High-grade GliomaNCT06002711
Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study
An observational study of High-grade Glioma, run by RenJi Hospital at 2 sites in China.
Trial summary
1. To retrospectively explore the feasibility of multi-dimensional heterogeneity imaging features of MRI in predicting the status of key gene mutations in high-grade gliomas; 2. To prospectively explore the correlation between multi-dimensional heterogeneous MRI image features and prognosis of high-grade glioma… Read more about this study
- Who is it for?
- Ages 18 to 70 years
- Conditions the study is for
- High-grade Glioma
- What is being tested?
- MR scanning; Clinical data collection
- How many people
- 500 participants
- Where
- 2 sitesChina
- Study dates
- 1 Sep 2023to 31 Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: High-grade glioma patients were recruited from multiple research centers, including Renji Hospital, Shanghai Jiao Tong University School of Medicine, Huashan Hospital, Fudan University; Shanghai Jing'an District Central Hospital, and Nantong First People's Hospital.
Who may be able to join
- Retrospective Study:
- Participants aged 18 to 70 years, of any gender.
- Confirmed postoperative pathology of adult diffuse glioma (WHO Grade III-IV).
- Standard MR contrast-enhanced imaging performed within 10 days before surgery.
- No history of prior radiotherapy or chemotherapy before surgery.
- Absence of concurrent significant comorbidities or other tumors.
Show all 14Show fewer
- Presence of molecular testing results (including IDH, MGMT, 1p19q, TERT, CDKN2A/B, BRAF).
- Availability of comprehensive clinical and follow-up data.
- Prospective Study:
- Participants aged 18 to 70 years, of any gender.
- Clinically suspected to have high-grade gliomas preoperatively, with final pathology confirming high-grade gliomas.
- Stable vital signs and capable of cooperating for a 40-minute MR scan.
- Absence of significant underlying medical conditions or history of other tumors.
- Documentation of informed consent through a signed consent form.
Who cannot join
- Retrospective Study:
- MRI images with artifacts or presence of intratumoral hemorrhage.
- Incomplete clinical data available.
- Prospective Study:
- Individuals with claustrophobia or other reasons unable to undergo MRI scans.
- History of allergic reactions to MRI contrast agents.
- Inappropriate for prolonged MRI scans due to other reasons.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China2 sites, 1 recruiting
- Recruiting
Department of Radiology, Renji Hospital School of Medicine, Shanghai Jiao Tong University
Shanghai, Select A State Or Province, 200127
Yan Zhou, Dr., +8613816523205, 787229957@qq.com
- Active, not recruiting
Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University
Shanghai, Shanghai Municipality, 200127
About this study
- To retrospectively explore the feasibility of multi-dimensional heterogeneity imaging features of MRI in predicting the status of key gene mutations in high-grade gliomas;
- To prospectively explore the correlation between multi-dimensional heterogeneous MRI image features and prognosis of high-grade glioma patients.
Read the detailed description
Glioblastoma, the most prevalent primary intracranial tumor, is characterized by its formidable therapeutic resistance, primarily attributed to its intrinsic heterogeneity. This heightened heterogeneity is not solely confined to inter-tumoral variations across different individuals but also encompasses considerable intratumoral diversity. The pervasive notion among the scientific community posits that this intratumoral heterogeneity substantiates an endogenous mechanism for drug resistance, thereby exerting substantial influence upon the design of clinical trials, prognostic prediction, and patient outcomes. Preceding methodologies for assessment are beleaguered by a constellation of challenges, impeding precise evaluation of global tumor heterogeneity and necessitating innovative modalities to surmount this impasse. MRI imaging, endowed with non-invasiveness and user-friendliness, surmounts the biases of single-point sampling, enabling comprehensive and dynamic appraisal of glioblastomas. Notably, high-grade gliomas exhibit pronounced microenvironmental pressure selectivity and adaptability, akin to species occupation within distinct ecological niches. This phenomenon, termed "habitat," manifests as a visual representation of the tumor's spatial distribution and temporal evolution, thus facilitating real-time, longitudinal monitoring. Given the substantial imaging heterogeneity inherent to glioblastomas, they stand as an opportune subject for habitat imaging techniques compared to their neoplastic counterparts.
The present investigation endeavors to leverage multi-center, multi-dimensional MRI spatial heterogeneity analysis to predict pivotal genes germane to prognosis and therapy in high-grade gliomas, ultimately constructing a stratified prognostic model for afflicted patients.
