Synovial DiseasesNCT04952896
Clinical Study of Magnetic Resonance Imaging and Deep Learning of Joint Synovial Disease
An observational study of Synovial Diseases and Pigmented Villonodular Synovitis, run by Peking University Third Hospital at 1 site in China.
Trial summary
Through the high-throughput feature extraction of magnetic resonance images, the deep learning prediction model of joint synovial lesions is constructed used for the diagnosis, differential diagnosis and curative effect monitoring of joint synovial lesions. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Synovial Diseases, Pigmented Villonodular Synovitis, Gout
- What is being tested?
- Synovitis diagnosis
- How many people
- 350 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2012to 29 Oct 2022
- 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
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients diagnosed with joint synovial disease through radiological examination, arthroscopy or pathological biopsy of the joint, or whose clinical manifestations meet the diagnostic criteria of the American College of Rheumatology (ACR) for joint synovial disease.
Who may be able to join
- Patients diagnosed with joint synovial disease through radiological examination, arthroscopy or pathological biopsy of the joint, or whose clinical manifestations meet the diagnostic criteria of the American College of Rheumatology (ACR) for joint synovial disease.
- Patients received pre-treatment MR.
Who cannot join
- Patients who have received surgery, medication or other systemic treatment before standardized MRI scan.
- Poor image quality.
- Articular hemorrhage.
Trial locations and contacts
1 site in 1 country.
China1 site
Peking University third hospital
Beijing, Please Select An Option Below, 100089
About this study
Official title: Using Magnetic Resonance Imaging and DL Methods to Explore the Diagnosis and Clinical Prognosis of Joint Synovitis.
Through the high-throughput feature extraction of magnetic resonance images, the deep learning prediction model of joint synovial lesions is constructed used for the diagnosis, differential diagnosis and curative effect monitoring of joint synovial lesions.
Read the detailed description
The study applies magnetic resonance and deep learning (DL) to the diagnosis of joint synovial lesions, aims to have a more comprehensive understanding of the pathophysiology of the occurrence and development of joint synovial lesions. As a non-invasive imaging method to assess the condition of the disease, DL methods excavates the deep features contained in the image, quantifies the joint synovial lesions, and then gives more information to the clinician in the diagnosis and differential diagnosis of the joint synovial lesions, provide important information for the planning of individualized treatment plans for patients with joint synovial diseases.
- Being tested
- Synovitis diagnosis
- Keywords
- pigmented villonodular synovitis, deep learning, knee synovitis, MRI
- Medical subject headings
- Synovitis, Pigmented Villonodular, Gout, Arthritis, Rheumatoid
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Synovitis diagnosisDiagnostic test
| Study group | Role | What they receive |
|---|---|---|
| Group of patients with pigmented villonodular synovitis | Diagnosis confirmed by arthroscopic pathological biopsy. Receives: Diagnostic Test: Synovitis diagnosis | |
| Group of patients with rheumatoid arthritis | Diagnosis determined by clinical history, laboratory tests and arthroscopic pathology biopsy. Receives: Diagnostic Test: Synovitis diagnosis | |
| Group of patients with gout | Diagnosis was determined by laboratory tests, energy spectrum imaging and arthroscopic pathology biopsy. Receives: Diagnostic Test: Synovitis diagnosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient's diagnosis
Type of synovitis disease in patients with a clear comprehensive diagnosis
Measured: 2019-2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jul 2021
- Study start1 Jan 2012
- Primary completion31 Mar 2022
- Study completion29 Oct 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Synovial DiseasesStudies of the same condition, open and under way.
- More trials run by Peking University Third HospitalThe 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
- Case-control
- Time perspective
- Prospective
- Enrolment
- 350 participants (actual)
Sponsor and investigators
- Lead sponsor
- Peking University Third Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04952896
- Sponsor's protocol ID
- LM2019168
- Status last verified
- May 2022
- First submitted
- 29 Jun 2021
- Last updated
- 2 Nov 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 2 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Magnetic Resonance Imaging and DL Methods to Explore the Diagnosis and Clinical Prognosis of Joint Synovitis.
