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Development and Validation of an AI Foundation Model for CNS Tumor Classification

NCT07685301 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 20000

Last updated 2026-07-06

No results posted yet for this study

Summary

This is a multi-center, retrospective, observational study to develop and internally validate an artificial intelligence (AI) foundation model for hierarchical classification of central nervous system (CNS) tumors using approximately 20,000 hematoxylin and eosin (H\&E) whole-slide images (WSIs) collected at Huashan Hospital Fudan University and Shandong Provincial Hospital. Archived pathology slides and linked de-identified clinical, histopathological, and molecular diagnostic data from patients who underwent neurosurgical tumor resection or biopsy between January 1, 2010 and December 31, 2025 will be retrospectively analyzed.

The study aims to train and evaluate weakly supervised multiple-instance learning models using pathology foundation models and conventional convolutional neural network feature extractors to predict tumor category, tumor family, terminal WHO 2021 CNS tumor diagnosis, and selected molecular alterations directly from routine H\&E slides. Internal model validation will be performed using patient-level training, validation, and hold-out test datasets. Secondary analyses include comparison of model architectures, virtual molecular profiling, interpretability analyses using attention heatmaps, and comparison of AI-assisted versus pathologist-only diagnostic performance on selected internal test cases.

Conditions

Sponsors & Collaborators

  • Shandong Provincial Hospital

    collaborator OTHER_GOV

  • Huashan Hospital

    lead OTHER

Eligibility

Min Age
9 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-08-01
Primary Completion
2027-07-30
Completion
2029-07-30

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07685301 on ClinicalTrials.gov