Clinical Trial Finder

Inclusion Criteria (if we will predict the molecular status and overall survival):

• - the patient was over 18 years old.

• - the lesion was located in the supratentorial space; - a histopathologic diagnosis of HGGs according to the WHO CNS4/5; - all subjects were the first diagnosed cases without any invasive or non-invasive treatment; - access to the complete preoperative MR imaging examinations, at least including four conventional sequences.

Inclusion Criteria (if we will differentiate recurrence from distant intracranial recurrence):

• - the patient was over 18 years old; - the lesion was located in the supratentorial space; - a histopathologic diagnosis of HGGs according to the WHO CNS4/5; - underwent concurrent chemoradiotherapy with temozolomide after surgical resection or biopsy; - underwent preoperative and postoperative MRI, at least including four conventional sequences; - had newly appeared or enlarging, measurable, contrast-enhancing mass which raises clinical suspicion of tumor recurrence and distant intracranial recurrence; - adequate follow-up examinations to determine treatment response on clinic-radiological consensus or pathologic confirmation.

Exclusion Criteria:

• - patient with other brain tumors or other grade gliomas at the same time; - patient with severe basic diseases at the same time; - patient with a survival time of less than 30 days, which can be caused by severe surgical trauma stress; - poor image quality and heavy artifact affect the subsequent image processing.

This is a single center experiment. The subjects of this study were patients diagnosed as high-grade glioma by multiparametric magnetic resonance imaging and pathological biopsy from January 1, 2008 to December 31, 2021(or at some interval within this period). Patients meeting the inclusion criteria will enter the next experimental stage. 1. Patients selection: The patients will be clustered according to the preoperative and postoperative examination methods performed by each patient, such as only DSC sequence, both DSC and DWI sequences, or a full set of functional imaging sequences at the same time; 2. Images segmentation: To select the patients who meet the experimental design, and use deep learning-based biomedical image segmentation methods, such as Brain Tumor Segmentation (BraTS) challenge, to segment more accurate and reproducible habitats as much as possible; 3. Construction of clinical model: We may be able to obtain the parameter values of the habitat, such as CBV, ADC, Ktrans, etc. Combining these data with the basic situation of patients can build a clinical model. 4. Construction of radiomics model: The radiomics analysis will probably be structured into four parts: habitats segmentation, feature extraction, feature selection and model construction. 5. We try to analyze that habitat imaging based on Multiparametric MRI is indeed better than the conventional rough and simple ROI analysis; We try to analyze the relation between the habitats and the IDH mutation status or MGMT promoter methylation status; We try to analyze the relation between the habitats and the overall survival (OS) of the patient; We try to analyze the habitats is conducive to differentiate recurrence from distant intracranial recurrence. Finally, statistical methods and survival analysis were used to determine whether the habitat was statistically significant for IDH mutation status and prognosis. For example, receiver operating characteristic curve (ROC) analysis evaluated the potential of the spatial habitats in IDH mutation prediction. The Kaplan-Meier curve evaluates the validation of the diagnosis in OS prediction in high-grade glioma.