated primarily through verbal descriptions between the surgeon and pathologist, which can be imprecise. This challenge is further compounded by the deformable nature of soft tissues, as once the specimen is resected, the shape and size of the specimen change, making it difficult to accurately map the specimen's margins back onto the surgical site. Emerging technologies -such as augmented reality (AR), 3D scanning, and advanced soft tissue modeling- offer promising solutions for improving surgical navigation and precision. Building on these advances, an AR-based surgical navigation system was developed specifically for head and neck tumor resections. The system uses a 3D scanner to generate virtual models of both the resected specimen and the patient's surgical site, as demonstrated in prior work. A soft tissue modeling algorithm is then applied to account for specimen shrinkage and deformation, enabling accurate tracking of positive tumor margins. This guidance information is visualized through an AR headset, which overlays the margin data directly onto the patient's surgical site, providing surgeons with real-time visual guidance during re-resection. In this study, the goal is to evaluate the benefits and usability of this novel navigation software, compared to the standard of care. By assessing surgeon performance and user experience in cadaveric tasks with and without the AR system to identify strengths, limitations, and opportunities for refinement of the system, ultimately advancing surgical precision and improving patient outcomes by reducing recurrence rates.
Conditions
- Physician
- Surgeon
- Resident Doctor
- Resident Surgeon
- Surgical
- Fellow
Eligibility
- Eligible Ages
- All ages
- Eligible Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- Post-graduate year 1, 2, 3, 4 and 5 (PGY2-5) resident physicians. (no age limit) 2. Surgical fellows. 3. Attending physicians. 4. Prior cadaver lab or surgical experience. 5. Any surgeon, regardless of training and experience, who has been involved in the surgeon-pathologist interaction during surgical resection for frozen section and margin clearance assessment.
Exclusion Criteria
- Non-physician surgery providers.
Study Design
- Phase
- Study Type
- Observational
- Observational Model
- Other
- Time Perspective
- Prospective
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
| Augmented Reality (AR) | Participants will be asked to localize simulated margins on tissue resection beds on a fresh-frozen cadaver head. Specimens of skin, buccal, or tongue tissue will be resected by the research team beforehand. Participants will be asked to place pins or stitches where the indicated targets are located. These positions will be recorded by the research team. Participants will first receive oral guidance only, corresponding to common descriptions between pathologists and surgeons. Participants will then reproduce the same task with AR guidance. In this case, the target will be displayed in the see-through AR headset. The target will be overlaid on the resection bed site and follow your head's movements. |
|
Recruiting Locations
Nashville, Tennessee 37232
Jie Ying Wu Assistant Professor of Computer Science, PhD
615-343-4996
JieYing.Wu@vanderbilt.edu
More Details
- Status
- Recruiting
- Sponsor
- Vanderbilt University Medical Center
Study Contact
Jie Ying Wu Assistant Professor of Computer Science, PhD615-343-4996
JieYing.Wu@vanderbilt.edu
Detailed Description
Augmented reality (AR) technology, combined with computer vision algorithms, offers significant potential to enhance surgical visualization by generating GPS-like spatial maps over the patient's anatomy. This study aims to evaluate the usability and impact of our AR surgical guidance system, delivered through Microsoft HoloLens 2 (or equivalent AR/VR goggles such as Magic Leap or Apple Vision Pro), among surgeons while they complete various surgical tasks on cadaveric specimens. Specifically, an assessment of how the AR system influences surgeon performance and user experience during tasks such as suturing and specimen relocation, performed both with and without AR assistance. Task accuracy (e.g., resection precision) will be measured and survey responses will be collected to assess the system's usability, ease of use, and comfort. Building on prior work where we validated the feasibility and accuracy of AR-guided surgical holograms, this study focuses on advancing the evaluation of the system's usability and impact on performance. The goal is to generate insights into the application of AR guidance in head and neck tumor resection, ultimately contributing to improved intraoperative surgical precision and patient outcomes.