- Conditions
- High-grade Glioma
- Being tested
- MR scanning; Clinical data collection
- Keywords
- glioma; MRI; spatial heterogeneity; habitat
- Medical subject headings
- Glioma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
MR scanning; Clinical data collectionDiagnostic test
Multi-dimensional spatial heterogeneity analysis of MRI
| Study group | Role | What they receive |
|---|---|---|
| retrospective study cohort | In the retrospective study, patient cases will be gathered from multi-center repositories, where surgical cases will be confirmed to be high-grade gliomas and will undergo preoperative contrast-enhanced MRI examinations. These patients will possess comprehensive clinical, pathological, and genetic data. Receives: Diagnostic Test: MR scanning; Clinical data collection | |
| Prospective study cohort | The prospective study will encompass a cohort of individuals who are clinically suspected to have high-grade gliomas and will undergo multimodal MRI imaging. Subsequent to surgery, their postoperative pathology will confirm the diagnosis of high-grade gliomas. Following the surgical intervention, these patients will undergo standard procedures for radiotherapy and chemotherapy, as well as regular follow-up assessments. Receives: Diagnostic Test: MR scanning; Clinical data collection |
What is being measured
The primary outcome is the main question the study is designed to answer.
Survival prediction model
Survival prediction efficiency of the included samples
Measured: 2025.06-2026.09
Time-depended ROC curve
A time-dependent ROC curve which will be drawn according to the survival analysis.
Measured: 2025.06-2026.09
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Aug 2023
- Study start1 Sep 2023
- Primary completion30 Sep 2026 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for High-grade GliomaStudies of the same condition, open and under way.
- More trials run by RenJi 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
- Cohort
- Time perspective
- Other
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- RenJi Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06002711
- Sponsor's protocol ID
- RenJiH-Rad-IIT-2023-0141
- Other IDs
- IIT-2023-0141
- Status last verified
- Aug 2025
- First submitted
- 16 Aug 2023
- Last updated
- 8 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Cao M, Wang X, Liu F, Xue K, Dai Y, Zhou Y. A three-component multi-b-value diffusion-weighted imaging might be a useful biomarker for detecting microstructural features in gliomas with differences in malignancy and IDH-1 mutation status. Eur Radiol. 2023 Apr;33(4):2871-2880. doi: 10.1007/s00330-022-09212-5. Epub 2022 Nov 8.
PubMed 36346441Cao M, Suo S, Zhang X, Wang X, Xu J, Yang W, Zhou Y. Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach. Biomed Res Int. 2021 Jan 22;2021:1235314. doi: 10.1155/2021/1235314. eCollection 2021.
PubMed 33553421Cao M, Ding W, Han X, Suo S, Sun Y, Wang Y, Qu J, Zhang X, Zhou Y. Brain T1rho mapping for grading and IDH1 gene mutation detection of gliomas: a preliminary study. J Neurooncol. 2019 Jan;141(1):245-252. doi: 10.1007/s11060-018-03033-7. Epub 2018 Nov 9.
PubMed 30414094Dextraze K, Saha A, Kim D, Narang S, Lehrer M, Rao A, Narang S, Rao D, Ahmed S, Madhugiri V, Fuller CD, Kim MM, Krishnan S, Rao G, Rao A. Spatial habitats from multiparametric MR imaging are associated with signaling pathway activities and survival in glioblastoma. Oncotarget. 2017 Dec 5;8(68):112992-113001. doi: 10.18632/oncotarget.22947. eCollection 2017 Dec 22.
PubMed 29348883Park JE, Kim HS, Kim N, Park SY, Kim YH, Kim JH. Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma. Clin Cancer Res. 2021 Jan 1;27(1):237-245. doi: 10.1158/1078-0432.CCR-20-2156. Epub 2020 Oct 7.
PubMed 33028594
Study at a glance
From the registry record, last updated by the sponsor on 8 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study
- ClinicalTrials.gov ID
- NCT06002711
- Acronym / sponsor ID
- RenJiH-Rad-IIT-2023-0141
- Conditions
- High-grade Glioma
- Keywords
- glioma; MRI; spatial heterogeneity; habitat
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- RenJi HospitalUniversity, hospital or other
- Study start
- 1 Sep 2023 (actual)
- Primary completion
- 30 Sep 2026 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 21 Aug 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.
- To retrospectively explore the feasibility of multi-dimensional heterogeneity imaging features of MRI in predicting the status of key gene mutations in high-grade gliomas;
- To prospectively explore the correlation between multi-dimensional heterogeneous MRI image features and prognosis of high-grade glioma patients.
Detailed description
Glioblastoma, the most prevalent primary intracranial tumor, is characterized by its formidable therapeutic resistance, primarily attributed to its intrinsic heterogeneity. This heightened heterogeneity is not solely confined to inter-tumoral variations across different individuals but also encompasses considerable intratumoral diversity. The pervasive notion among the scientific community posits that this intratumoral heterogeneity substantiates an endogenous mechanism for drug resistance, thereby exerting substantial influence upon the design of clinical trials, prognostic prediction, and patient outcomes. Preceding methodologies for assessment are beleaguered by a constellation of challenges, impeding precise evaluation of global tumor heterogeneity and necessitating innovative modalities to surmount this impasse. MRI imaging, endowed with non-invasiveness and user-friendliness, surmounts the biases of single-point sampling, enabling comprehensive and dynamic appraisal of glioblastomas. Notably, high-grade gliomas exhibit pronounced microenvironmental pressure selectivity and adaptability, akin to species occupation within distinct ecological niches. This phenomenon, termed "habitat," manifests as a visual representation of the tumor's spatial distribution and temporal evolution, thus facilitating real-time, longitudinal monitoring. Given the substantial imaging heterogeneity inherent to glioblastomas, they stand as an opportune subject for habitat imaging techniques compared to their neoplastic counterparts.
