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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.
Background and Rationale NSCLC with supraclavicular or cervical lymph node metastasis (N3 disease) was historically considered unresectable. With the advance of multimodal therapy, complete lymph node dissection in selected patients has been shown to improve locoregional control. However, the supraclavicular fossa - frequently described as 'Pandora's Box' - is anatomically narrow and dense, with metastatic nodes often abutting the subclavian vessels, internal jugular vein, phrenic nerve, and brachial plexus. Conventional surgery relies heavily on the surgeon's tactile experience and 2D mental reconstruction of preoperative CT, increasing the risk of inadvertent neurovascular injury and incomplete clearance of post-treatment fibrotic versus active disease.
Intervention This study integrates two complementary technologies. (1) Multimodal image fusion using Fujifilm Synapse 3D maps PET SUV hotspots representing biologically active tumor onto a high-resolution CT anatomical model, producing a patient-specific digital twin. The fused model is exported to a static 3D format (OBJ/STL) and imported into the OpVerse XR platform - an offline data-conversion workflow with no real-time API coupling between the two systems, ensuring system stability and software compatibility. (2) Preoperative XR planning: in the operating room after general anesthesia and head/neck positioning, the surgeon wears an XR head-mounted display (HoloLens) and performs surface registration using stable bony landmarks. The 'see-through' overlay enables the surgeon to identify subcutaneous tumor hotspots and superficial venous anatomy, and to mark the optimal skin incision and initial dissection trajectory before any cut is made. The XR headset is then removed; lymph node dissection proceeds using standard sterile technique. Therefore the device functions purely as a preoperative visual aid (Non-Significant Risk), without entry into the sterile operative field.
Lymph node dissection definition En bloc systematic resection of the fibrofatty tissue containing metastatic nodes within the defined cervical or supraclavicular region, to achieve oncologic clearance and provide adequate tissue for pathologic staging and next-generation sequencing.
Statistical analysis All analyses are performed using SPSS. Continuous variables (operative time, blood loss, lymph node count) are summarized as mean ± SD or median; categorical variables (complications, registration success) as frequency and percentage. Successful completion rate of the XR-assisted workflow is reported with 95% confidence intervals. As a single-arm feasibility trial, no formal hypothesis testing is planned.
Preliminary data The investigators have completed a prior pilot trial (REC 202502149RINB, 2025) of XR-assisted lung nodule localization in 20 patients undergoing thoracoscopic sublobar resection, achieving 6-7 mm mean target registration error and 19/20 successful localizations without major complications. Because the supraclavicular region is more rigidly tethered to the bony skeleton and less affected by respiratory motion, registration accuracy in the present study is expected to be ≤5 mm.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| XR-Assisted Surgical Planning | Experimental | 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| OpVerse XR Surgical Planning Platform with HoloLens HMD | Device | An offline workflow in which patient-specific PET/CT-fused 3D models built in Synapse 3D are exported to OBJ/STL format and rendered via the OpVerse platform on a HoloLens head-mounted display. The surgeon performs surface registration to bony landmarks of the neck and shoulder for preoperative incision planning. The device is removed prior to skin incision and is not used during the sterile dissection. |
| Measure | Description | Time Frame |
|---|---|---|
| Successful Completion of XR-Assisted Preoperative Surgical Planning Workflow | Proportion of participants in whom the complete XR-assisted preoperative planning workflow is successfully executed, defined as meeting ALL of the following technical criteria:
| Intraoperatively, prior to skin incision (Day 0) |
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of Procedure-Related Adverse Events | Proportion of participants experiencing Grade ≥2 (Clavien-Dindo classification) adverse events related to the surgical procedure, including phrenic nerve injury, brachial plexus injury, chyle leak, Horner syndrome, or major vascular injury. | From surgery through 30 days postoperatively |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Chih-Hsiang Chang | Contact | +886-2-2312-3456 | 53384 | changch1986@ntuh.gov.tw |
| Name | Affiliation | Role |
|---|---|---|
| Jin-Shing Chen | National Taiwan University Hospital | Principal Investigator |
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| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 21703862 | Background | Ueda 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. | |
| 24442678 | Background | Jensen 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. |
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Individual participant data will not be shared outside the investigator team during this feasibility study. De-identified aggregate results will be reported in peer-reviewed publications.
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|
| Cervical / Supraclavicular Lymph Node Dissection | Procedure | En bloc systematic resection of fibrofatty tissue and metastatic lymph nodes within the cervical or supraclavicular region, performed using standard open surgical technique after XR-assisted incision planning. |
|
| Surgeon-Assessed Adequacy of XR-Planned Surgical Incision (3-Point Categorical Scale) |
Adequacy of the XR-planned skin incision in exposing the targeted lymph nodes, assessed intraoperatively by the operating surgeon using a 3-point categorical scale:
The endpoint is reported as the proportion of cases (out of 10) in each grade. |
| Intraoperatively, at time of skin incision and during initial dissection (Day 0) |
| PET Hotspot Clearance Rate | Proportion of preoperatively identified PET-positive lymph nodes (SUV hotspots) that are completely resected, confirmed by review of the operative specimen against preoperative imaging. | At time of surgery |
| Target Registration Error (TRE) | Mean spatial offset (millimeters) between virtual model bony landmarks and corresponding patient anatomy after XR surface registration. | At time of surgery |
| Operative Time | Total time from skin incision to skin closure (minutes). | At time of surgery |
| Estimated Intraoperative Blood Loss | Volume of blood loss recorded during the procedure (milliliters). | At time of surgery |
| 17223351 | Background | Hu 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. |
| 36084694 | Background | Bakhuis 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. |
| 30248803 | Background | Sato 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. |
| 33347848 | Background | Sadeghi 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. |
| 40163682 | Background | Zheng 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. |
| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| D008207 | Lymphatic Metastasis |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D009362 | Neoplasm Metastasis |
| D009385 | Neoplastic Processes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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