Clinical trial · Interventional

XR-Assisted PET/CT Navigation for Cervical Lymph Node Dissection in Lung Cancer

Application of Extended Reality (XR)-Assisted PET/CT Fusion Navigation in Supraclavicular-to-Cervical Lymph Node Dissection for Lung Cancer

NCT07593872CI-TRIAL-00111833XR-NeckLNDnot yet recruitingN/AClinicalTrials.gov clinicaltrialsPublishedExplore in graph →

Summary

Brief summary (as posted)

This single-arm, prospective feasibility study evaluates an Extended Reality (XR) headset-based preoperative surgical planning workflow that fuses 18F-FDG PET metabolic hotspots with CT anatomy on the OpVerse platform, in patients with non-small cell lung cancer (NSCLC) and supraclavicular or cervical lymph node metastasis (N3 disease) requiring lymph node dissection. Ten participants will undergo standard preoperative contrast-enhanced CT and whole-body PET. Synapse 3D software is used to segment key anatomic structures (clavicle, sternocleidomastoid, internal jugular vein, subclavian vessels, brachial plexus) and to project PET SUV hotspots onto the high-resolution CT model, yielding a patient-specific digital twin of functional tumor boundaries and at-risk neurovascular structures. Immediately prior to skin incision, the operating surgeon dons an XR head-mounted display (HoloLens via OpVerse) and registers the digital twin to the patient's neck using stable bony landmarks (clavicular head, sternal notch, mastoid). The surgeon plans the optimal incision and initial dissection trajectory, avoiding superficial veins and projecting the location of deep PET-positive nodes. The XR device is then removed, and the planned cervical or supraclavicular lymph node dissection is performed using standard surgical technique without further intraoperative XR guidance. The primary endpoint is a composite of safety and feasibility: absence of Grade ≥2 (Clavien-Dindo) phrenic nerve, brachial plexus, chyle leak, Horner syndrome, or major vascular injury through 30 days postoperatively, together with successful XR registration and incision planning. Secondary endpoints include incision planning accuracy, PET hotspot clearance rate, target registration error, operative time, estimated blood loss, and lymph node yield.

Conditions

Conditions (3)

Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.

Condition (as posted)	Mapped entity	Match	Confidence
Lymph Node Metastasis	—	UNRESOLVED	—
Non-Small Cell Lung Cancer	Lung Non-Small Cell Carcinoma	ALIAS	0.90
Supraclavicular Lymph Node Metastasis	—	UNRESOLVED	—

Interventions

Interventions (2)

Intervention	Type	Mapped drug	Match
Cervical / Supraclavicular Lymph Node Dissection	Procedure	—	UNRESOLVED
OpVerse XR Surgical Planning Platform with HoloLens HMD	Device	—	UNRESOLVED

Design

Arms and outcomes

Arms (1)

type
EXPERIMENTAL
label
XR-Assisted Surgical Planning
description
Patients undergo XR-assisted preoperative incision planning using the OpVerse platform with HoloLens HMD, overlaying a PET/CT-fused 3D digital twin onto the patient's neck before skin incision. The XR device is then removed, and standard cervical/supraclavicular lymph node dissection is performed without intraoperative XR guidance.
interventionNames
1. Device: OpVerse XR Surgical Planning Platform with HoloLens HMD
2. Procedure: Cervical / Supraclavicular Lymph Node Dissection

Primary outcomes (1)

measure
Successful Completion of XR-Assisted Preoperative Surgical Planning Workflow
timeFrame
Intraoperatively, prior to skin incision (Day 0)
description
Proportion of participants in whom the complete XR-assisted preoperative planning workflow is successfully executed, defined as meeting ALL of the following technical criteria: 1. Successful import and rendering of the patient-specific PET/CT fused 3D digital twin (OBJ/STL format) on the OpVerse platform via the HoloLens head-mounted display. 2. Successful surface registration to the patient's bony landmarks (clavicular head, sternal notch, mastoid) with a Target Registration Error (TRE) of 5 mm or less. 3. Successful surgeon-performed marking of the optimal skin incision and initial dissection trajectory prior to skin incision. The endpoint is reported as the percentage of cases (out of 10) meeting all three criteria.

