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Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study

Not yet recruiting
Conditions
High-grade Glioma
Interventions
Diagnostic Test: MR scanning; Clinical data collection
Registration Number
NCT06002711
Lead Sponsor
RenJi Hospital
Brief 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 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.

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
500
Inclusion Criteria

Retrospective Study:

  1. Participants aged 18 to 70 years, of any gender.
  2. Confirmed postoperative pathology of adult diffuse glioma (WHO Grade III-IV).
  3. Standard MR contrast-enhanced imaging performed within 10 days before surgery.
  4. No history of prior radiotherapy or chemotherapy before surgery.
  5. Absence of concurrent significant comorbidities or other tumors.
  6. Presence of molecular testing results (including IDH, MGMT, 1p19q, TERT, CDKN2A/B, BRAF).
  7. Availability of comprehensive clinical and follow-up data.

Prospective Study:

  1. Participants aged 18 to 70 years, of any gender.
  2. Clinically suspected to have high-grade gliomas preoperatively, with final pathology confirming high-grade gliomas.
  3. Stable vital signs and capable of cooperating for a 40-minute MR scan.
  4. Absence of significant underlying medical conditions or history of other tumors.
  5. Documentation of informed consent through a signed consent form.
Exclusion Criteria

Retrospective Study:

  1. MRI images with artifacts or presence of intratumoral hemorrhage.
  2. Incomplete clinical data available.

Prospective Study:

  1. Individuals with claustrophobia or other reasons unable to undergo MRI scans.
  2. History of allergic reactions to MRI contrast agents.
  3. Inappropriate for prolonged MRI scans due to other reasons.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
retrospective study cohortMR 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 cohortMR 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.
Primary Outcome Measures
NameTimeMethod
Survival prediction model2025.06-2026.09

Survival prediction efficiency of the included samples

Time-depended ROC curve2025.06-2026.09

A time-dependent ROC curve which will be drawn according to the survival analysis.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Department of Radiology, Renji hospital, School of Medicine, Shanghai Jiao Tong University

🇨🇳

Shanghai, Shanghai, China

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