AstrocytomaNCT05624736
Hierarchical Diagnosis for Adult Diffuse Glioma Based on Deep Learning
An observational study of Astrocytoma and Glioblastoma Multiforme, run by The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School at 1 site in China.
Trial summary
This is a restrospective study to establish a deep learning model based on multi-parametric magnetic resonance imaging scans to predict Grade, histopathologic type and genotype of adult diffuse Glioma. Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Astrocytoma, Glioblastoma Multiforme, Oligodendroglioma
- What is being tested?
- multi-parametric magnetic resonance imaging scan and Pathology examination
- How many people
- 500 participants
- Where
- 1 siteChina
- Study dates
- 20 Nov 2022to 1 May 2025
- 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 18 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with diagnosis of adult diffuse glioma who recevived tumor rection surgery in our center
Who may be able to join
- Patients undergoing surgery in Nanjing DrumTower Hospital between 2010.01 and 2022.05 with post-surgery pathological diagnosis of WHO Grade II to IV Adult Diffuse Glioma.
- Available pre-surgery T1WI, T2WI, T1CE, FLARI and DWI MR sequences
- No pre-surgery anti-tumor therapy
Who cannot join
- Poor image quality
- Failed image preprocessing
- Unavailable pathology data
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Department of Radiology, the Affiliated Drum Tower Hospital of Nanjing University
Nanjing, Jiangsu, 210093
Xin Zhang, Master, 13814066403, zhangxin@njglyy.com
About this study
Official title: Artificial Intelligence Research of Hierarchical Diagnosis for Adult Diffuse Glioma Based on Deep Learning
This is a restrospective study to establish a deep learning model based on multi-parametric magnetic resonance imaging scans to predict Grade, histopathologic type and genotype of adult diffuse Glioma.
Read the detailed description
Glioma is a common kind of tumor in central nervous system. The pre-operative prediction of grade, histopathologic type and genotype is important for treatment and management of Adult diffuse Glioma patients. Right now, most of the diagnostic prediction models on glioma are based on 2016 WHO central nervous system tumor guideline. The goal of this study is to establish a new deep learning model to predict Grade, histopathologic type and genotype of adult diffuse Glioma. We will recruit 500 patients with pathologically confirmed diagnosis of Glioblastoma, Astrocytoma and Oligodendroglioma who received neurologic surgery in our center. Each subject underwent pre-operative multi-parametric magnetic resonance imaging scans including T1WI, T2WI, T1CE, FLAIR and DWI. Pathologic diagnosis of each patient are available in pathology department. A deep learning based hierarchical diagnosis
- Conditions
- Astrocytoma, Glioblastoma Multiforme, Oligodendroglioma
- Being tested
- multi-parametric magnetic resonance imaging scan, Pathology examination
- Keywords
- Astrocytoma, Glioblastoma, Oligodendroglioma, deep learning, artificial intelligence
- Medical subject headings
- Astrocytoma, Glioblastoma, Oligodendroglioma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
multi-parametric magnetic resonance imaging scanDiagnostic test
Pre-operative multi-parametric magnetic resonance imaging scans including T1WI, T2WI, T1CE, FLAIR and DWI were taken for clinical needs.
Pathology examinationDiagnostic test
The tumor specimen obtained from the surgery were sent to the pathology department for histopathologic examination, immunohistochemistry and gene sequencing test
| Study group | Role | What they receive |
|---|---|---|
| Glioblastoma Group | Patients with the diagnosis of Glioblastoma based on 2021 WHO central nervous system tumor guideline. Receives: Diagnostic Test: multi-parametric magnetic resonance imaging scan; Diagnostic Test: Pathology examination | |
| Astrocytoma Group | Patients with the diagnosis of Astrocytoma based on 2021 WHO central nervous system tumor guideline. Receives: Diagnostic Test: multi-parametric magnetic resonance imaging scan; Diagnostic Test: Pathology examination | |
| Oligodendroglioma Group | Patients with the diagnosis of Oligodengroglioma based on 2021 WHO central nervous system tumor guideline. Receives: Diagnostic Test: multi-parametric magnetic resonance imaging scan; Diagnostic Test: Pathology examination |
What is being measured
The primary outcome is the main question the study is designed to answer.
Tumor Grade
Tumor Grade based on 2021 WHO central nervous system tumor guideline
Measured: up to 2 weeks
Tumor Histologic diagnosis
Tumor histologic diagnosis based on 2021 WHO central nervous system tumor guideline
Measured: up to 2 weeks
Tumor genotype
Tumor genotype based on 2021 WHO central nervous system tumor guideline
Measured: up to 2 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Nov 2022
- Study start20 Nov 2022 (estimated)
- Primary completion1 May 2023 (estimated)
- Study completion1 May 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AstrocytomaStudies of the same condition, open and under way.
