AUGUR-AI - Indocyanine Green Fluorescence Angiography Representer
Trial ID: NCT06708819
Status: NOT_YET_RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-01
Completion date: 2026-01
Sponsor: Mater Misericordiae University Hospital
Collaborators: Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico; Humanitas Research Hospital IRCCS, Rozzano-Milan; Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA); University Hospital, Geneva; The Leeds Teaching Hospitals NHS Trust; Oxford University Hospitals NHS Trust; Frimley Park Hospital NHS Trust; IRCCS San Raffaele; UZ Leuven; University College Dublin
Conditions: Colorectal Surgery; Colorectal Resection; Anastomosis, Surgical; Fluorescence Guided Surgery; Indocyanine Green; Perfusion Imaging; Anastomotic Leaks
Locations: Mater Misericordiae University Hospital
Countries: Ireland
Enrollment: 300
Age range: 18 Years - None
Sex: ALL

Summary:
Surgery can effectively treat colorectal cancer, but it is a complex procedure with risks and complications. Surgeons often rely on cameras to visually guide their instruments during operations, especially in minimally invasive ("keyhole") and endoscopic procedures. The camera is connected to a computer and generates the internal scene onto a display screen, which the surgeon looks at throughout the procedure, helping them make informed decisions throughout the operation. Fluorescence-guided surgery uses a particular type of camera that can detect images in both normal light and in the near-infrared range. To work, it needs the administration of an agent called indocyanine green to a patient and then the camera can see if the agent is in the tissue of interest to the operation at the time of the surgery. In this way, decisions regarding blood supply ("perfusion") can be helped, especially related to safety in joining together portions of tissue after removal of disease. The equipment and agent are approved for use in this way and have very good safety profiles. Many international studies have already demonstrated that the use of fluorescence-guided surgery is associated with lower rates of leaks when disease bowel segments are removed, and the healthy ends are joined back together.

Previous work we have done has shown that sophisticated computing methods can learn to interpret the fluorescence patterns to a similar standard as a surgeon who is very experienced in fluorescence-guided surgery.

In this study, we aim to assess whether the computer system we have developed work in real-time, in theatre to provide a reliable interpretation of the fluorescence pattern, that would match how an expert would interpret the same pattern. The system's analysis will not impact on the operation; instead, video images will be recorded, processed and analysed by our computer system. The results of the interpretation will not be shown to the operating surgeon during the procedure to avoid any impact on decision-making.

Eligibility criteria:
Inclusion Criteria:

* Participant is willing and able to give informed consent for participation in the study.
* Aged 18 years or above.
* Colorectal disease requiring segmental resection with anastomosis.
* Participant has clinically acceptable laboratory results, including liver function tests.
* In the Investigator's opinion, is able and willing to comply with all study requirements.
* Willing to allow his or her General Practitioner and consultant, if appropriate, to be notified of participation in the study.

Exclusion Criteria:

The participant may not enter the study if ANY of the following apply:

* Participant who is pregnant, lactating or planning pregnancy during the course of the study.
* Significant renal or hepatic impairment.
* Any other significant disease or disorder which, in the opinion of the Investigator, may either put the participants at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.
* Allergy to intravenous contrast agent or indocyanine green.
* Concurrent use of anticonvulsants, bisulphite containing drugs, methadone and nitrofurantoin.

Outcomes:
Accuracy of AI interpretation relative to intra-operative decision made by operating surgeon