Eligibility

Eligibility (as posted)

Sex: All
Minimum age: 18 Years
Maximum age: 80 Years

Show eligibility criteria text

Inclusion Criteria:

* Age 18 to 80 years.
* Confirmed or highly suspected lung cancer with supraclavicular or cervical lymph node metastasis requiring lymph node dissection.
* Willing to undergo preoperative PET/CT imaging.
* Able to provide written informed consent.

Exclusion Criteria:

* Prior high-dose radiation therapy to the neck causing severe distortion of cervical anatomy.
* Inability to undergo imaging studies, or known allergy to iodinated contrast media.
* Vulnerable populations as defined by local IRB regulations (e.g., pregnant women, prisoners, individuals lacking decisional capacity).

References

Publications (7)

BACKGROUNDUeda K, Tanaka T, Hayashi M, Tanaka N, Li TS, Hamano K. What proportion of lung cancers can be operated by segmentectomy? A computed-tomography-based simulation. Eur J Cardiothorac Surg. 2012 Feb;41(2):341-5. doi: 10.1016/j.ejcts.2011.05.034. Epub 2011 Dec 12. PMID 21703862
BACKGROUNDJensen K, Ringsted C, Hansen HJ, Petersen RH, Konge L. Simulation-based training for thoracoscopic lobectomy: a randomized controlled trial: virtual-reality versus black-box simulation. Surg Endosc. 2014 Jun;28(6):1821-9. doi: 10.1007/s00464-013-3392-7. Epub 2014 Jan 18. PMID 24442678
BACKGROUNDHu Y, Malthaner RA. The feasibility of three-dimensional displays of the thorax for preoperative planning in the surgical treatment of lung cancer. Eur J Cardiothorac Surg. 2007 Mar;31(3):506-11. doi: 10.1016/j.ejcts.2006.11.054. Epub 2007 Jan 16. PMID 17223351
BACKGROUNDBakhuis W, Sadeghi AH, Moes I, Maat APWM, Siregar S, Bogers AJJC, Mahtab EAF. Essential Surgical Plan Modifications After Virtual Reality Planning in 50 Consecutive Segmentectomies. Ann Thorac Surg. 2023 May;115(5):1247-1255. doi: 10.1016/j.athoracsur.2022.08.037. Epub 2022 Sep 6. PMID 36084694
BACKGROUNDSato M, Kobayashi M, Kojima F, Tanaka F, Yanagiya M, Kosaka S, Fukai R, Nakajima J. Effect of virtual-assisted lung mapping in acquisition of surgical margins in sublobar lung resection. J Thorac Cardiovasc Surg. 2018 Oct;156(4):1691-1701.e5. doi: 10.1016/j.jtcvs.2018.05.122. Epub 2018 Jul 20. PMID 30248803
BACKGROUNDSadeghi AH, Mathari SE, Abjigitova D, Maat APWM, Taverne YJHJ, Bogers AJJC, Mahtab EAF. Current and Future Applications of Virtual, Augmented, and Mixed Reality in Cardiothoracic Surgery. Ann Thorac Surg. 2022 Feb;113(2):681-691. doi: 10.1016/j.athoracsur.2020.11.030. Epub 2020 Dec 19. PMID 33347848
BACKGROUNDZheng YA, Lee YC, Huang JY, Hsieh HY, Chen YS, Chiang XH, Han PH, Lin MW, Hsu HH, Hung YP, Chen JS. Enhancing three-dimensional anatomical understanding in complex thoracic surgery: a comparative study of OpVerse and Synapse 3D. Eur J Cardiothorac Surg. 2025 Mar 28;67(4):ezaf069. doi: 10.1093/ejcts/ezaf069.