Spots Global Cancer Trial Database for Synapse 3D With Intravascular Indocyanine Green

Study Description

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.

Keywords

Eligibility

Minimum Age: 18 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Contact Details

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