- More trials run by The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical SchoolThe 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 crossover
- Time perspective
- Retrospective
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05624736
- Sponsor's protocol ID
- 2022-LCYJ-MS-25
- Status last verified
- Jul 2022
- First submitted
- 13 Nov 2022
- Last updated
- 22 Nov 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: We don't plan to share IPD with other researches
Study at a glance
From the registry record, last updated by the sponsor on 22 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence Research of Hierarchical Diagnosis for Adult Diffuse Glioma Based on Deep Learning
- ClinicalTrials.gov ID
- NCT05624736
- Acronym / sponsor ID
- 2022-LCYJ-MS-25
- Conditions
- Astrocytoma, Glioblastoma Multiforme, Oligodendroglioma
- Keywords
- Astrocytoma, Glioblastoma, Oligodendroglioma, deep learning, artificial intelligence
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical SchoolUniversity, hospital or other
- Study start
- 20 Nov 2022 (estimated)
- Primary completion
- 1 May 2023 (estimated)
- Study completion
- 1 May 2025 (estimated)
- First posted
- 22 Nov 2022 (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.
This is a restrospective study to establish a deep learning model based on multi-parametric magnetic resonance imaging scans to predict Grade, histopathologic type and genotype of adult diffuse Glioma.
Detailed description
Glioma is a common kind of tumor in central nervous system. The pre-operative prediction of grade, histopathologic type and genotype is important for treatment and management of Adult diffuse Glioma patients. Right now, most of the diagnostic prediction models on glioma are based on 2016 WHO central nervous system tumor guideline. The goal of this study is to establish a new deep learning model to predict Grade, histopathologic type and genotype of adult diffuse Glioma. We will recruit 500 patients with pathologically confirmed diagnosis of Glioblastoma, Astrocytoma and Oligodendroglioma who received neurologic surgery in our center. Each subject underwent pre-operative multi-parametric magnetic resonance imaging scans including T1WI, T2WI, T1CE, FLAIR and DWI. Pathologic diagnosis of each patient are available in pathology department. A deep learning based hierarchical diagnosis
Study design
- Observational model
- Case crossover
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Glioblastoma Group | – | Diagnostic Test: multi-parametric magnetic resonance imaging scan, Diagnostic Test: Pathology examinationPatients with the diagnosis of Glioblastoma based on 2021 WHO central nervous system tumor guideline. |
| Astrocytoma Group | – | Diagnostic Test: multi-parametric magnetic resonance imaging scan, Diagnostic Test: Pathology examinationPatients with the diagnosis of Astrocytoma based on 2021 WHO central nervous system tumor guideline. |
| Oligodendroglioma Group | – | Diagnostic Test: multi-parametric magnetic resonance imaging scan, Diagnostic Test: Pathology examinationPatients with the diagnosis of Oligodengroglioma based on 2021 WHO central nervous system tumor guideline. |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with diagnosis of adult diffuse glioma who recevived tumor rection surgery in our center
Key inclusion criteria (3 listed)
- Patients undergoing surgery in Nanjing DrumTower Hospital between 2010.01 and 2022.05 with post-surgery pathological diagnosis of WHO Grade II to IV Adult Diffuse Glioma.
- Available pre-surgery T1WI, T2WI, T1CE, FLARI and DWI MR sequences
- No pre-surgery anti-tumor therapy
Key exclusion criteria (3 listed)
- Poor image quality
- Failed image preprocessing
- Unavailable pathology data
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 |
|---|---|---|
| multi-parametric magnetic resonance imaging scanPre-operative multi-parametric magnetic resonance imaging scans including T1WI, T2WI, T1CE, FLAIR and DWI were taken for clinical needs. | Diagnostic test | Astrocytoma Group, Glioblastoma Group, Oligodendroglioma Group |
| Pathology examinationThe tumor specimen obtained from the surgery were sent to the pathology department for histopathologic examination, immunohistochemistry and gene sequencing test | Diagnostic test | Astrocytoma Group, Glioblastoma Group, Oligodendroglioma Group |
Primary outcome
Tumor Grade
Time frame: up to 2 weeks
Tumor Grade based on 2021 WHO central nervous system tumor guideline
Tumor Histologic diagnosis
Time frame: up to 2 weeks
Tumor histologic diagnosis based on 2021 WHO central nervous system tumor guideline
Tumor genotype
Time frame: up to 2 weeks
Tumor genotype based on 2021 WHO central nervous system tumor guideline
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Nov 2022.
- Individual participant dataSharing planned: No. We don't plan to share IPD with other researches
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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 Astrocytoma and Glioblastoma Multiforme, run by The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School 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 3 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: status not confirmed, as of the sponsor's last update on 22 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Xin Zhang, Master (13814066403, zhangxin@njglyy.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Tumor Grade (time frame: up to 2 weeks). The study lists 3 primary outcomes in all. 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 22 Nov 2022.