AI-assisted Diagnosis of Malignant Brain Tumors

NCT07198256 | Recruiting

• 1 other identifier: 2023-1050
• Study Type: observational
• Target: 3,000
• Locations: 1 country
• Sites: 2

Brief Summary

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.

Conditions

Gliomas; Brain Metastases, Adult; Lymphoma; Brain Tumor Adult

Keywords

brain tumor; glioma; brain metastases; lymphoma; magnetic resonance imaging; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• 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.

  30 days

Study Arms (1)

malignant brain tumors

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

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study 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.

You may qualify if:

• Patients diagnosed with glioma, brain metastases, and brain lymphoma by pathology, with the patient being at least 18 years old; preoperative MRI was complete.

You may not qualify if:

• Poor image quality; history of previous brain surgery or radiotherapy; accompanied by other intracranial lesions.

Sponsors & Collaborators

• Second Affiliated Hospital, School of Medicine, Zhejiang University: lead
• Zhejiang Cancer Hospital: collaborator

Study Sites (2)

2nd Affiliated Hospital, School of Medicine, Zhejiang University

Hangzhou, Zhejiang, 310009, China

RECRUITING

Zhejiang Cancer Hospital

Hangzhou, Zhejiang, 310022, China

NOT YET RECRUITING

MeSH Terms

Conditions

Glioma; Brain Neoplasms; Lymphoma

Condition Hierarchy (Ancestors)

Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Nerve Tissue; Central Nervous System Neoplasms; Nervous System Neoplasms; Neoplasms by Site; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Lymphoproliferative Disorders; Lymphatic Diseases; Hemic and Lymphatic Diseases; Immunoproliferative Disorders; Immune System Diseases

Central Study Contacts

Chao Wang, MD

CONTACT

8613706518691; wangchaosmart@zju.edu.cn

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 22, 2025
• First Posted: September 30, 2025
• Study Start: September 1, 2025
• Primary Completion: December 31, 2025
• Study Completion (Estimated): December 31, 2028
• Last Updated: September 30, 2025

Record last verified: 2025-09

Locations

CN (2)