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3-Dimensional Virtual Reality Modelling With Intravascular Indocyanine Green Fluorescence Mapping for Targeted Pulmonary Segmental Resection Trial

3-Dimensional Virtual Reality Modelling With Intravascular Indocyanine Green Fluorescence Mapping for Targeted Pulmonary Segmental Resection Trial

Status
Not yet recruiting
Phases
Phase 1Phase 2
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06638125
Enrollment
89
Registered
2024-10-15
Start date
2026-12-01
Completion date
2028-12-31
Last updated
2026-02-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Non Small Cell Lung Cancer

Keywords

3-Dimensional Virtual Reality Modelling, Intravascular Indocyanine Green Fluorescence Mapping, Pulmonary Segmental Resection

Brief summary

With the advent of CT screening for lung cancer, an increasing number of NSCLCs are being detected at very early stages, and the demand for pulmonary segmentectomy is rising rapidly. As such, there is a need to develop new surgical techniques to facilitate minimally invasive pulmonary segmentectomy, as segmentectomy may provide a number of significant advantages over lobectomy for patients presenting with early-stage lung cancer, or for patients unable to undergo a full lobectomy due to existing comorbidities. This study will provide the first case series using preoperative 3D virtual reality (VR) anatomical planning (Elucis) added to ICG and NIF-guided robotic segmentectomy to date and will be the first reported use of Elucis-guided targeted pulmonary segmental resection in Canada. As lung cancer is the most frequently fatal cancer in North America, many thousands of patients will be able to benefit from this operation every year. If successful, this project will establish a novel operation that has the potential of increasing the rates of success for segmental resection. This will allow for further research that will externally validate this technique and ensure that it is reproducible in other centres by other surgeons. As segmental resection is the new standard of care for surgical management of early-stage NSCLC, and because lung cancer is the most frequently fatal cancer in North America, many thousands of patients will be able to benefit from this operation every year. Equally importantly, the investigators believe that this method will enable them to develop a new way of teaching lung resections, in a manner that is more effective for learners. Further research on the role of VR in teaching lung cancer surgery will very likely be a downstream effect of developing this surgical method.

Detailed description

Segmental resection is the new standard of care for early-stage non-small cell lung cancer (NSCLC). However, minimally invasive segmental resection is very difficult to perform, due to high inconsistency and variation in segmental anatomy, and the lack of clearly visible tissue planes between segments (intersegmental planes). The investigators have demonstrated that the rate of successful completion of a segmental resection is only 60%. As such, segmental resections are unlikely to become widely adopted by surgeons outside of centres of high volume expertise, unless an adjunct to facilitate and improve the success rate of this operation is developed. In this trial, the investigators propose to use 3-dimensional (3D) virtual reality (VR) modelling to plan, simulate, and execute segmental resections. The investigators believe that this adjunct will improve the rate of successful completion of this operation. This submission proposes a novel operation for segmental resections of the lung. Segmental resections are extremely difficult to perform because of the high rate of anatomical variations in segmental anatomy, and the lack of visible tissue planes between segments. In the largest prospective series on segmental resection, the investigators demonstrated that the rate of completion was only 60%. The investigators therefore conducted a subsequent trial utilizing 3D preoperative anatomical planning (Synapse 3D) in conjunction with intraoperative NIF-mapping using intravascular ICG in order to increase the rate of successful completion of a segmental resection. However, planned interim analyses has shown that there is no difference in the rate of successful completion of a segmental resection using Synapse 3D or NIF. This is likely the case because the investigators are using 2D models to plan a 3D operation. In this submission, the investigators hypothesize that adding 3D VR preoperative anatomical planning (Elucis) to NIF-guided segmental resection can greatly increase the rate of success of segmental resections. In this Phase I trial, the investigators propose to describe the technical details of this novel operation, and to evaluate it for safety, feasibility, and learning curve. If successful, this would be the first trial to do so, and would allow for further Phase II and III comparative trials to evaluate this operation.

Interventions

DEVICE3-Dimensional VR Modelling (Elucis) with Intravascular Indocyanine Green Fluorescence Mapping

All patients in Phase I and those randomized to Intervention in Phase II will have preoperative 3D VR reconstructions of their pulmonary anatomy with the target lesion created using the Elucis platform. Segment identification and confidence rating will be collected before and after visualizing the 3D VR reconstruction. Intraoperatively, the surgeon will use this 3D VR model as a guide to determine which inflow and outflow vessels to the involved segment need to be removed. After vascular ligation, a 8mL bolus of ICG solution will be injected into a peripheral vein catheter by anesthesia. The surgeon will mark out the segmental plane based on the fluorescence pattern seen on the infrared mode of the robotic camera. The surgeon will then perform the pulmonary resection and the resected non-fluorescent lung segment will be extracted from the body cavity. Study patients will receive routine postoperative care as non-study patients and will be followed until the 3-4-week mark.

DEVICE3-Dimensional Modelling (Synapse 3D) with Intravascular Indocyanine Green Fluorescence Mapping

The patients that are randomized to Control in Phase II will undergo the same intervention as above, but instead of using Elucis for 3D VR reconstructions, Synapse 3D will be used for 3D reconstructions.

Sponsors

St. Joseph's Healthcare Hamilton
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE

Intervention model description

Phase I is a single centre, prospective, clinical trial evaluating the safety, feasibility, and learning curve of adding 3D VR anatomical reconstructions and real-time intraoperative mapping using the Elucis platform to NIF-guided targeted segmental resection. Phase II is a single centre, prospective, randomized controlled trial evaluating if this novel operation (Intervention) can increase the rate of successful completion of a segmental resection when compared to Synapse 3D with intraoperative NIF-mapping using intravascular ICG (Control). Patients who are scheduled to undergo robotic pulmonary segmental resection at St. Joseph's Healthcare Hamilton will qualify for inclusion in the study. Exclusion criteria will be patients with tumors \> 3 cm or those with clinical evidence of N1 or N2 disease on preoperative imaging.

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Age \>/= 18 years * Tumour size \< 3 cm * Clinical Stage 1 Non-Small Cell Lung Cancer (NSCLC) * CT-imaging confirming that the tumour is confined to one broncho-pulmonary segment, rendering the patient a candidate for segmental resection.

Exclusion criteria

* Hypersensitivity or allergy to ICG, sodium iodide, or iodine * Women who are currently pregnant or breastfeeding; or women of childbearing potential who are not currently taking adequate birth control.

Design outcomes

Primary

MeasureTime frameDescription
Phase I: Feasibility of the operationThrough study completion, an average of 2 yearsBased on the proportion of completed minimally invasive segmental resections. A rate of 60%, similar to the established current standard, will be considered adequate.
Phase I: Safety of the operation30-days from date of surgeryBased on rates of perioperative complications within 30-days of surgery, as defined by the Ottawa Thoracic Morbidity \& Mortality (TMNM) System.
Phase I: Surgeon's learning curveThrough study completion, an average of 2 yearsEvaluated using CUSUM analysis of operative time and successful segmentectomy completion rate over time.
Phase II: Rate of conversion to robotic lobectomy in each armThrough study completion, an average of 2 yearsEvaluated based on the proportion of minimally invasive segmental resections converted to robotic lobectomy in each arm.

Countries

Canada

Contacts

CONTACTYogita S Patel
patelys@mcmaster.ca905-522-1155
PRINCIPAL_INVESTIGATORWaël C Hanna, MDCM, MBA, FRCSC

St. Joseph's Healthcare Hamilton / McMaster University

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026