Application of MRI to DBS Patients
Noam Harel1
1University of Minnesota, Minneapolis, MN, United States

Synopsis

Deep brain stimulation (DBS) can be highly effective at improving symptoms and enhancing the patient’s quality of life. However, clinical outcomes can vary greatly within- and across-studies. Much of this variability can likely be accounted for by differences in the stimulating lead location. High resolution 7T MRI data provides a unique opportunity to create an accurate, patient-specific, 3D anatomical model for visualization of the target structures. Accurate lead location, in respect to the anatomical borders of the intended target structure and its functional domains, is a crucial information for an efficient programming for patient optimal benefits.

Deep brain stimulation (DBS) is a surgical therapy that involves implanting electrodes deep within the brain into very specific anatomical targets. These electrodes produce electrical impulses that modulate abnormal neuronal activity and circuits. DBS treatment can be highly effective at improving symptoms and enhancing the patient’s quality of life. However, identification of subcortical brain structures for DBS surgery targeting on standard clinical MRI is challenging and may lead to inaccurate targeting which results is suboptimal electrode placement that has been associated with reduced efficacy and adverse effects. As a result, clinical outcomes can vary significantly within- and across-studies. Much of this variability can likely be accounted for by differences in electrode location [1, 2]. High-field 7 Tesla (T) MRI provides enhanced SNR and high-resolution images with an improved contrast of brain structures that are otherwise unobservable in-vivo [3, 4]. Combining multi-modal 7T imaging including T1-weighted, T2-weighted, susceptibility weighted imaging (SWI) and multi-directional diffusion-weighted imaging, a comprehensive, patient-specific, 3D anatomical model of the target region and the associated connectivity networks can be created [5-7]. The 7T MRI-based patient-specific anatomical models were validated against neurophysiological and clinical data obtained from the same patients. These 7T studies have demonstrated marked inter-individual variability in the size, shape, and orientation of the subthalamic nucleus (STN) [5, 6, 8] and the globus pallidus interna (GPi) [9], the main targets for DBS in Parkinson’s disease patients.Pushing forward this technology, it is now feasible to perform a patient-specific dissection of the target structure into its subdivisions, i.e., parcellation to its functional domains [10]. These new imaging and post-processing capabilities allow for a direct targeting surgical approach with accurate delivery of the DBS lead into the intended sub-region of the anatomical structure. Furthermore, by combining the postoperative computed-tomography (CT) images, the final electrode location, its individual contacts and orientations, can be accurately determined [11, 12]. Lead location, in respect to the anatomical borders of the intended target structure and its functional domains, is a crucial information for an efficient programming of the patient for optimal benefits [13]. Another advantage that the 7T imaging data provides is the ability to generate ground-truth data to be used for training deep-learning algorithms for precise segmentations of basal ganglia structures. Robust, accurate, and automated techniques are needed for reliability and reduction of human bias as well as increased segmentation throughput especially now that the 7T MRI is FDA approved for clinical applications [14, 15].

Acknowledgements

National Institution of Health; P50 NS098753, R01 NS081118, R01 NS113746

References

1. Starr, P.A., et al., Magnetic resonance imaging-based stereotactic localization of the globus pallidus and subthalamic nucleus. Neurosurgery, 1999. 44(2): p. 303-13; discussion 313-4.

2. Rolston, J.D., et al., An unexpectedly high rate of revisions and removals in deep brain stimulation surgery: Analysis of multiple databases. Parkinsonism Relat Disord, 2016. 33: p. 72-77.

3. Abosch, A., et al., An assessment of current brain targets for deep brain stimulation surgery with susceptibility-weighted imaging at 7 tesla. Neurosurgery, 2010. 67(6): p. 1745-56; discussion 1756.

4. Forstmann, B.U., et al., Multi-modal ultra-high resolution structural 7-Tesla MRI data repository. Sci Data, 2014. 1: p. 140050.

5. Duchin, Y., et al., Patient-specific anatomical model for deep brain stimulation based on 7 Tesla MRI. PLoS One, 2018. 13(8): p. e0201469.

6. Plantinga, B.R., et al., Individualized parcellation of the subthalamic nucleus in patients with Parkinson's disease with 7T MRI. Neuroimage, 2018. 168: p. 403-411.

7. Lenglet, C., et al., Comprehensive in vivo mapping of the human basal ganglia and thalamic connectome in individuals using 7T MRI. PLoS One, 2012. 7(1): p. e29153.

8. Keuken, M.C., et al., Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI. Neuroimage, 2014. 94: p. 40-46.

9. Patriat, R., et al., Individualized tractography-based parcellation of the globus pallidus pars interna using 7T MRI in movement disorder patients prior to DBS surgery. Neuroimage, 2018. 178: p. 198-209.

10. Behrens, T.E., et al., Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci, 2003. 6(7): p. 750-7.

11. Shamir, R.R., et al., Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery. Neurosurgery, 2018.

12. Aman, J.E., et al., Directional deep brain stimulation leads reveal spatially distinct oscillatory activity in the globus pallidus internus of Parkinson's disease patients. Neurobiol Dis, 2020. 139: p. 104819.

13. Schrock, L.E., et al., 7T MRI and Computational Modeling Supports a Critical Role of Lead Location in Determining Outcomes for Deep Brain Stimulation: A Case Report. Front Hum Neurosci, 2021. 15: p. 631778.

14. Kim, J., et al., Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation. Hum Brain Mapp, 2019. 40(2): p. 679-698.

15. Solomon, O., et al., Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI. Hum Brain Mapp, 2021.

Figures

7T MRI for DBS applications

Proc. Intl. Soc. Mag. Reson. Med. 29 (2021)