Precise placement of DBS electrodes can facilitate maximal therapeutic outcomes with minimal side effects [13
]. As such, DBS surgical targeting continues to evolve and become more precise with new advances in imaging, neurophysiology, and brain atlas technology. This proof of principle study presents a technique to automate the alignment of a generic 3-dimensional brain atlas to intraoperative MER, and thereby assist in the definition of a stereotactic target location for implantation of the DBS electrode.
Recent advances in MRI make it possible to directly define target locations by direct visualization of nuclei such as the STN [30
]. However, contrast and resolution limitations in mainstream MR scanners deter many from only using imaging data to make DBS implantation decisions [6
]. As such, current techniques for electrode placement typically require indirect probabilistic targeting [1
]. Furthermore, the large anatomical variability across patients provides motivation for the use of additional techniques that characterize the topography within the nucleus [5
] and refine the implant location for the DBS electrode [3
One traditional technique for integrating the multiple data sets used in DBS surgery is the manual overlay of 2-dimensional brain atlas slices that approximate specific regions of the brain onto graphs of MER points [5
]. However, this process can be taxing given that the patient's MR images, brain atlas, and MER points are typically not coplanar, or are not available in a common visualization platform. Thus, strict adherence to the stereotactic coordinate system is typically lost, thereby limiting accuracy of the data analysis and target predictions. This study provides an example of how multiple data sets can be used together within the same stereotactic coordinate system.
Our results showed significantly larger distances between therapeutic electrode contacts and theoretical targets predicted by the conventional AC/PC method compared to the human expert and optimization fitting methods. Previous studies have proposed that there are no additional benefits from using sophisticated computer systems and high-field MRI for DBS target identification when compared to traditional indirect AC/PC-based methods [34
]. In contrast, our results suggest that AC/PC-based target identification does not adequately account for the substantial variability in patient brain geometry [30
In general, brain atlases are associated with numerous limitations. Commonly used atlases are constructed from a single brain that may not be representative of the broader patient population or disease state. In addition, even after an atlas is fit to a patient's brain the atlas may be misleading to the true anatomy of the patient. We restricted our atlas fits to the use of linear transformations (i.e., atlas is nondeformable) to maintain the original anatomical relationships between brain nuclei. One advantage of this method is that it limits the degrees of freedom and can be used with any 3-dimensional brain atlas. However, advances in nonlinear brain atlas deformation algorithms could increase correctly fitted MER percentages, and provide better adherence to the neuroanatomy visible in the MRI [14
]. It might also be useful to include additional constraints from image-based landmarks and/or weighting schemes to account for known locations of side effects identified by macro/ microstimulation to further improve the optimization-based fit [3
Our optimization algorithm performed as well as experienced human experts, but in less time and without interexpert variability. Although the human expert fits achieved similar percentages of correctly fitted MER, the transformations required to position the brain atlas with respect to each patient's MER were significantly different (p < 0.05), particularly in three degrees of freedom: dorsoventral translation (tz), rotation about the dorsoventral (vertical) axis, and scaling along the medial-lateral direction. Thus, while the strategies followed by individual experts may provide a similar overall outcome, small differences in the fitting process can add variance to the analysis and determination of a target location. Larger fitting error variance in the human expert fit (σ2 = 475 mm2) than in the optimization fit (σ2 = 106 mm2) suggests that the optimization algorithm provides more consistent fits.
Algorithms, similar to that presented in this study, could be developed to suggest stereotactic trajectories for MER that maximize the probability of gathering information to constrain the fit. Such an advance could reduce the number of penetrations required for target identification. For example, after a single MER track the fit between a brain atlas and the MER points is relatively unconstrained (fig. ); however, acquisition of data along specific trajectories can substantially limit the possible permutations of the brain atlas to fit the data. Computational assistance in subsequent track selection could offer a degree of standardization that might benefit less experienced users by improving consistency across procedures and maximizing the amount of information gained by each track.
Human interpretation remains the gold standard for neurophysiological identification of MER points and nuclei borders. However, the fitting performance and speed of the optimization algorithm create a realistic opportunity for its clinical use during DBS surgeries. The basic goal would be to assist human experts in their decision-making process. Although traditional (manual) atlas fitting techniques can be performed while the microelectrode is being retracted and readied for the next track, fast automated atlas fits (which can be updated as each new MER point is acquired) allow the surgical team to dedicate more time to critical decision-making instead of manual atlas fits.
The results of this study support the concept that computational refinement of DBS target locations based on 3-dimensional brain atlases and MER can assist electrode placement. The atlas fitting and targeting method presented here, coupled with advanced DBS surgical navigation software tools [6
], should improve the management of data and allow for selection of an optimal DBS electrode location in a reduced amount of time. As DBS applications and target sites continue to expand, 3-dimensional renderings of atlases and trajectories may improve opportunities to optimize the stimulation of targeted brain regions with novel electrode placement strategies.