Value of functional connectivity in outcome prediction for pallidal stimulation in Parkinson disease

Yijie LaiDepartment of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;

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Naying HeDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;

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Hongjiang WeiDepartment of Biomedical Engineering, Institute for Medical Imaging Technology, Shanghai Jiao Tong University, Shanghai, China;

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Lifu DengCenter for Cognitive Neuroscience, Duke University, Durham, North Carolina;

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Haiyan ZhouDepartment of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;

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Jun LiSchool of Information Science and Technology, Shanghai Technical University, Shanghai, China;

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Marcus KaiserSchool of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom; and

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Chencheng ZhangDepartment of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;
Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai, China

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Dianyou LiDepartment of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;

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Bomin SunDepartment of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;

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OBJECTIVE

Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction.

METHODS

The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome.

RESULTS

Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = −0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive.

CONCLUSIONS

The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.

ABBREVIATIONS

AC-PC = anterior commissure–posterior commissure; DBS = deep brain stimulation; fMRI = functional MRI; FOV = field of view; GPe = globus pallidus externus; GPi = globus pallidus internus; LEDD = levodopa-equivalent daily dose; MDS-UPDRS III = Movement Disorder Society Unified Parkinson’s Disease Rating Scale Part III; MNI = Montreal Neurological Institute; M1 = primary motor cortex; PD = Parkinson disease; PIGD = postural instability/gait difficulty; PMC = premotor cortex; PMd = PMC dorsal plane; PMv = PMC ventral plane; PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses; SMA = supplementary motor area; STN = subthalamic nucleus; TD = tremor dominant; VTA = volume of tissue activated.

Supplementary Materials

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Figure from Ramos et al. (pp 95–103).

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