An Automated Navigation System for Deep Brain Electrode Implantation

Obsessive-compulsive Disorder Clinical Trial

Official title: An Automated Deep Brain Electrode Implantation System Assisted by Simultaneous Imaging and Electrophysiology Navigation

Status Active, not recruiting

Clinical Trial Summary

1. Analysis of the correlation between imaging and electrophysiological signals.

2. Real time analysis method for optimal implantation position.

3. Simultaneous Imaging and electrophysiology navigation.

4. Accuracy and security verification of navigation system.

Expectation(Hypothesis):

Develop an automated DBS surgical navigation system based on multimodal brain imaging data and neural electro-physiological signals, which can achieve real-time linkage navigation between imaging and electrophysiology, and automatically generate the optimal implantation position of DBS electrodes based on imaging and electrophysiological information through deep learning algorithms, thereby reducing DBS electrode implantation position errors and improving surgical efficacy.

Clinical Trial Description

Firstly, we choose patients who voluntarily participate in this clinical study and sign an informed consent form, whose age range from 35 to 75 years old, regardless of gender. Their clinical diagnosis is consistent with typical Parkinson's disease or muscle tone disorders, and the medical history is within 20 years. Additionally, their MRI examination excludes obvious structural changes. Last but not least, patients should have basic normal vision and hearing, and good compliance.

Then, we collect general information of enrolled patients, input preoperative MRI images of the head and thin-layer CT scans with a head rest on the surgical day into the system for image processing. Connect this system to the electrophysiological signal acquisition system during DBS surgery and record the electrophysiological signals. The first one is to analyze the degree of matching between the position and length of nuclei displayed by electrophysiological signals and imaging information, and verify the matching of the intraoperative imaging electrophysiological linkage tool. At the same time, compare the position and length information of nuclei prompted by the tool with the judgment of the surgeon, and analyze the differences between it and the judgment of clinical doctors. The second one is to using an automatic analysis tool for electrophysiological signals, record the analysis results, compare the optimal electrode implantation position automatically calculated by the system with the final implantation position selected by the surgeon, calculate the differences between the two, and further analyze the differences with the judgment of clinical doctors.

Finally, This study will test the accuracy and usability of the two tools involved in DBS surgery, and collect the following indicators: 1) the length of nuclei and the position of nucleus boundaries on imaging data, the length of nuclei and the position of nucleus boundaries on electrophysiological data, the matching degree between imaging and electrophysiology, and the consistency of nucleus information interpreted by clinical doctors after imaging electrophysiology integration; 2) Using an automatic analysis tool for electrophysiological signals, record the analysis results, compare the optimal electrode implantation position automatically calculated by the system with the final implantation position selected by the surgeon, calculate the differences between the two, and further analyze the differences with the judgment of clinical doctors. ;

Related Conditions & MeSH terms

• Advanced Parkinson's Disease
• Drug Resistant Epilepsy
• Obsessive-Compulsive Disorder
• Parkinson Disease
• Refractory Epilepsy

• NCT number: NCT06396494
• Study type: Observational [Patient Registry]
• Source: Beijing Tiantan Hospital
• Status: Active, not recruiting
• Start date: January 1, 2024
• Completion date: December 31, 2025