MR scanning; Clinical data collection
Diagnostic TestMulti-dimensional spatial heterogeneity analysis of MRI
NCT Number: NCT06002711
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.
Interested in participating?
Request Info18 year–70 year
All sexes
Observational
Department of Radiology, Renji Hospital School of Medicine, Shanghai Jiao Tong University, Shanghai, Select A State Or Province, China
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.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Retrospective Study:
Prospective Study:
Exclusion criteria
Retrospective Study:
Prospective Study:
Multi-dimensional spatial heterogeneity analysis of MRI
Time frame: 2025.06-2026.09
Survival prediction efficiency of the included samples
Time frame: 2025.06-2026.09
A time-dependent ROC curve which will be drawn according to the survival analysis.
Contact information is provided by the study sponsor or research team.
RenJi Hospital
Other
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT06482905
Glioma, High-Grade Glioma
Phoenix, Arizona, United States
View Trial DetailsNCT07480941
Astrocytoma, Glioblastoma
Shenzhen, Guangdong, China
View Trial DetailsNCT06829173
Glioma, High-Grade Glioma
New York, United States
View Trial DetailsNCT04299191
Glioma, High-Grade Glioma
Little Rock, Arkansas, United States
View Trial Details