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Model based computer assisted surgery for Deep Brain Stimulation



  • 2014 Best Paper Award at the International Conference of Computer Assisted Radiology and Surgery in Fukuoka (Japan)
  • The ANR ACouStiC project was awarded with the 2013 Grand Prix des trophées “Loading the Future”

General purpose

High frequency and continuous electrical stimulation of deep brain structures (DBS) has been demonstrated as an efficient minimally invasive surgical treatment for treating motor related diseases and recently severe neuropsychological diseases. The quality of the clinical improvement, as well as the existence of motor, neuropsychological or psychiatric side effects strongly depend on the location of the electrodes. To improve targeting and post operative evaluation for better outcome and reduced side effects, we studied and implemented an approach based on numeric and symbolic models for helping decision making process in deep brain stimulation surgery, in the context of the ANR project ACouStiC (PI: P. Jannin).



We first developed a software environment allowing to fully automatically, i.e. without user interaction, compute a pre-operative patient specific model from his/her multimodal medical images and from anatomical atlases (allowing segmentation of anatomical targets not visible in the medical images) (Figure 1). This software also includes visualisation and interaction modules with few interaction and increase of automation to ease planning phase. The software was installed at two surgical centers for pre-clinical evaluation and is protected by APP. In order to improve decision making, we introduced the concept of anatomo-clinical atlases, which consists of analysing retrospective data of previously implanted DBS patients. In opposition to classical works using anatomical and electro-physiological data [39,41,42,43,44], we studied the correlation between stimulated areas and clinical scores. By non-linear registration of images to compensate anatomical differences between individuals (Figure 2), we were able to compute 3D atlases highlighting areas with best clinical results according to different clinical scores. We introduced the concept of such atlas for outcome prediction. This work resulted into two patent submissions (in review). The first clinical evaluations seem to show better outcome and decrease of operating time, resulting in fewer infections.

See also the ACouStiC web site: ANR Blanc grant for 4 years starting in 2011 - PI: P. Jannin

  • Valorisation: Two submitted patents and 2 APP protected software (pyDBS and Park MedAtlis)

Main Collaborators


inserm rennes1 ltsi