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.
Age range
18 Years
Sex
ALL
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Multi-model habitats constructed by multiparametric MRI predict IDH mutation status and the prognosis in high-grade gliomas
Timeframe: From the date of operation until the date of death from any cause,assessed up to 120 months