Deep Brain Stimulation (DBS) has shown to be particularly effective in treating symptoms associated with movement disorders, such as Parkinson’s Disease. However, surgeons would need even better tools to identify the most effective spots to target in the brain and a more automated way of testing the implanted electrodes.
As part of his PhD project, funded through the AFR PhD scheme of the Luxembourg National Research Fund (FNR), computer scientist Dr Andreas Husch developed innovative image-based computational approaches that help improve DBS precision and are already being used by scientists and clinicians around the world. This work was carried out at the Centre Hospitalier de Luxembourg (CHL) and the Luxembourg Centre for Systems Biomedicine (LCSB) of the University of Luxembourg).
Deep brain stimulation (DBS) is an intervention based on implanting permanent electrodes into the human brain to alleviate the symptoms of various movement and neuropsychiatric disorders, such as tremors, dystonia and Parkinson’s disease. The first DBS experiments took place about 60 years ago with modern DBS treatments being around for some 30 year.
“A deep brain stimulator is a bit like a pacemaker for the heart: it’s normally placed in the chest area cable running to the brain under the skin. This is connected to the fully flexible electrode in the brain.”, Dr Andreas Husch explains. “. The electrode has multiple contacts, which are connected to the ‘pacemaker’. Over the operation the pacemaker has to be programmed in order to define which of the four contacts is stimulated, and how strongly. The stimulation can be adapted to the patient to get the best effect and ideally no side effects.”
Despite the experience of several decades with DBS, some aspects would benefit from further improvement. A key question in DBS research is how to precisely define the optimal stimulation targets for the treatment of different diseases – in this case, for Parkinson’s disease. Here computer scientists like Dr Andreas Husch, whose studies were focused on Software Engineering, Machine Learning and Imaging, can help.
From methods for flood prediction to computer aided deep brain stimulation
During his Bachelors (B.Sc.) at the University of Applied Sciences in Trier, Andreas started working on a project looking at flood prediction for the Moselle River. The link between flood prediction and DBS is not obvious, but Andreas explains a common thread:
“For example, in a river, you can measure the water gauge changing over time. In the brain, you can measure microelectric recordings from single neuron cells, which is a signal over time – so data-wise, it’s very similar. This means you can apply similar algorithms.”
During his Masters’, Andreas worked with Computer Science Prof. Peter Gemmar, who was involved in projects relating to DBS and flood prediction. Gemmar applied some algorithmic ideas from flood prediction to DBS in collaborative work with Prof Dr Frank Hertel, who is leading the National Neurosurgical Department of Luxemburg, at the Centre Hospitalier de Luxembourg (CHL) and expressed an urgent need to get computer scientists into the DBS operating room.
“I spent a lot of time observing surgeries, trying to understand the needs of the surgeons: what do they really need and how can we help with computer science,” Andreas explains.
Responding to a need for post-operative aids
“Originally, my project was meant to focus on improving the intra-operative phase, but during the project new developments in the field changed the focus to post-operative,” Andreas explains. The reason was new developments with electrodes for DBS use: traditionally, four contacts are implanted in the brain for DBS, however, now it is possible to have as many as eight with more complex shapes enabling a “steering” of the current in a certain direction.
“This makes the post-operative part much more complex, naturally, as you are working with more contacts and there is a significantly larger amount time required for programming the stimulator. This created an urgent need to come up with post-operative aid for surgeons,” Andreas explains.
This led Andreas to come up with the ‘PaCER’ algorithm, which is currently the most precise and only fully automatic algorithm published to recover post-operative electrode from CT data. The overall goal of the project was to create the means to allow objective and as far as possible automatic assessment and support of a personalised deep brain stimulation process. This contributes to a better understanding of the action of DBS in an individual subject and may enable improved therapy by providing personalised computational guidance of the physician.
To patent or open source?
With the PaCER software being open source, the scientific community can use it freely. Such as a research group at Charité Berlin in Germany ( LeadDBS group), who integrated it in their Lead DBS stimulation research software package and making it accessible to researchers around the globe.
Automated solution for surgeons
But Andreas wanted to go a step further by automating the surgeons’ routine even further.
“We teamed up with Mikkel Petersen from the University of Aarhus, Denmark, and tried to bring PaCER into an automatic pipeline. To help a doctor you need an estimate of the individual brain structure of the patient and provide him with a fully interactive 3D map of the brain – which is exactly what we did in the next project,” Andreas explains.
“With the new 3D tool the surgeons can see how well placed the contacts / electrodes are and how they can improve without having to test everything. While this is still a prototype, the idea is to show how it could be used clinically.” His collaborators in Denmark already ran a small independent clinical validation study, in which they were quickly able to apply the methods to their clinical data.
When asked whether PaCER could become the standard for post-operative DBS, Andreas explains that it could, but that it would still need some extensions, and company involvement to get a CE Mark, which is the regulatory statement that a method is approved to be applied to patients within the European Union.
Findings awarded for improvements for post-operative DBS phase
In September 2018, Andreas Husch was given an award for his PhD work by InSilico Trials and the VPH Institute, in particular for the improvements to the post-operative phase of DBS. Dr Husch was also recently invited to give a talk in Shanghai, which covered the key contributions of thesis. The talk was delivered together with Prof Dr Frank Hertel, Dr Husch’s PhD co-supervisor. A good example how interdisciplinary research made in Luxembourg is now ready for application around the world.
> Patients with movement disorders, such as Parkinson’s disease, tremor disorders (essential tremor and rare tremor diseases) or dystonia (adults or children) can present themselves for expert diagnosis and treatment at the Centre for Deep Brain Stimulation in Luxembourg.