Ignite Creation Date:
2025-12-25 @ 1:33 AM
Ignite Modification Date:
2025-12-27 @ 4:31 AM
Study NCT ID:
NCT06396494
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-05-02
First Post:
2024-04-11
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
An Automated Navigation System for Deep Brain Electrode Implantation
Sponsor:
Beijing Tiantan Hospital
Organization:
Study Overview
Official Title:
An Automated Deep Brain Electrode Implantation System Assisted by Simultaneous Imaging and Electrophysiology Navigation
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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.
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.
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 Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: