About this trial
This study aims to establish a large-scale, multi-center MRI database for malignant brain tumors. It will develop an artificial intelligence system for the segmentation and classification of multiple subtypes of brain tumors (including glioma, metastatic tumor and lymphoma et al.) using deep learning technology. This will address the issues of small sample sizes and limited classification performance in existing methods, thereby improving the accuracy of non-invasive preoperative diagnosis, reducing the need for biopsies, and having significant clinical translational value.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients diagnosed with glioma, brain metastases, and brain lymphoma by pathology, with the patient being at least 18 years old; preoperative MRI was complete.
Disqualifiers
Poor image quality; history of previous brain surgery or radiotherapy; accompanied by other intracranial lesions.
Trial population
Retrospectively collected cases of malignant brain tumors (including gliomas, brain metastases, and brain lymphomas) that were confirmed by histopathology and had preoperative multimodal MRI images (mainly including CE-T1WI and T2-FLAIR) over the past 10 years.
Trial design
Case-control
Retrospective
Treatments tested in this trial
Not listed
Trial groups
Trial outcomes
Primary outcomes
Construct an AI-assisted diagnostic system for multiple subtypes of brain tumors based on deep learning.
Construct an AI-assisted diagnostic system for multiple subtypes of brain tumors based on deep learning, mainly including glioma, metastatic tumor and lymphoma.
Sponsors and contacts
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Second Affiliated Hospital, School of Medicine, Zhejiang University
Lead sponsor
Zhejiang Cancer Hospital
Collaborator