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

5. august 2026 oppdatert av: 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.

Studieoversikt

Status

Rekruttering

Forhold

Intervensjon / Behandling

Detaljert 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.

Studietype

Intervensjonell

Registrering (Antatt)

30

Fase

  • Tidlig fase 1

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

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

Studiesteder

  • Forente stater
    • Tennessee
      • Nashville, Tennessee, Forente stater, 37232
        • Rekruttering
        • Vanderbilt University Medical Center
        • Ta kontakt med:

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Barn
  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

Studiepopulasjon

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

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Primært formål: Enhetens gjennomførbarhet
  • Tildeling: N/A
  • Intervensjonsmodell: Enkeltgruppeoppdrag
  • Masking: Ingen (Open Label)

Våpen og intervensjoner

Deltakergruppe / Arm
Intervensjon / Behandling
Annen: 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.
Annen: Augmented Reality

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.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
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.

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Sponsor

Vanderbilt University Medical Center

Samarbeidspartnere

Vanderbilt University

Etterforskere

  • Hovedetterforsker: Michael Topf, MD, Vanderbilt University Medical Center

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart (Faktiske)

18. februar 2026

Primær fullføring (Antatt)

1. juni 2029

Studiet fullført (Antatt)

1. juni 2029

Datoer for studieregistrering

Først innsendt

30. juni 2026

Først innsendt som oppfylte QC-kriteriene

30. juni 2026

Først lagt ut (Faktiske)

7. juli 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

10. august 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

5. august 2026

Sist bekreftet

1. juni 2026

Mer informasjon

Begreper knyttet til denne studien

Nøkkelord

Andre studie-ID-numre

  • 251090

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

UBESLUTTE

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).

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

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