A Network Analysis of 15O-H2O PET Reveals Deep Brain Stimulation Effects on Brain Network of Parkinson's Disease.
10.3349/ymj.2015.56.3.726
- Author:
Hae Jeong PARK
1
;
Bumhee PARK
;
Hae Yu KIM
;
Maeng Keun OH
;
Joong Il KIM
;
Misun YOON
;
Jong Doo LEE
;
Jin Woo CHANG
Author Information
1. Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Korea.
- Publication Type:Original Article ; Research Support, Non-U.S. Gov't
- Keywords:
Deep brain stimulation;
brain networks;
Parkinson's disease;
H2O PET;
independent component analysis
- MeSH:
Aged;
Brain/*radionuclide imaging;
Cross-Sectional Studies;
Deep Brain Stimulation/*methods;
Female;
Functional Laterality/*physiology;
Humans;
Male;
Middle Aged;
Parkinson Disease/radionuclide imaging/*therapy;
Positron-Emission Tomography;
Severity of Illness Index;
Subthalamic Nucleus/*physiopathology
- From:Yonsei Medical Journal
2015;56(3):726-736
- CountryRepublic of Korea
- Language:English
-
Abstract:
PURPOSE: As Parkinson's disease (PD) can be considered a network abnormality, the effects of deep brain stimulation (DBS) need to be investigated in the aspect of networks. This study aimed to examine how DBS of the bilateral subthalamic nucleus (STN) affects the motor networks of patients with idiopathic PD during motor performance and to show the feasibility of the network analysis using cross-sectional positron emission tomography (PET) images in DBS studies. MATERIALS AND METHODS: We obtained [15O]H2O PET images from ten patients with PD during a sequential finger-to-thumb opposition task and during the resting state, with DBS-On and DBS-Off at STN. To identify the alteration of motor networks in PD and their changes due to STN-DBS, we applied independent component analysis (ICA) to all the cross-sectional PET images. We analysed the strength of each component according to DBS effects, task effects and interaction effects. RESULTS: ICA blindly decomposed components of functionally associated distributed clusters, which were comparable to the results of univariate statistical parametric mapping. ICA further revealed that STN-DBS modifies usage-strengths of components corresponding to the basal ganglia-thalamo-cortical circuits in PD patients by increasing the hypoactive basal ganglia and by suppressing the hyperactive cortical motor areas, ventrolateral thalamus and cerebellum. CONCLUSION: Our results suggest that STN-DBS may affect not only the abnormal local activity, but also alter brain networks in patients with PD. This study also demonstrated the usefulness of ICA for cross-sectional PET data to reveal network modifications due to DBS, which was not observable using the subtraction method.
