Feb Virtual Implantation of the Neural Interface in the Nerve Model, Integration of Fibrotic Tissue Layers, Discretization

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Description: Virtual implantation of the neural interface in the nerve model, integration of fibrotic tissue layers, discretization.

Deliverable: Studies on o²S²PARC

Acceptance criteria: Multiple nerve models with implanted neural interfaces and fibrotic tissue layers on o²S²PARC.

Out of scope: -

Deadline: Q2

wrike Y7-MS 11.2.1.3: Virtual Implantation of the Neural Interface in the Nerve Model, Integration of Fibrotic Tissue Layers, Discretization

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Y7Q2 Status update (29/02/2024): Delayed Implementation: Virtual implantation of a neural interface model was demonstrated at the monthly update meeting on 02/07/2024 and 02/28/2024. An image-based modeling pipeline was established that uses the NECTAR module from COSMIIC-Nest4 . The electrode geometries of monopolar and bipolar electrodes have been provided by Tina Vrabec and parameterized. As a result, we were able to compare the recruitment curves between bipolar and monopolar electrode designs (a homogeneous 7.5 µm MRG motor fiber population was used). The results suggest that for small currents, the two electrodes recruit similar fascicles (the superficial ones closest to the contacts). But with increasing current magnitudes, recruitment characteristics differ strongly.

Integration of a fibrotic tissue layer has not yet been realized; hence this milestone is only partially completed and delayed.

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Y7Q3 Status update (06/13/2024): Completed

Implementation: The only missing functionality in Q2 concerned insertion of fibrotic tissue layers in the model, which has now been completed. In addition, the previously established neural interface insertion functionality was also considerably strengthened in Q3. Scripts were developed: (i) to create simplified electrode geometries (which still encompasses many commercially available bipolar cuff electrodes) and apply them to image-based nerve models; (ii) to import complex 3D electrode geometries provided as CAD files and apply them in a user-defined positions along the nerve. For the former (i), simplified and parameterized electrode geometries can be created using combinations of 2D and 3D constructive geometry operations, or by directly leveraging cross-sectional geometry information from the segmented 2D nerve image. The scripts, which also handle discretization, are fully parameterized and automatized to allow for application of the meta-modeling framework. The scripts were extended to allow the integration of parameterized scar tissue layers within acute models of multi-contact electrodes applied to complex multifascicular nerves. The scar tissue is created around the electrode by extruding the electrode-tissue interface patch for a parameterizable thickness, directly adapting the unstructured mesh created from the model geometry (nerve, electrode and surrounding tissue). Users can specify which tissues should not be altered by the insertion of the scar tissue. This newly established scar tissue creation functionality facilitates the modeling of chronic neurostimulation scenarios without requiring complex de novo remeshing. Users can study the impact of scar tissue formation by varying the assigned dielectric tissue parameter and/or scar tissue thickness.