An Automated Navigation System for Deep Brain Electrode Implantation

Active, not recruiting

• Conditions: Refractory Epilepsy; Obsessive-compulsive Disorder; Advanced Parkinson's Disease

• Registration Number: NCT06396494
• Lead Sponsor: Beijing Tiantan Hospital

Brief 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.

Detailed 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.

Study Timeline

• Study Start: 2024-01-01
• Primary Completion: 2024-03-18
• Study First Submitted: 2024-04-11
• Status Verified: 2024-05
• Study First Submitted QC: 2024-05-01
• Last Update Submitted: 2024-05-01
• Study First Posted: 2024-05-02
• Last Update Posted: 2024-05-02
• Study Completion: 2025-12-31

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 30

Inclusion Criteria

• Clinical diagnosis is consistent with typical Parkinson's disease or dystonia, and the medical history is within 20 years;
• MRI examination excludes obvious structural changes.

Exclusion Criteria

• Severe mental, cognitive, or psychological disorders ;
• Contraindications to neurosurgery, such as hydrocephalus, brain atrophy, sequelae of cerebrovascular disease, heart disease, etc. Cardiovascular and cerebrovascular diseases;
• The presence of tumors, severe abnormalities in liver and kidney function (indicators more than 3 times normal) and other concomitant diseases that seriously affect health;
• The presence of intracranial mass, cerebrovascular disease, mental illness, and other neurological diseases , claustrophobia or implants in the body that affect MRI scans.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The accuracy of automatic electrode position analysis tools	2025.12	The best placement of the electrode (indicated by coordinates) is compared with the final placement of the implant selected by the surgeon (indicated by coordinates), then the difference between the two is calculated in millimeters as the outcome measures.

Secondary Outcome Measures

Name	Time	Method
The matching of image-electrophysiology linkage tools	2025.12	Record the boundary of the nucleus (in millimeters) on the imaging data and the boundary of the nucleus (in millimeters) on the electrophysiological data. The difference between these two nuclear information data is calculated as the outcome measures to verify the image-electrophysiological matching.

Trial Locations

Locations (1)

Beijing Tiantan Hospital; 🇨🇳 Beijing, Beijing, China