MRI-based Computer Aided Diagnosis Software (V1) for Glioma

The goal of this multi-center clinical trial is to evaluate the effectiveness of MRI-based computer-aided diagnosis software (V1) for glioma segmentation, gene prediction, and tumor grading. Machine learning methods such as high-precision tumor segmentation and classification and discrimination modeling can further optimize the non-invasive molecular diagnosis and prognosis prediction. The main question it aims to answer is whether the software can predict the molecular type and the prognosis quickly and correctly. The results will be compared with the real-world clinical data double-blindly. Finally, form a set of user-friendly automatic glioma diagnosis and treatment systems for clinics.

Inclusion Criteria:Age front 18 to 70 years old (not including threshold), gender is not limited;Preliminary diagnosis of glioma patients and patients who plan to undergo surgical treatment;Preoperative cranial MRI (T1, T2, T2 Flair, T1 enhanced GE company magnetic resonance package), tumor pathological examination (H&E section, Kuoran Gene Company package), acceptable follow-up and brain MRI scan;The patient himself voluntarily participated and signed the informed consent in writing.Exclusion Criteria:Patients who only underwent biopsy rather than surgical tumor resection;Postoperative pathologically confirmed non-glioma patients;Patients with multiple glioma metastases or multiple gliomas;Patients who died of complications in the early postoperative period;The researcher believes that this researcher should not be included.