Prediction of neurosurgical treatment outcomes in Parkinson’s disease
The project aims at integration of the multimodal patient data such as brain MRI, neurological and neuropsychological assessment, molecular markers, and developing the virtual personalized Parkinson’s disease model for prediction of the neurosurgical treatment outcome and selection of the best treatment strategy.
Parkinson’s disease (PD) is the second most common neurodegenerative disease characterized by a progressive loss of dopaminergic neurons. Deterioration of the dopaminergic system leads to severe motor symptoms including resting tremor, rigidity, bradykinesia and postural instability as well as increased risk of cognitive impairment and decreased quality of life in older age. Current treatments for Parkinson’s disease offer symptomatic relief, but a disease-modifying or neuroprotective agent capable of halting the progression of the disease is not yet available.
This project aims to foster the development of PD treatment, improvement of patient care and patients’ health related quality of life, deepen disease understanding by a) integration of the multimodal data including brain MRI, neurological and neuropsychological assessment, molecular markers using The Virtual Brain platform; b) investigation of new treatment targets to be used in neurosurgery and Gamma knife radiosurgery for PD; c) systematical analysis of outcomes of currently available neurosurgical PD treatment options; d) search for novel radiological and molecular predictors that will allow better patients’ selection for surgical procedures and reduce the risk of postoperative complications.
Uniqueness and novelty of this project also comes from its multidisciplinary approach to patients’ functional status assessment.
Time frame: 2022/01/01 - 2022/12/31
Origin: EBRAINS Research Infrastructure Voucher 2020
Funding: HBP SGA3