Clinical Research Directory

Combing a Deep Learning-Based Radiomics With Liquid Biopsy for Preoperative and Non-invasive Diagnosis of Glioma

Sponsor: Second Affiliated Hospital of Nanchang University

Summary

This registry has the following objectives. First, according to the guidance of 2021 WHO of CNS classification, we constructed and externally tested a multi-task DL model for simultaneous diagnosis of tumor segmentation, glioma classification and more extensive molecular subtype, including IDH mutation, ATRX deletion status, 1p19q co-deletion, TERT gene mutation status, etc. Second, based on the same ultimate purpose of liquid biopsy and radiomics, we innovatively put forward the concept and idea of combining radiomics and liquid biopsy technology to improve the diagnosis of glioma. And through our study, it will provide some clinical validation for this concept, hoping to supply some new ideas for subsequent research and supporting clinical decision-making.

Official title: Combing a Deep Learning-Based MRI Multimodal Radiomics Method With Liquid Biopsy Technique for Preoperative and Non-invasive Diagnosis of Glioma Grading and Molecular Subtype

Key Details

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Interventions

Locations (2)