Objective: To propose a definition of Subthalamic Nucleus Deep Brain Stimulation (STN-DBS) electrode misplacement (MP) based on ideal brain connectivity strength.

Background: MP is defined as >2mm deviation from the expected target,[1]​ and is suggested to account for 46% of DBS failures.[2] However, empirical confirmation for this definition has not been published.

Method: A theoretical exercise based on an ideal target stimulation and its pattern of connectivity was carried out. An ideal STN-DBS connectivity profile model to treat PD was estimated based on a suggested “sweet spot” (X=±12.58mm, Y=-13.41mm, Z=-5.87mm, MNI space) correlated with optimal clinical response.[3-5] Using Lead-DBS software,[6] a volume of tissue activated (VTA) was generated and its connectivity strength with cortical​​​​ parcellations [7,8] using a normative​​ connectome was estimated for the sweet spot.[9,10] Then, this procedure was repeated for 1mm stepwise displacements in each axis (X,Y,Z) in both hemispheres. Changes in connectivity strength were defined as the percentage of error relative to the “sweet spot”.

Results: Lateral displacements of 1mm increased connectivity strength with M1 by approximately 50%. Further lateral displacements exponentially increased connectivity to the sensorimotor cortex. Medial displacements required >3 mm to decrease connectivity to those areas by >50%. Posterior displacements of 1mm increased connectivity to M1 by >50%, with further displacements progressively increasing connectivity to sensorimotor cortex. Anterior displacements of >2 mm decreased connectivity to the same areas by  >50%. Ventral displacement required >3mm to increase connectivity strength to sensorimotor cortex by >50%, whereas dorsal displacement >2mm decreased connectivity strength by >50%. Differences between hemispheres were observed in the Z-axis.

Conclusion: Displacement from the sweet spot does not produce equivalent changes in connectivity strength in any direction. This study explores the limits of admissible MP, which depend on the direction and magnitude of the displacement. Connectivity strength gradually changes as the VTA moves away from the target, but it causes an abrupt change when intersecting structures related to adverse effects.

References: [1] K. E. Lyons, S. B. Wilkinson, J. Overman, and R. Pahwa, “Surgical and hardware complications of subthalamic stimulation,” Neurology, vol. 63, no. 4, pp. 612–616, Aug. 2004, doi: 10.1212/01.WNL.0000134650.91974.1A.
[2] M. S. Okun et al., “Management of Referred Deep Brain Stimulation Failures: A Retrospective Analysis From 2 Movement Disorders Centers,” Arch Neurol, vol. 62, no. 8, pp. 1250–1255, Aug. 2005, doi: 10.1001/ARCHNEUR.62.8.NOC40425.
[3] F. Caire, D. Ranoux, D. Guehl, P. Burbaud, and E. Cuny, “A systematic review of studies on anatomical position of electrode contacts used for chronic subthalamic stimulation in Parkinson’s disease,” Acta Neurochir (Wien), vol. 155, no. 9, pp. 1647–1654, Sep. 2013, doi: 10.1007/S00701-013-1782-1.
[4] A. Horn, A. A. Kühn, A. Merkl, L. Shih, R. Alterman, and M. Fox, “Probabilistic conversion of neurosurgical DBS electrode coordinates into MNI space,” Neuroimage, vol. 150, pp. 395–404, Apr. 2017, doi: 10.1016/J.NEUROIMAGE.2017.02.004.
[5] M. Bot et al., “Deep brain stimulation for Parkinson’s disease: defining the optimal location within the subthalamic nucleus,” J Neurol Neurosurg Psychiatry, vol. 89, no. 5, pp. 493–498, May 2018, doi: 10.1136/JNNP-2017-316907.
[6] A. Horn et al., “Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging,” Neuroimage, vol. 184, pp. 293–316, Jan. 2019, doi: 10.1016/J.NEUROIMAGE.2018.08.068.
[7] M. A. Mayka, D. M. Corcos, S. E. Leurgans, and D. E. Vaillancourt, “Three-dimensional locations and boundaries of motor and premotor cortices as defined by functional brain imaging: A meta-analysis,” Neuroimage, vol. 31, no. 4, p. 1453, Jul. 2006, doi: 10.1016/J.NEUROIMAGE.2006.02.004.
[8] E. T. Rolls, M. Joliot, and N. Tzourio-Mazoyer, “Implementation of a new parcellation of the orbitofrontal cortex in the automated anatomical labeling atlas,” Neuroimage, vol. 122, pp. 1–5, Nov. 2015, doi: 10.1016/J.NEUROIMAGE.2015.07.075.
[9] S. Ewert et al., “Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity,” Neuroimage, vol. 170, pp. 271–282, Apr. 2018, doi: 10.1016/J.NEUROIMAGE.2017.05.015.
[10] K. Marek et al., “The Parkinson Progression Marker Initiative (PPMI),” Prog Neurobiol, vol. 95, no. 4, pp. 629–635, Dec. 2011, doi: 10.1016/J.PNEUROBIO.2011.09.005.

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