Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT06396494 |
| Other study ID # |
YGLX202321 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
January 1, 2024 |
| Est. completion date |
December 31, 2025 |
Study information
| Verified date |
May 2024 |
| Source |
Beijing Tiantan Hospital |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational [Patient Registry]
|
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.
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.
