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Deformable Tissue Modelling and Augmented Reality Based Guidance for Head and Neck Tumor Re-Resection Task (SPeAR)

5. august 2026 opdateret af: Michael Topf, Vanderbilt University Medical Center

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.

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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 the investigators 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.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

30

Fase

  • Tidlig fase 1

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

  • Navn: Jie Ying Wu Assistant Professor of Computer Science, PhD
  • Telefonnummer: 615-343-4996
  • E-mail: JieYing.Wu@vanderbilt.edu

Studiesteder

    • Tennessee
      • Nashville, Tennessee, Forenede Stater, 37232
        • Rekruttering
        • Vanderbilt University Medical Center
        • Kontakt:

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Barn
  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Studiebefolkning

Surgeon-physician, surgical fellow, or post-graduate year 1, 2, 3, 4 and 5 (PGY2-5) resident physicians

Beskrivelse

Inclusion Criteria:

  1. 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:

1. Non-physician surgery providers.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Enhedens gennemførlighed
  • Tildeling: N/A
  • Interventionel model: Enkelt gruppeopgave
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Andet: 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.

Task accuracy will be evaluated by measuring distances between the points identified with and without AR guidance, and the pathologist-intended target locations.

Participants will then complete post-tasks surveys and interviews.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Performance Task accuracy (e.g., resection precision)
Tidsramme: within 90 minutes of AR-guided use
Surgeon performance of target re-localization compared with and without the AR-headset.
within 90 minutes of AR-guided use
User Experience
Tidsramme: immediately after the AR-guided task.
Assess AR usability, ease of use, and comfort, through surgeon feedback surveys
immediately after the AR-guided task.
Accuracy of overlay alignment
Tidsramme: within 90 minutes of completing the AR-guided task.
This will validate the accuracy of overlay alignment through landmark-based (tumor margin relocation) error metrics, which support precision of re-resection tasks.
within 90 minutes of completing the AR-guided task.

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Samarbejdspartnere

Efterforskere

  • Ledende efterforsker: Michael Topf, MD, Vanderbilt University Medical Center

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

18. februar 2026

Primær færdiggørelse (Anslået)

1. juni 2029

Studieafslutning (Anslået)

1. juni 2029

Datoer for studieregistrering

Først indsendt

30. juni 2026

Først indsendt, der opfyldte QC-kriterier

30. juni 2026

Først opslået (Faktiske)

7. juli 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

10. august 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

5. august 2026

Sidst verificeret

1. juni 2026

Mere information

Begreber relateret til denne undersøgelse

Andre undersøgelses-id-numre

  • 251090

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

UBESLUTET

IPD-planbeskrivelse

NIH requires through Data Management and Sharing Plans (DMSP) that all data collected during the research project be archived indefinitely and shared with the community after the project termination. De-identified data will then be transferred to Open Science Framework (OSF).

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