Ningbo Yu1,2, Siquan Liang3, Jiewei Lu1,2, Zhilin Shu1,2, Haitao Li3, Yang Yu4, Jialing Wu5,6,7, Jianda Han8,9. 1. College of Artificial Intelligence, Nankai University, Tianjin, China. 2. Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China. 3. Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China. 4. Department of Neurorehabilitation, Tianjin Huanhu Hospital, Tianjin, China. 5. Department of Neurorehabilitation, Tianjin Huanhu Hospital, Tianjin, China. wywjl2009@hotmail.com. 6. Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China. wywjl2009@hotmail.com. 7. Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin Neurosurgical Institute, Tianjin Huanhu Hospital, Tianjin, China. wywjl2009@hotmail.com. 8. College of Artificial Intelligence, Nankai University, Tianjin, China. hanjianda@nankai.edu.cn. 9. Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin, China. hanjianda@nankai.edu.cn.
Abstract
BACKGROUND: Deep brain stimulation (DBS) has proved effective for Parkinson's disease (PD), but the identification of stimulation parameters relies on doctors' subjective judgment on patient behavior. METHODS: Five PD patients performed 10-meter walking tasks under different brain stimulation frequencies. During walking tests, a wearable functional near-infrared spectroscopy (fNIRS) system was used to measure the concentration change of oxygenated hemoglobin (△HbO2) in prefrontal cortex, parietal lobe and occipital lobe. Brain functional connectivity and global efficiency were calculated to quantify the brain activities. RESULTS: We discovered that both the global and regional brain efficiency of all patients varied with stimulation parameters, and the DBS pattern enabling the highest brain efficiency was optimal for each patient, in accordance with the clinical assessments and DBS treatment decision made by the doctors. CONCLUSIONS: Task fNIRS assessments and brain functional connectivity analysis promise a quantified and objective solution for patient-specific optimization of DBS treatment. TRIAL REGISTRATION: Name: Accurate treatment under the multidisciplinary cooperative diagnosis and treatment model of Parkinson's disease. Registration number is ChiCTR1900022715. Date of registration is April 23, 2019.
BACKGROUND: Deep brain stimulation (DBS) has proved effective for Parkinson's disease (PD), but the identification of stimulation parameters relies on doctors' subjective judgment on patient behavior. METHODS: Five PDpatients performed 10-meter walking tasks under different brain stimulation frequencies. During walking tests, a wearable functional near-infrared spectroscopy (fNIRS) system was used to measure the concentration change of oxygenated hemoglobin (△HbO2) in prefrontal cortex, parietal lobe and occipital lobe. Brain functional connectivity and global efficiency were calculated to quantify the brain activities. RESULTS: We discovered that both the global and regional brain efficiency of all patients varied with stimulation parameters, and the DBS pattern enabling the highest brain efficiency was optimal for each patient, in accordance with the clinical assessments and DBS treatment decision made by the doctors. CONCLUSIONS: Task fNIRS assessments and brain functional connectivity analysis promise a quantified and objective solution for patient-specific optimization of DBS treatment. TRIAL REGISTRATION: Name: Accurate treatment under the multidisciplinary cooperative diagnosis and treatment model of Parkinson's disease. Registration number is ChiCTR1900022715. Date of registration is April 23, 2019.
Authors: Andres M Lozano; Nir Lipsman; Hagai Bergman; Peter Brown; Stephan Chabardes; Jin Woo Chang; Keith Matthews; Cameron C McIntyre; Thomas E Schlaepfer; Michael Schulder; Yasin Temel; Jens Volkmann; Joachim K Krauss Journal: Nat Rev Neurol Date: 2019-03 Impact factor: 42.937