Clinical trial NCT03953144: Synapse 3D With Intravascular Indocyanine Green
Official title: Synapse 3D With Intravascular Indocyanine Green Fluorescence Mapping for Targeted Pulmonary Segmental Resection Trial: A Phase I Safety and Feasibility Trial
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: PHASE1
PHASE2
Conditions: Non-small Cell Lung Cancer
Primary Neoplasm
Keywords: Segmentectomy
Lung Cancer
Robotic Surgery
3D Modelling
CT Imaging
Near-Infrared Fluorescence
IC-GREEN
Surgical Planning
Indocyanine Green
Early-Stage Lung Cancer
Surgical Mapping
Lung Preservation
Lead sponsor: St. Joseph's Healthcare Hamilton
Sponsor class: OTHER
First posted: 2019-05-16
Enrollment: 32
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: This study is a single centre, prospective clinical trial evaluating the safety and feasibility of adding 3D anatomical reconstructions and real-time intraoperative planning using Synapse 3D software added to NIF-guided targeted segmental resection. It is anticipated that 32 participants will be enrolled within a 1-year period. Enrollment will take place at St. Joseph's Healthcare Hamilton. All patients enrolled will be evaluated until their first scheduled follow-up appointment (within 30 days post-surgery).
Primary purpose: TREATMENT

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 anatomical planning (Synapse 3D) added to ICG and NIF-guided robotic segmentectomy to date and will be the first reported use of Synapse 3D-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.

Detailed description: Lungs are made up of individual lobes. When a lung cancer tumour is found in one of these lobes, the surgeon often performs a Lobectomy. A Lobectomy is the surgery most commonly done to treat early-stage lung cancer and requires removal of an entire lobe of the lung, which removes a large amount of lung tissue

For patients with small tumours saving as much healthy lung tissue as possible is important. Each lobe of the lung has smaller sections called segments. When a lung cancer is in one of these segments, it is possible to remove that segment, without removing the entire lobe. This surgery is called a Segmentectomy. Compared to a lobectomy, a segmentectomy saves a larger amount of healthy lung tissue. Research shows that a segmentectomy can result in less blood loss, shorter operation time, less days of having a chest tube, and a shorter hospital stay, compared to a lobectomy.

With the advances in screening technology for lung cancer tumours, an increasing amount of very small lung cancer tumours are being found, and the demand for segmentectomy is increasing. A segmentectomy is a hard surgery to perform robotically because it is difficult to view the tissue lines that separate each segment within the lobe. As a result, it is difficult for the surgeon to see exactly which pieces of tissue should be removed in order to safely complete the segmentectomy. Because of these challenges, many patients having robotic surgery will have a lobectomy, even if a full lobectomy is not needed.

In response to these challenges, our surgical group has developed the technique of using Near-Infrared Fluorescence (NIF) mapping with intravascular indocyanine green (ICG) dye injection. With the aid of an infrared camera the surgeon is able to see the segment within a lobe of lung after injection of the ICG dye, allowing for a more accurate segmentectomy. We recently reported a 60% success rate of segmental resections with the use of ICG and NIF-guided surgical resection. However, a limitation to this technique is that the segmental anatomy can only be seen during the operation and only after cutting the blood vessels.

The introduction of 3D reconstruction and virtual modeling provides a new way to locate lesions accurately within a segment and plan the appropriate operation before the actual surgery occurs. Synapse 3D (Mississauga, Canada) is a 3D modelling technology that is capable of producing a detailed 3D virtual model of a patient's lung based on Computed Tomography (CT) scans. It has been shown to be safe and feasible in performing segmental pulmonary resections on a robotic platform. In this study, we propose a new operation that uses 3D anatomical planning before the surgery (Synapse 3D) and real-time NIF-mapping at the time of surgery using ICG dye, which we believe will greatly increase the likelihood of a successful segmentectomy. If this new operation is successful, it will help patients save more of their healthy lung tissue when they are undergoing surgery for lung cancer.

Eligibility criteria: Inclusion Criteria:

* 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.
* Patients with clinical evidence of N1 or N2 disease on preoperative imaging
* Pulmonary Function tests demonstrating Forced Expiratory Volume in 1s (FEV1) or diffusion capacity of the lung for carbon monoxide (DLCO) less than or equal to 30% of predicted.

Primary outcomes:
measure: Segmental Resection Conversion Rate
timeFrame: 1 year
measure: Number of Participants with Post Operative Complications
timeFrame: 1 year
Secondary outcomes:
measure: Anatomical Accuracy of the 3D Lung Model
timeFrame: 1 year
measure: Surgeon Confidence
timeFrame: 1 year
measure: Operation Time
timeFrame: 1 year
measure: Conversion to Thoracotomy
timeFrame: 1 year
measure: Chest Tube Duration
timeFrame: 1 year
measure: Length of Stay
timeFrame: 1 year
measure: Estimated Blood Loss
timeFrame: 1 year
Other outcomes:
Locations:
city: Hamilton
country: Canada
facility: St. Josephs Healthcare Hamilton
state: Ontario
Study officials:
affiliation: St. Joseph's Healthcare Hamilton / McMaster University
name: Waël C Hanna, MDCM, MBA, FRCSC
role: PRINCIPAL_INVESTIGATOR
References:
citation: Landreneau RJ, Sugarbaker DJ, Mack MJ, Hazelrigg SR, Luketich JD, Fetterman L, Liptay MJ, Bartley S, Boley TM, Keenan RJ, Ferson PF, Weyant RJ, Naunheim KS. Wedge resection versus lobectomy for stage I (T1 N0 M0) non-small-cell lung cancer. J Thorac Cardiovasc Surg. 1997 Apr;113(4):691-8; discussion 698-700. doi: 10.1016/S0022-5223(97)70226-5.
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citation: Fukuhara K, Akashi A, Nakane S, Tomita E. Preoperative assessment of the pulmonary artery by three-dimensional computed tomography before video-assisted thoracic surgery lobectomy. Eur J Cardiothorac Surg. 2008 Oct;34(4):875-7. doi: 10.1016/j.ejcts.2008.07.014. Epub 2008 Aug 15.
citation: Baste JM, Soldea V, Lachkar S, Rinieri P, Sarsam M, Bottet B, Peillon C. Development of a precision multimodal surgical navigation system for lung robotic segmentectomy. J Thorac Dis. 2018 Apr;10(Suppl 10):S1195-S1204. doi: 10.21037/jtd.2018.01.32.
citation: Ivanovic J, Al-Hussaini A, Al-Shehab D, Threader J, Villeneuve PJ, Ramsay T, Maziak DE, Gilbert S, Shamji FM, Sundaresan RS, Seely AJ. Evaluating the reliability and reproducibility of the Ottawa Thoracic Morbidity and Mortality classification system. Ann Thorac Surg. 2011 Feb;91(2):387-93. doi: 10.1016/j.athoracsur.2010.10.035.
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