ArticleContrast media & molecular imaging2021
The Impacts of Subthalamic Nucleus-Deep Brain Stimulation (STN-DBS) on the Neuropsychiatric Function of Patients with Parkinson's Disease Using Image Features of Magnetic Resonance Imaging under the Artificial Intelligence Algorithms.
Article in Contrast media & molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Computational Insights Into Smart Bioelectronics in Digital Health Care (2020-2024): Topic Modeling Study.JMIR medical informatics · 2026Review
- AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.Brain sciences · 2025Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was to explore the effect of subthalamic nucleus- (STN-) deep brain stimulation (DBS) on the neuropsychiatric function of Parkinson's disease (PD) patients using the magnetic resonance imaging (MRI) image analysis technology and the artificial intelligence (AI) algorithm. In this study, 40 PD patients admitted to our hospital from August 2018 to March 2020 were selected as the research objects, and they were divided into a control group and an observation group according to the random number table method, with 20 cases in each group. The patients in the control group were given oral treatment with levodopa tablets; and patients in the observation group were treated with STN-DBS + levodopa tablets. In patients, MRI examinations were performed before and after the treatment, and the image optimization processing algorithm under AI was adopted to process the images. The MRI imaging results of the two groups of patients were observed, analyzed, and compared before and after treatment; and the sports, cognition, and mental states of the two groups of patients were analyzed. It was believed that the MRI image before using the AI algorithm was blurry, and the image was clear after the noise reduction optimization process, which was convenient for observation. The data analysis revealed that the signal-to-noise ratio (SNR) after denoising (32.41) and structural similarity (SSIM) (0.79) had been improved. The results of the study suggested that the space occupation and bleeding symptoms of the two groups of patients were reduced after treatment, and those in the observation group were better than those of the control group; the incidences of dyskinesia and motor symptom fluctuations in the observation group were 5% and 0%, respectively, which were lower than those in the control group (35% and 25%, respectively). After treatment, the Unified Parkinson's Disease Rating Scale (UPDRS) score of the two groups of patients decreased, and it was lower in the observation group than in the control group; and the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Scale (MMSE) scores increased, and those in the observation group were higher in contrast to those in the control group (all
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