While directional deep brain stimulation (DBS) shows promising clinical effects by providing a new degree of freedom in programming, precise knowledge of the lead position and orientation is necessary to mitigate the resulting increased complexity. Two methods for orientation assessment based on postoperative CT imaging have become available, but neither of them is currently able to resolve the respective 180° artifact symmetry. Both rely on information about the intended orientation and assume that a deviation of more than ± 90° is very unlikely. Our aim was to develop an enhanced algorithm capable of detecting asymmetries in the CT data and to thus eliminate the need for user interaction. Two different approaches are presented: one based on the lead marker’s center of mass (COM) and one based on asymmetric sampling of the marker’s intensity profile (ASM). Both were tested on a total of 98 scans of 2 lead phantoms, resulting in 165 measurements with a large variety of lead implantation and orientation angles. The 180° ambiguity was correctly resolved in 99.4% of cases by COM and in 96.4% of cases by ASM. These results demonstrate the substantial and currently unused asymmetry in CT and the potential for a truly automated workflow.
Automatic anatomical segmentation of patients’ anatomical structures and modeling of the volume of tissue activated (VTA) can potentially facilitate trajectory planning and post-operative programming in deep brain stimulation (DBS). We demonstrate an approach to evaluate the accuracy of such software for the ventral intermediate nucleus (VIM) using directional leads. In an essential tremor patient with asymmetrical brain anatomy, lead placement was adjusted according to the suggested segmentation made by the software (Brainlab). Postoperatively, we used directionality to assess lead placement using side effect testing (internal capsule and sensory thalamus). Clinical effects were then compared to the patient-specific visualization and VTA simulation in the GUIDE™ XT software (Boston Scientific). The patient’s asymmetrical anatomy was correctly recognized by the software and matched the clinical results. VTA models matched best for dysarthria (6 out of 6 cases) and sensory hand side effects (5/6), but least for facial side effects (1/6). Best concordance was observed for the modeled current anterior and back spread of the VTA, worst for the current side spread. Automatic anatomical segmentation and VTA models can be valuable tools for DBS planning and programming. Directional DBS leads allow detailed postoperative assessment of the concordance of such image-based simulation and visualization with clinical effects.
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