Deep Brain Stimulation (DBS) is commonly used to treat, inter alia, movement disorder symptoms in patients with Parkinson’s disease, dystonia or essential tremor. The procedure stimulates a targeted region of the brain through implanted leads that are powered by a device called an implantable pulse generator (IPG). The mentioned targeted region is mainly chosen to be subthalamic nucleus (STN) during most of the operations. STN is a nucleus in the midbrain with a size of 3 mm × 5 mm × 9 mm that consist of parts with different physiological functions. The purpose of the study was to predict Parkinson’s patient’s symptoms defined by Unified Parkinson’s Disease Rating Scale (UPDRS) that may occur after the DBS treatment. Parameters had been obtained from 3DSlicer (Harvard Medical School, Boston, MA), which allowed us to track connections between the stimulated part of STN and the cortex based on the DTI (diffusion tensor imaging).

The results have shown that it is possible to introduce a new, autonomous, doctor independent and a highly accurate method of disease course prediction.


Key Value
Title DTI helps to predict Parkinson’s patient’s symptoms using data mining techniques
Author Chudzik, Artur and Szymański, Artur and Nowacki, Jerzy Paweł and Przybyszewski, Andrzej W
Book title Asian Conference on Intelligent Information and Database Systems
Pages 615-623
Year 2019
Publisher Springer
DOI 10.1007/978-3-030-14802-7_53