Brain network analysis using 7-Tesla MRI and magnetoencephalography for deep brain stimulation

The effect of deep brain stimulation (DBS) relies on the modulation of
dysfunctional motor brain networks. On average, 50% motor improvement is
achieved, using standardized motor assessments. However, approximately 20% of
patients shows insufficient benefit, with less than 30% improvement. To improve
these outcomes, better electrode placement and selection of DBS electrical
parameter programming is needed. This necessitates more advanced visualization
of the intricate motor networks; both anatomical (7 Tesla MRI) and functional
(MEG). Current DBS implantations are based on 1.5- or 3- Tesla MR scans. The
resolution of these scans however, is not sufficient enough to visualize brain
networks, preventing precise electrode placement directly at the motor parts
within the small (size of a coffee bean) brain nucleus. In addition to the 7
Tesla MRI guided electrode placement, programming will be directed at
influencing the cortical motor areas, by applying MEG, resulting in an overall
decrease in dysfunctional network activity; instead of the "one-brain" model
for everyone, DBS thereby becomes patient-specific, focused on one's own brain
network.

Hypothesis: implementation of individualized, integrated 7 Tesla MRI and MEG
brain networks can increase the effectiveness of DBS by improving motor
symptoms and quality of life in patients with Parkinson's disease and essential
tremor.

Objective 1. Visualization of motor projections and the position of the DBS
electrode relative to these projections using 7 Tesla MRI in 270 patients; the
anatomical 7 Tesla MRI brain networks. (Figure 2 left)
Objective 2. Visualization of cortical activity and distribution of the effect
of DBS using MEG in 270 patients; the functional MEG brain networks.
Objective 3. To relate brain networks from D1 and D2 to motor improvements by
DBS with different electrode programming. The pathophysiological network and
the correlation of the DBS effect on brain network activity is visualized; the
optimal DBS electrode programming is selected. (Figure 2 right)
Objective 4. After selecting the best DBS programming (D3), the goal is to
optimize the outcome of DBS in 270 patients by: a) increasing the mean
improvement in motor function and quality of life by at least 10% b) achieving
a minimum of 30% improvement in motor function for each patient (measured by
standardized assessment of motor function and quality of life).
Objective 5. Develop a prediction model based on the generated networks
(connectomes) using the variable autoencoder (machine learning algorithm).
Create a (7 Tesla MRI and MEG) open access database including the connectomes;
applicable in any center for both clinical and fundamental studies.

Single-center, prospective study with repeated measures; standardized
evaluations of motor skills and quality of life (UPDRS-III, PDQ-39, TETRAS)
after DBS placement will be compared with scores after adjustments based on
network analyses.

Patients will undergo an additional MEG scan.

The 7-Tesla MRI and MEG protocols (including stimulation parameters) already
developed by our group and reported in (five) studies will be applied. After
selecting the best DBS programming, the aim is to optimize DBS outcome by: a)
increasing the mean improvement in motor function and quality of life by at
least 10% and b) achieving a minimum of 30% improvement in motor function for
each patient (measured by standardized assessment of motor function and quality
of life). The proposed research project involves treatment options that are
non-invasive and/or part of standard care in daily practice. The therapies will
not be combined with other research products. Participation in this study
constitutes negligible risk according to NFU criteria for human research.