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NCT04908267

How the Precise Habitats Can Predict the IDH Mutation Status and Prognosis of the Patients With High-grade Gliomas

Status unknown Last updated 11 January 2023
What this trial tests

trial in High-grade Glioma in 100 participants. Status unknown.

Timeline
1 August 2022
Primary endpoint
31 December 2024
31 December 2024

Quick facts

Lead sponsorWeiguo Zhang
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment100
Start date1 August 2022
Primary completion31 December 2024
Estimated completion31 December 2024
Sites1 location across China

Conditions studied

Sponsor

Weiguo Zhang

Who can join

18 and older, any sex, with High-grade Glioma. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

High-grade glioma is the most common primary malignant tumor in central nervous system, and its high tumor heterogeneity is the main cause of tumor progression, treatment resistance and recurrence. Habitat imaging is a segmentation technique by dividing tumor regions to characterize tumor heterogeneity based on tumor pathology, blood perfusion, molecular characteristics and other tumor biological features. In some studies, the Hemodynamic Multiparametric Tissue Signature (HTS) method has been proven to be feasible. The Hemodynamic Multiparametric Tissue Signature (HTS) consists of a set of vascular habitats obtained by Dynamic Susceptibility Weighted Contrast Enhanced Magnetic Resonance Imaging (DSC-MRI) of high-grade gliomas using a multiparametric unsupervised analysis method. This allowed them to automatically draw 4 reproducible vascular habitats (High-angiogenic enhancing tumor; Low-angiogenic enhancing tumor; Potentially tumor infiltrated peripheral edema; Vasogenic peripheral edema) which enable to describe the tumor vascular heterogeneity robustly. In other studies, contrast-enhancing mass can divided into spatial habitats by K-means clustering of voxel-wise apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) values to observe the changes of voxels in spatial habitat on the time line. Using this so-called spatiotemporal habitat to identify progression or pseudoprogression in cancer therapy. Above all, we have sufficient and firm reasons to deem that habitat imaging based on multiparametric MRI is more conducive to reflect the potential biological information inside the tumor and realize individualized diagnosis and treatment. To sum up, the assumption of this experiment is that the Habitats Created by preoperative or postoperative Multiparametric MRI ,such as conventional MRI sequences, Dynamic Susceptibility Weighted Contrast Enhanced Magnetic Resonance Imaging (DSC-MRI), Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI), Diffusion Weighted Magnetic Resonance Imaging(DWI) ,Vessel Size Imaging (VSI) ,or Magnetic Resonance Spectroscopy (MRS) can predict the molecular mutation status, prognosis, treatment residence, progression, pseudoprogression, and even recurrence and distant intracranial recurrence in patients with high-grade gliomas.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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