- ClinicalTrials.gov ID
- NCT04952896
- Acronym / sponsor ID
- LM2019168
- Keywords
- pigmented villonodular synovitis, deep learning, knee synovitis, MRI
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 350 participants (actual)
- Lead sponsor
- Peking University Third HospitalUniversity, hospital or other
- Study start
- 1 Jan 2012 (actual)
- Primary completion
- 31 Mar 2022 (actual)
- Study completion
- 29 Oct 2022 (actual)
- First posted
- 7 Jul 2021 (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.
Through the high-throughput feature extraction of magnetic resonance images, the deep learning prediction model of joint synovial lesions is constructed used for the diagnosis, differential diagnosis and curative effect monitoring of joint synovial lesions.
Detailed description
The study applies magnetic resonance and deep learning (DL) to the diagnosis of joint synovial lesions, aims to have a more comprehensive understanding of the pathophysiology of the occurrence and development of joint synovial lesions. As a non-invasive imaging method to assess the condition of the disease, DL methods excavates the deep features contained in the image, quantifies the joint synovial lesions, and then gives more information to the clinician in the diagnosis and differential diagnosis of the joint synovial lesions, provide important information for the planning of individualized treatment plans for patients with joint synovial diseases.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Group of patients with pigmented villonodular synovitis | – | Diagnostic Test: Synovitis diagnosisDiagnosis confirmed by arthroscopic pathological biopsy. |
| Group of patients with rheumatoid arthritis | – | Diagnostic Test: Synovitis diagnosisDiagnosis determined by clinical history, laboratory tests and arthroscopic pathology biopsy. |
| Group of patients with gout | – | Diagnostic Test: Synovitis diagnosisDiagnosis was determined by laboratory tests, energy spectrum imaging and arthroscopic pathology biopsy. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients diagnosed with joint synovial disease through radiological examination, arthroscopy or pathological biopsy of the joint, or whose clinical manifestations meet the diagnostic criteria of the American College of Rheumatology (ACR) for joint synovial disease.
Key inclusion criteria (2 listed)
- Patients diagnosed with joint synovial disease through radiological examination, arthroscopy or pathological biopsy of the joint, or whose clinical manifestations meet the diagnostic criteria of the American College of Rheumatology (ACR) for joint synovial disease.
- Patients received pre-treatment MR.
Key exclusion criteria (3 listed)
- Patients who have received surgery, medication or other systemic treatment before standardized MRI scan.
- Poor image quality.
- Articular hemorrhage.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Synovitis diagnosis | Diagnostic test | Group of patients with gout, Group of patients with pigmented villonodular synovitis, Group of patients with rheumatoid arthritis |
Primary outcome
Patient's diagnosis
Time frame: 2019-2022
Type of synovitis disease in patients with a clear comprehensive diagnosis
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Nov 2022.
- Individual participant dataSharing planned: Yes
Related trials for Synovial Diseases
Recruiting
Synovial Tissue as a Biomarker in the Management of Pigmented Villonodular Synovitis
Synovitis Villonodular
RecruitingObservational study
Exploring Factors Linked to Worsening Over Time in People With Early-stage Knee Osteoarthritis and Those With Prior Proven Acute Knee Injury.
Knee Osteoarthritis
RecruitingObservational study
Evaluation for NCI Surgery Branch Clinical Research Protocols
Synovial Cell Cancer, Melanoma
RecruitingObservational study
SVF Cellular Composition, Secretome, and Responses in Knee Osteoarthritis
Osteoarthritis, Knee
RecruitingPhase 1
AOH1996 for the Treatment of Refractory Solid Tumors
Refractory Malignant Solid Neoplasm, Osteosarcoma
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.
The record lists no contact. Use the official record to reach the sponsor.
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 Synovial Diseases and Pigmented Villonodular Synovitis, run by Peking University Third Hospital 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 2 inclusion and 3 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: finished, as of the sponsor's last update on 2 Nov 2022. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient's diagnosis (time frame: 2019-2022). 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 2 Nov 2022.