NCT03955614: inOr

Intelligent Operating Room

Status unknown NA Last updated 11 April 2022

What this trial tests

NA trial testing pedal-controlled GoSurgeryTM in Surgery in 150 participants. Status unknown.

Timeline

4 October 2019

Primary endpoint
1 October 2022

1 October 2022

Quick facts

Lead sponsor	Imperial College London
Phase	NA
Status	Status unknown
Study type	INTERVENTIONAL
Allocation	non randomized
Design	sequential
Masking	none
Primary purpose	health services research
Enrollment	150
Start date	4 October 2019
Primary completion	1 October 2022
Estimated completion	1 October 2022
Sites	1 location across United Kingdom

Drugs / interventions tested

• pedal-controlled GoSurgeryTM
• ML-controlled GoSurgeryTM
• NoGo

Conditions studied

• Surgery — all drugs for Surgery →

Sponsor

Imperial College London

Who can join

18 and older, any sex, with Surgery. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The widely varied practice of surgery, alongside rapidly expanding specialised knowledge and evolving technology as well as the fast turnover of operating theatre staff means they often face unfamiliar operations, techniques and equipment. To the investigator's knowledge, there is no formal induction for the work undertaken specifically within the operating theatre.

Many studies have shown that standardised practices, formal training and mental rehearsal improve surgical performance.

In this context, Artificial Intelligence (AI) is expected to have vast applications in surgery, particularly through standardisation, clinical decision and training support as well as patient-centred care optimisation.

Digital SurgeryTM developed GoSurgeryTM software to consolidate induction processes, support training and achieve standardised surgical practices, ultimately improving surgical performances and patient outcomes.

GoSurgeryTM allows surgeons to prepare step-by-step standardised workflows of procedures, including equipment, tips and warnings.

In preparation for surgery, workflows can used by operating team staff as a form of induction and mental rehearsal. During the surgery, using pedal-controlled tablets, relevant information for each step of the procedure is presented. GoSurgeryTM has developed AI computer vision to recognise the steps and automatically present the workflows without user-intervention.

After the surgery, the AI will allow surgeons to review their performances uploaded onto a personal virtual Hub and compare timing of steps to their previous repository of cases, as well as giving them the ability to share any interesting or difficult cases, supporting learning opportunities and monitoring of progression.

This feasibility study sets the bases to test the ability of GoSurgeryTM to improve induction processes, team performance, surgical training and patient outcomes.

The research will compare preparedness and performance of operating staff with/without the use of GoSurgeryTM, through questionnaires, observational team assessments, technical measures and patient outcomes.

Data will be collected at Imperial College Trust, Chelsea and Westminster Hospital and University College Hospital on patients undergoing general surgery. Anonymised images of keyhole surgery shall be analysed in collaboration with Digital SurgeryTM to develop the AI computer vision software.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Surgical data science - from concepts toward clinical translation.
   Maier-Hein L, Eisenmann M, Sarikaya D, März K, et al · · 2022 · cited 158× · PMID 34879287 · DOI 10.1016/j.media.2021.102306