DepressionNCT05872607
The Quantitative Study of the Habenula Based on Multi-channel Cascaded Neural Network and the Establishment of the Prediction Model of the Curative Effect in Patients With Depression
An observational study of Depression, run by The First Hospital of Jilin University at 1 site in China.
Trial summary
Depression is the second leading cause of disease burden in our country. It has serious effects on the physical and mental health of human beings, and about 30% of patients with depression are unresponsive or respond poorly to antidepressant treatment. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Depression
- How many people
- 300 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2022to 31 Dec 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Premiere depressed patients
Who may be able to join
- Premiere depressed patients
Who cannot join
- Drug therapy modality change、Incomplete MR image data
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
The First Hospital of Jilin University
Changchun, Jilin, 130000
Lei Zhang, doctor, 15804300150, zlei99@jlu.edu.cn
About this study
Depression is the second leading cause of disease burden in our country. It has serious effects on the physical and mental health of human beings, and about 30% of patients with depression are unresponsive or respond poorly to antidepressant treatment. Clinical practice is in a tough position of wanting objective measures of assessing depression. The applicant and her team have devoted many years to the basic and clinical research on habenular nucleus (Hb) accumulating a significant amount of experience from animal experiments and patients' magnetic resonance (MR) studies. These studies have demonstrated that the habenular nucleus is the key target area that is responsible for the pathophysiological changes in depression as well as its treatment. Small volumes and unsatisfactory contrast have been knotty problems in the MR imaging of Hb. In addition, time-consuming manual segmentation and lack of quantitative standards in conventional studies has impeded the advancement of Hb research. Fortunately, the development of high-resolution multi-parametric quantitative MR imaging and the extensive use of artificial intelligence (AI) technology in medical imaging can just provide powerful support for the imaging, segmentation and quantification of Hb. This project proposes to use high resolution MR anatomy of Hb combined with multimodal fusion to 1) construct a model for automatic 3D segmentation of Hb MR images based on the densely connected multichannel dilated convolutional neural networks; 2) sift out the quantitative imaging signatures related to the antidepressants' efficacy using the radiomics methodology, and in combination with clinical information, construct an individualized prediction model for treatment efficacy.
Overall, this study focuses on the translation of basic research to clinical application in the hope of providing quantifiable objective imaging markers in clinical practice, facilitating clinical decision-making and bringing about individualized precise diagnosis and treatment.
- Conditions
- Depression
- Keywords
- Depression, Habenula, Convolution neural network, Segmentation, Curative effect prediction
- Medical subject headings
- Depression
What is being measured
The primary outcome is the main question the study is designed to answer.
Multimodal MR data of habenula
To extract high-dimensional features of multimodal image data including MP2RAGE, T1MAP, T2 SPACE, DIR, QSM, T2 *
Measured: Baseline (Before medication)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 May 2023
- Study start1 Jan 2022
- Primary completion31 Dec 2024 (estimated)
- Study completion31 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for DepressionStudies of the same condition, open and under way.
- More trials run by The First Hospital of Jilin UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The First Hospital of Jilin University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05872607
- Sponsor's protocol ID
- zlei19810830
- Status last verified
- Feb 2023
- First submitted
- 15 May 2023
- Last updated
- 24 May 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Quantitative Study of the Habenula Based on Multi-channel Cascaded Neural Network and the Establishment of the Prediction Model of the Curative Effect in Patients With Depression
- ClinicalTrials.gov ID
- NCT05872607
- Acronym / sponsor ID
- zlei19810830
- Conditions
- Depression
- Keywords
- Depression, Habenula, Convolution neural network, Segmentation, Curative effect prediction
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- The First Hospital of Jilin UniversityUniversity, hospital or other
- Study start
- 1 Jan 2022 (actual)
- Primary completion
- 31 Dec 2024 (estimated)
- Study completion
- 31 Dec 2024 (estimated)
- First posted
- 24 May 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Depression is the second leading cause of disease burden in our country. It has serious effects on the physical and mental health of human beings, and about 30% of patients with depression are unresponsive or respond poorly to antidepressant treatment. Clinical practice is in a tough position of wanting objective measures of assessing depression. The applicant and her team have devoted many years to the basic and clinical research on habenular nucleus (Hb) accumulating a significant amount of experience from animal experiments and patients' magnetic resonance (MR) studies. These studies have demonstrated that the habenular nucleus is the key target area that is responsible for the pathophysiological changes in depression as well as its treatment. Small volumes and unsatisfactory contrast have been knotty problems in the MR imaging of Hb. In addition, time-consuming manual segmentation and lack of quantitative standards in conventional studies has impeded the advancement of Hb research. Fortunately, the development of high-resolution multi-parametric quantitative MR imaging and the extensive use of artificial intelligence (AI) technology in medical imaging can just provide powerful support for the imaging, segmentation and quantification of Hb. This project proposes to use high resolution MR anatomy of Hb combined with multimodal fusion to 1) construct a model for automatic 3D segmentation of Hb MR images based on the densely connected multichannel dilated convolutional neural networks; 2) sift out the quantitative imaging signatures related to the antidepressants' efficacy using the radiomics methodology, and in combination with clinical information, construct an individualized prediction model for treatment efficacy.
Overall, this study focuses on the translation of basic research to clinical application in the hope of providing quantifiable objective imaging markers in clinical practice, facilitating clinical decision-making and bringing about individualized precise diagnosis and treatment.
Study design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Premiere depressed patients
Key inclusion criteria (1 listed)
- Premiere depressed patients
Key exclusion criteria (1 listed)
- Drug therapy modality change、Incomplete MR image data
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Multimodal MR data of habenula
Time frame: Baseline (Before medication)
To extract high-dimensional features of multimodal image data including MP2RAGE, T1MAP, T2 SPACE, DIR, QSM, T2 *
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 May 2023.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Depression, run by The First Hospital of Jilin University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 24 May 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Lei Zhang, doctor (15804300150, zlei99@jlu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Multimodal MR data of habenula (time frame: Baseline (Before medication)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 May 2023; AzTrials last refreshed its copy on 6 Nov 2026.