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Trial at NHNN to test effectiveness of robot guiding electrode placement during neurosurgery

9 February 2018

We are delighted to announce that a randomised clinical trial for EpiNav™ has begun at the National Hospital for Neurosurgery and Neurology (NHNN).

Epinav

The trial will test the effectiveness of a robot micro-guided system which is used to help guide intracranial electrode placement during diagnostic brain surgery for epilepsy patients.

The EpiNav™ project is an interactive neuro-navigation system to assist in planning and guiding surgical interventions for patients with epilepsy. It is a collaborative effort between researchers from the Institute of Healthcare Engineering (led by WEISS), the UCL Institute of Neurology, and the NHNN. The work is led by principal investigators Prof John Duncan and Prof Sebastien Ourselin, engineering lead Rachel Sparks, the neurosurgical consultants Mr Andrew McEvoy and Ms Anna Miserocchi, and senior clinical researcher Vejay Vakharia. 

Epilepsy is a condition that affects the brain and causes repeated seizures, affecting about half a million people in the UK. About 30-40% of individuals with epilepsy continue to experience seizures despite medication. In some individuals neurosurgical resection can be curative, if the part of the brain responsible for seizure onset can be identified. 

The part to be removed is identified by first implanting stereo-electroencephalography (SEEG) depth electrodes into the brain to find out whereabouts the abnormal electrical brain signals that cause seizures are being generated from. This part can then be removed in a second operation provided that surgery would not cause a new difficulty, such as loss of speech or limb movement. 

EpiNav™ helps avoid these risks by using software programming to create multi-modal 3D maps of patient’s brain structures. These can then be used to plan for surgery and assist neurosurgeons in navigating the brain, like a kind of ‘3–dimensional satnav’. By combining a variety of the latest imaging methods, the software is able to visualise the entire brain and can quickly and safely plan precise routes for the electrodes, with trajectories that avoid blood vessels and critical brain areas.

surgeon
 

This careful planning of electrode placement is further aided by assisted tools during the surgery itself, which reassess planned trajectories using an automated entry point search and risk evaluation. After initial success and with the help of an additional £1.75m funding from the Wellcome Trust and the Department of Health, the software has been advanced further to interact with Medtronic robotic guidance that will be able to operate with minimum human interaction during surgery. This work is a key aspect of the UCLH/UCL Biomedical Research Centre Neuroscience programme, which contributes essential support to make this possible. 

Whilst the software planning tools have been of great assistance to neurosurgeons the placement of the electrodes is still performed manually and the need for ultra-precise insertion meant that each electrode could take up to 30 minutes to properly align. The robot currently being tested under the trial will interact with the surgical tools and the planning software to speed up the time it takes to reach the correct angle of insertion, reducing the insertion time of each electrode to a matter of minutes with a 0.5mm accuracy. 

It is hoped that these advances will enable more patients to benefit from the procedure by increasing the number of surgeries hospitals can perform and widening the number of patients eligible who would currently be assessed as high risk. There is also hope that future developments could extend this software to be applied far more widely, helping to assist other surgical interventions such as biopsies and tumour removals.

The randomised control trial will run at NHNN 12 October 2017 – 12 June 2019. Reference number: ISRCTN17209025. For further details, please contact Prof John Duncan, j.duncan@ucl.ac.uk or Dr Vejay Vakharia, v.vakharia@ucl.ac.uk.

Risk map of brain