Virtual 3D modeling for improved surgical planning
Research type
Research Study
Full title
Virtual 3D modelling for improved surgical planning of robotic-assisted partial nephrectomy.
IRAS ID
295968
Contact name
Reza Rezavi
Contact email
Sponsor organisation
King’s College London
Clinicaltrials.gov Identifier
Duration of Study in the UK
3 years, 0 months, 0 days
Research summary
Robotic-assisted surgery is a rapidly developing field with robots in 70+ UK surgical centres. However, how a surgeon plans for an operation has not changed for 30 years. They still have to interpret hundreds of 2D images from medical scans, like CT (Computed Tomography (scanning by x-rays)) and MRI (Magnetic Resonance Imaging (scanning by high-powered magnets)), to perceive the patient’s 3D anatomy. In complex surgeries, poor understanding of the patient's anatomy can lead to preventable complications causing: NHS £380M p.a. costs; surgery cancellations; long hospital stays for patients; avoidable blood transfusions and follow-up procedures; and ultimately threatening patient lives.
We have developed CE-marked-software, called Innersight3D, that generates interactive virtual 3D models of the patient anatomy to provide a detailed roadmap for the surgeon to devise the optimal treatment and surgical plan, and help them to explain the surgical risks to patients. The model generation relies on the extraction of the patient’s anatomical structures such as bones, organs and vessels from standard-of-care CT scans, allowing the surgeon to view the patient anatomy in 3D prior to the operation, with the aim of enhancing their understanding of their patient’s unique anatomy, and minimising the chances of a surgical complication.
We plan to integrate our software with existing hospital IT systems and gather evidence on the product’s effectiveness in actual clinical practice. The study will compare current planning method to planning with the addition of virtual 3D models. The study will recruit 328 patients scheduled for kidney-sparing surgery from 5 NHS Trusts and will last 3 years. In addition, we will determine whether surgical navigation is easier and therefore quicker and results in fewer complications, benefiting patients by reducing hospital stay and time spent under anesthesia. The financial benefit to the NHS and how to best roll out the product nationally will also be explored.
REC name
Wales REC 1
REC reference
22/WA/0039
Date of REC Opinion
29 Mar 2022
REC opinion
Further Information Favourable Opinion