Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study
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ClinicalTrials.gov Identifier: NCT06002711 |
Recruitment Status :
Not yet recruiting
First Posted : August 21, 2023
Last Update Posted : August 21, 2023
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Tracking Information | |||||
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First Submitted Date | August 16, 2023 | ||||
First Posted Date | August 21, 2023 | ||||
Last Update Posted Date | August 21, 2023 | ||||
Estimated Study Start Date | September 1, 2023 | ||||
Estimated Primary Completion Date | September 30, 2026 (Final data collection date for primary outcome measure) | ||||
Current Primary Outcome Measures |
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Original Primary Outcome Measures | Same as current | ||||
Change History | No Changes Posted | ||||
Current Secondary Outcome Measures | Not Provided | ||||
Original Secondary Outcome Measures | Not Provided | ||||
Current Other Pre-specified Outcome Measures | Not Provided | ||||
Original Other Pre-specified Outcome Measures | Not Provided | ||||
Descriptive Information | |||||
Brief Title | Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study | ||||
Official Title | Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study | ||||
Brief Summary |
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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. |
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Study Type | Observational | ||||
Study Design | Observational Model: Cohort Time Perspective: Other |
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Target Follow-Up Duration | Not Provided | ||||
Biospecimen | Not Provided | ||||
Sampling Method | Non-Probability Sample | ||||
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. | ||||
Condition | High-grade Glioma | ||||
Intervention | Diagnostic Test: MR scanning; Clinical data collection
Multi-dimensional spatial heterogeneity analysis of MRI
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Study Groups/Cohorts |
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Publications * |
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* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline. |
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Recruitment Information | |||||
Recruitment Status | Not yet recruiting | ||||
Estimated Enrollment |
500 | ||||
Original Estimated Enrollment | Same as current | ||||
Estimated Study Completion Date | December 31, 2027 | ||||
Estimated Primary Completion Date | September 30, 2026 (Final data collection date for primary outcome measure) | ||||
Eligibility Criteria | Inclusion Criteria: Retrospective Study:
Prospective Study:
Exclusion Criteria: Retrospective Study:
Prospective Study:
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Sex/Gender |
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Ages | 18 Years to 70 Years (Adult, Older Adult) | ||||
Accepts Healthy Volunteers | No | ||||
Contacts |
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Listed Location Countries | China | ||||
Removed Location Countries | |||||
Administrative Information | |||||
NCT Number | NCT06002711 | ||||
Other Study ID Numbers | RenJiH-Rad-IIT-2023-0141 IIT-2023-0141 ( Other Identifier: Renji hospital, School of Medicine, Shanghai Jiao Tong University ) |
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Has Data Monitoring Committee | No | ||||
U.S. FDA-regulated Product |
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IPD Sharing Statement |
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Current Responsible Party | RenJi Hospital | ||||
Original Responsible Party | Same as current | ||||
Current Study Sponsor | RenJi Hospital | ||||
Original Study Sponsor | Same as current | ||||
Collaborators | Not Provided | ||||
Investigators | Not Provided | ||||
PRS Account | RenJi Hospital | ||||
Verification Date | August 2023 |