» Articles » PMID: 30133472

Patient-specific Anatomical Model for Deep Brain Stimulation Based on 7 Tesla MRI

Overview
Journal PLoS One
Date 2018 Aug 23
PMID 30133472
Citations 36
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: Deep brain stimulation (DBS) requires accurate localization of the anatomical target structure, and the precise placement of the DBS electrode within it. Ultra-high field 7 Tesla (T) MR images can be utilized to create patient-specific anatomical 3D models of the subthalamic nuclei (STN) to enhance pre-surgical DBS targeting as well as post-surgical visualization of the DBS lead position and orientation. We validated the accuracy of the 7T imaging-based patient-specific model of the STN and measured the variability of the location and dimensions across movement disorder patients.

Methods: 72 patients who underwent DBS surgery were scanned preoperatively on 7T MRI. Segmentations and 3D volume rendering of the STN were generated for all patients. For 21 STN-DBS cases, microelectrode recording (MER) was used to validate the segmentation. For 12 cases, we computed the correlation between the overlap of the STN and volume of tissue activated (VTA) and the monopolar review for a further validation of the model's accuracy and its clinical relevancy.

Results: We successfully reconstructed and visualized the STN in all patients. Significant variability was found across individuals regarding the location of the STN center of mass as well as its volume, length, depth and width. Significant correlations were found between MER and the 7T imaging-based model of the STN (r = 0.86) and VTA-STN overlap and the monopolar review outcome (r = 0.61).

Conclusion: The results suggest that an accurate visualization and localization of a patient-specific 3D model of the STN can be generated based on 7T MRI. The imaging-based 7T MRI STN model was validated using MER and patient's clinical outcomes. The significant variability observed in the STN location and shape based on a large number of patients emphasizes the importance of an accurate direct visualization of the STN for DBS targeting. An accurate STN localization can facilitate postoperative stimulation parameters for optimized patient outcome.

Citing Articles

Virtual anatomical atlas of the deep brain nuclei.

Sevgi U, Gungor A, Erol G, Canbolat C, Middlebrooks E, Sonmez O Neurosurg Rev. 2024; 47(1):849.

PMID: 39607537 DOI: 10.1007/s10143-024-03096-3.


Machine learning for the localization of Subthalamic Nucleus during deep brain stimulation surgery: a systematic review and Meta-analysis.

Inggas M, Coyne T, Taira T, Karsten J, Patel U, Kataria S Neurosurg Rev. 2024; 47(1):774.

PMID: 39387996 DOI: 10.1007/s10143-024-03010-x.


Neural pathways associated with reduced rigidity during pallidal deep brain stimulation for Parkinson's disease.

Lecy E, Linn-Evans M, Amundsen-Huffmaster S, Palnitkar T, Patriat R, Chung J J Neurophysiol. 2024; 132(3):953-967.

PMID: 39110516 PMC: 11427047. DOI: 10.1152/jn.00155.2024.


Active contact proximity to the cerebellothalamic tract predicts initial therapeutic current requirement with DBS for ET: an application of 7T MRI.

Ikramuddin S, Brinda A, Butler R, Hill M, Dharnipragada R, Aman J Front Neurol. 2023; 14:1258895.

PMID: 38020603 PMC: 10666159. DOI: 10.3389/fneur.2023.1258895.


Role of the volume conductor on simulations of local field potential recordings from deep brain stimulation electrodes.

Noor M, Howell B, McIntyre C PLoS One. 2023; 18(11):e0294512.

PMID: 38011104 PMC: 10681243. DOI: 10.1371/journal.pone.0294512.


References
1.
Kim J, Lenglet C, Duchin Y, Sapiro G, Harel N . Semiautomatic segmentation of brain subcortical structures from high-field MRI. IEEE J Biomed Health Inform. 2014; 18(5):1678-95. PMC: 4381448. DOI: 10.1109/JBHI.2013.2292858. View

2.
Lin L . A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989; 45(1):255-68. View

3.
Hamel W, Koppen J, Alesch F, Antonini A, Barcia J, Bergman H . Targeting of the Subthalamic Nucleus for Deep Brain Stimulation: A Survey Among Parkinson Disease Specialists. World Neurosurg. 2016; 99:41-46. DOI: 10.1016/j.wneu.2016.11.012. View

4.
Pereira J, B A S, Sharim J, Yazdi D, DeSalles A, Pouratian N . Lateralization of the Subthalamic Nucleus with Age in Parkinson's Disease. Basal Ganglia. 2016; 6(2):83-88. PMC: 4755314. DOI: 10.1016/j.baga.2016.01.003. View

5.
Shamir R, Dolber T, Noecker A, Walter B, McIntyre C . Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease. Brain Stimul. 2015; 8(6):1025-32. PMC: 5015434. DOI: 10.1016/j.brs.2015.06.003. View