Abstract
BackgroundGrowing interest exists for superolateral medial forebrain bundle (slMFB) deep brain stimulation (DBS) in psychiatric disorders. The surgical approach warrants tractographic rendition. Commercial stereotactic planning systems use deterministic tractography which suffers from inherent limitations, is dependent on manual interaction (ROI definition), and has to be regarded as subjective. We aimed to develop an objective but patient-specific tracking of the slMFB which at the same time allows the use of a commercial surgical planning system in the context of deep brain stimulation.MethodsThe HAMLET (Hierarchical Harmonic Filters for Learning Tracts from Diffusion MRI) machine learning approach was introduced into the standardized workflow of slMFB DBS tractographic planning on the basis of patient-specific dMRI. Rendition of the slMFB with HAMLET serves as an objective comparison for the refinement of the deterministic tracking procedure. Our application focuses on the tractographic planning of DBS (N = 8) for major depression and OCD.ResultsPrevious results have shown that only fibers belonging to the ventral tegmental area to prefrontal/orbitofrontal axis should be targeted. With the proposed technique, the deterministic tracking approach, that serves as the surgical planning data, can be refined, over-sprouting fibers are eliminated, bundle thickness is reduced in the target region, and thereby probably a more accurate targeting is facilitated. The HAMLET-driven method is meant to achieve a more objective surgical fiber display of the slMFB with deterministic tractography.ConclusionsThe approach allows overlying the results of patient-specific planning from two different approaches (manual deterministic and machine learning HAMLET). HAMLET shows the slMFB as a volume and thus serves as an objective tracking corridor. It helps to refine results from deterministic tracking in the surgical workspace without interfering with any part of the standard software solution. We have now included this workflow in our daily clinical experimental work on slMFB DBS for psychiatric indications.
Highlights
There is a growing interest in deep brain stimulation (DBS) of the superolateral medial forebrain bundle for the alleviation of otherwise treatment-resistant psychiatric disorders like major depression (MD) [2, 3, 14, 15, 25] and obsessivecompulsive disorder (OCD) [11, 17]
DBS of the superolateral medial forebrain bundle (slMFB) is performed under tractographic assistance [10, 14, 25] and addresses fibers that project from the ventral tegmental area (VTA) to the prefrontal (PFC) and orbitofrontal (OFC) cortices
In the deep-seated white matter, HAMLET is not able to exclude motor fibers related to ansa lenticularis which run lateral to the slMFB, a phenomenon only appearing in very deep-seated regions of the midbrain
Summary
There is a growing interest in deep brain stimulation (DBS) of the superolateral medial forebrain bundle (slMFB) for the alleviation of otherwise treatment-resistant psychiatric disorders like major depression (MD) [2, 3, 14, 15, 25] and obsessivecompulsive disorder (OCD) [11, 17]. An anatomically plausible display of the structure in a surgical planning system is dependent on a variety of factors (e.g., MRI/DWI sequence quality, field strength, accuracy of ROI definition, algorithms used). Despite the use of clearly defined ROIs and procedural definitions [1, 8,9,10], individual tractographic display of the slMFB remains subjective and is influenced—amongst others—by factors like quality of DTI MRI data, appreciation of the anatomical structure, and accuracy of the ROI definition.
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