NCT06703112Not yet recruiting
Establishment and Clinical Application of AI-based Multimodal Diagnosis System for Ovarian Tumors
Source: ClinicalTrials.gov · Last updated 25 Nov 2024 · Not updated for over 12 months - ask the site whether it is still open
Brief summary (registry, in English)
Ovarian tumors are a common disease that threatens women's health. They are insidious in onset, have over ten pathological types, and exhibit diverse biological behaviors, making accurate diagnosis a key factor in clinical decision-making and improving prognosis. Introducing AI technology to establish an auxiliary diagnosis system composed of multi-dimensional clinical data, including medical imaging and tumor markers, will greatly enhance diagnosis efficiency by predicting the pathological types of common ovarian tumors. Our research group has innovatively developed an AI-based ultrasound intelligent auxiliary diagnosis software for ovarian tumors, which has been clinically validated to be effective. This project will build on this by: (1) utilizing a wealth of multi-center retrospective clinical data to combine ultrasound, MRI images, physiological, pathological, and laboratory data to form the first multi-modal ovarian tumor public dataset supporting AI tasks; (2) using convolutional neural network technology to realize multi-modal image multi-classification intelligent recognition on this dataset based on surgical pathology as the standard, and then fuse features at the level of clinical data with the intelligent recognition model to train and validate an auxiliary diagnosis model for predicting the top ten pathological types of ovarian tumors; (3) applying privacy computing and federated learning methods to conduct multi-center, prospective validation and optimization of the above model, ultimately forming a clinical auxiliary diagnosis system that can predict the pathological types of most ovarian tumors and apply it to clinical practice.
- Status (registry)
- Not yet recruiting
- Study type
- Interventional
- Enrollment
- 584 (estimated)
- First submitted
- 17 Nov 2024
- Start date
- 1 Jun 2025
- Primary completion date
- 31 Dec 2026
- Lead sponsor
- Beijing Shijitan Hospital, Capital Medical University
- Diseases
- Ovarian cancer, Childhood cancers
- NCT number
- NCT06703112
What you commit to
- Study type: Interventional
- Planned participants: 584
- From 1 Jun 2025 to the primary completion date, 31 Dec 2026
- No sites listed in no country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- 1\. Patients with non-ovarian origin tumor as surgical pathology;
- 3\. Cases receiving radiotherapy and chemotherapy;
Other
- 2\. Repetitive cases;
- 4\. Recurrent cases; 5. Poor image quality of ovarian lesions;
Who the study is looking for
- 1\. Continuous cases admitted for diagnosis of ovarian tumor and preparation for surgical treatment;
- 2\. Complete imaging data (ultrasound or MRI) and tumor marker results within 3 months before surgery;
- 3\. Voluntarily sign informed consent.
Sex: Female · Does not accept healthy volunteers
This page is information, not medical advice. Discuss any trial with your doctor.