The present investigation endeavors to leverage multi-center, multi-dimensional MRI spatial heterogeneity analysis to predict pivotal genes germane to prognosis and therapy in high-grade gliomas, ultimately constructing a stratified prognostic model for afflicted patients.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| retrospective study cohort | – | Diagnostic Test: MR scanning; Clinical data collectionIn the retrospective study, patient cases will be gathered from multi-center repositories, where surgical cases will be confirmed to be high-grade gliomas and will undergo preoperative contrast-enhanced MRI examinations. These patients will possess comprehensive clinical, pathological, and genetic data. |
| Prospective study cohort | – | Diagnostic Test: MR scanning; Clinical data collectionThe prospective study will encompass a cohort of individuals who are clinically suspected to have high-grade gliomas and will undergo multimodal MRI imaging. Subsequent to surgery, their postoperative pathology will confirm the diagnosis of high-grade gliomas. Following the surgical intervention, these patients will undergo standard procedures for radiotherapy and chemotherapy, as well as regular follow-up assessments. |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- High-grade glioma patients were recruited from multiple research centers, including Renji Hospital, Shanghai Jiao Tong University School of Medicine, Huashan Hospital, Fudan University; Shanghai Jing'an District Central Hospital, and Nantong First People's Hospital.
Key inclusion criteria (14 listed)
- Participants aged 18 to 70 years, of any gender.
- Confirmed postoperative pathology of adult diffuse glioma (WHO Grade III-IV).
- Standard MR contrast-enhanced imaging performed within 10 days before surgery.
- No history of prior radiotherapy or chemotherapy before surgery.
- Absence of concurrent significant comorbidities or other tumors.
Key exclusion criteria (7 listed)
- MRI images with artifacts or presence of intratumoral hemorrhage.
- Incomplete clinical data available.
- Individuals with claustrophobia or other reasons unable to undergo MRI scans.
- History of allergic reactions to MRI contrast agents.
- Inappropriate for prolonged MRI scans due to other reasons.
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 |
|---|---|---|
| MR scanning; Clinical data collectionMulti-dimensional spatial heterogeneity analysis of MRI | Diagnostic test | Prospective study cohort, retrospective study cohort |
Primary outcome
Survival prediction model
Time frame: 2025.06-2026.09
Survival prediction efficiency of the included samples
Time-depended ROC curve
Time frame: 2025.06-2026.09
A time-dependent ROC curve which will be drawn according to the survival analysis.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Aug 2025.
- Background: PubMed 36346441Cao M, Wang X, Liu F, Xue K, Dai Y, Zhou Y. A three-component multi-b-value diffusion-weighted imaging might be a useful biomarker for detecting microstructural features in gliomas with differences in malignancy and IDH-1 mutation status. Eur Radiol. 2023 Apr;33(4):2871-2880. doi: 10.1007/s00330-022-09212-5. Epub 2022 Nov 8.
- Background: PubMed 33553421Cao M, Suo S, Zhang X, Wang X, Xu J, Yang W, Zhou Y. Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach. Biomed Res Int. 2021 Jan 22;2021:1235314. doi: 10.1155/2021/1235314. eCollection 2021.
- Background: PubMed 30414094Cao M, Ding W, Han X, Suo S, Sun Y, Wang Y, Qu J, Zhang X, Zhou Y. Brain T1rho mapping for grading and IDH1 gene mutation detection of gliomas: a preliminary study. J Neurooncol. 2019 Jan;141(1):245-252. doi: 10.1007/s11060-018-03033-7. Epub 2018 Nov 9.
- Background: PubMed 29348883Dextraze K, Saha A, Kim D, Narang S, Lehrer M, Rao A, Narang S, Rao D, Ahmed S, Madhugiri V, Fuller CD, Kim MM, Krishnan S, Rao G, Rao A. Spatial habitats from multiparametric MR imaging are associated with signaling pathway activities and survival in glioblastoma. Oncotarget. 2017 Dec 5;8(68):112992-113001. doi: 10.18632/oncotarget.22947. eCollection 2017 Dec 22.
- Background: PubMed 33028594Park JE, Kim HS, Kim N, Park SY, Kim YH, Kim JH. Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma. Clin Cancer Res. 2021 Jan 1;27(1):237-245. doi: 10.1158/1078-0432.CCR-20-2156. Epub 2020 Oct 7.
- Individual participant dataSharing planned: Undecided
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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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of High-grade Glioma, run by RenJi Hospital at 2 sites 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 14 inclusion and 7 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: looking for participants now, as of the sponsor's last update on 8 Aug 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yan Zhou, MD,PhD (+86-021-68383086, clare1475@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Survival prediction model (time frame: 2025.06-2026.09). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06002711, which also lists 5 linked publications.
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 8 Aug 2025.