Assessing Deep Brain Stimulation Efficacy in Epilepsy: Target Accuracy and Thalamic Pathology
Presented During:
Wednesday, June 25, 2025: 6:45 PM - 6:57 PM
Brisbane Convention & Exhibition Centre
Room:
Great Hall
Poster No:
6
Submission Type:
Abstract Submission
Authors:
Yejin Ann1, Young-Min Shon2, Seok-Jun Hong3
Institutions:
1Sungkyunkwan University, Suwon, Korea, Republic of, 2Samsung Medical Center, Seoul, Korea, Republic of, 3IBS Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, Korea, Republic of
First Author:
Co-Author(s):
Seok-Jun Hong
IBS Center for Neuroscience Imaging Research, Sungkyunkwan University
Suwon, Korea, Republic of
IBS Center for Neuroscience Imaging Research, Sungkyunkwan University
Suwon, Korea, Republic of
Introduction:
The anterior and centromedian thalamic nuclei (ATN, CM) are commonly targeted regions in deep brain stimulation (DBS) for epilepsy (Fig 1A). The motivation for this target strategy is related to the circuits they are involved in. On the one hand, the ATN, which plays a vital role in seizure propagation of focal epilepsy with a mesial temporal focus, is a core node of the Papez circuit that is central to the functional dynamics of the entire limbic structures. On the other hand, the CM, often associated with generalized epilepsy, is also the core of the cerebello-thalamic-cortical (CTC) circuit characterized by diffuse cortical projections [1]. While the efficacy of targeting these nuclei has been previously replicated, the details of the biological substrates that may affect its outcomes remain poorly understood. Here, we sought to address this question by assessing i) the relation between DBS target accuracy and seizure reduction, ii) pathological effects on the thalamic nuclei and their white matter bundles based on the morphological analysis and track density imaging (TDI) and finally iii) the clinical utility of these neuroimaging features to classify responder and non-responder groups (RG/NRG).
Methods:
Our study consists of three analyses: 1) To examine the effect of DBS target accuracy on seizure reduction, we first analyzed structural MRIs of 53 patients (34 focal [ATN], 19 generalized epilepsy [CM]) and computed a dice index (DI) between the stimulated areas and the MRI-validated thalamic nucleus segmentation (Fig 1B). A receiver operating characteristic curve was plotted to evaluate the classification accuracy for RG and NRG (Fig 1C). 2) Next, to investigate which biological factor could affect such DBS outcomes, we examined the morphological change of the thalamus using SPHARM-MAT [2] (Fig 2A) as well as the network substrates connected to the targeted thalamic nuclei (Fig 2B). Specifically for the latter, we delineated the Papez and CTC circuits based on diffusion tractography and compared the track density between RG, NRG and healthy controls using voxel-wise TDI analyses [3]. 3) Finally we have used three neuroimaging features that have been analyzed so far - Dice index, Deformation from the shape analysis, and track density from DTI - to train the machine learning classification algorithm (i.e., RUSBoost) with a leave-one-out validation to predict RG and NRG (Fig 2C).
Results:
The receiver operating characteristic curve for classifying RG/NRG revealed an area under the curve of 0.81 for ATN and 0.37 for CM (Fig 1C). It suggests that in the ATN (but not CM) group, the higher the overlap between the stimulated areas and the thalamic nucleus is, the better the SR is. In the following shape analysis, the RG revealed more atrophic patterns across multiple thalamic nuclei (Fig 2A) and increased track density along the specific thalamic pathway (Fig 2B) than NRG in both ATN and CM groups. Lastly, multimodal imaging-based classification demonstrated a higher accuracy to that of the unimodal in both ATN (≥ 0.85) and CM groups (≥ 0.77) (Fig 2C).
Conclusions:
Our study suggested that DBS surgical outcomes are influenced by the accuracy of stimulation targeting as well as the pathological characteristics of a relevant circuitry within and beyond the thalamus. Leveraging multimodal imaging features to quantify these potential factors could enhance our ability to predict the seizure outcome after DBS. Further investigation on how DBS modulates brain networks and its functional impact on seizure dynamics is required to elucidate the mechanisms underlying the lower surgical efficacy observed in patients targeting the CM nucleus.
Brain Stimulation:
Deep Brain Stimulation 1
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Keywords:
Epilepsy
MRI
Thalamus
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
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2. Calamante, F., Tournier, J. D., Jackson, G. D., & Connelly, A. (2010). Track-density imaging (TDI): super-resolution white matter imaging using whole-brain track-density mapping. Neuroimage, 53(4), 1233-1243.
3. Shen, L. (2010). SPHARM-MAT v1. 0.0 documentation.