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Research on the application value of non-invasive rapid tumor early screening based on imaging artificial intelligence

Research on the application value of non-invasive rapid tumor early screening based on imaging artificial intelligence

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400080300
Enrollment
Unknown
Registered
2024-01-25
Start date
2024-02-01
Completion date
Unknown
Last updated
2024-01-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cancer of the liver, breast and thyroid

Interventions

Observation group:a. Two-dimensional ultrasound, color Doppler, contrast-enhanced ultrasound and liver elasticity were performed, raw data were collected, and quantitative analysis was performed offli
b. Qualitative diagnosis: size, shape, echo/density/signal, number, etc., of liver, breast and thyroid lesions
The enhancement pattern and morphology of contrast-enhanced ultrasound
Elastic hardness value and so on. c. Multimodal image feature analysis of liver, breast and thyroid lesions
d. Collecting biopsy and postoperative pathological results of liver, breast and thyroid lesions
e. To analyze the accuracy of multimodal imaging in the diagnosis and treatment of liver, breast and thyroid lesions
f. Perform deep learning analysis to select the best diagnosis and treatment method.

Sponsors

The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: A. Age >18 years; B. Have imaging, examination and pathological data of liver, thyroid and breast space; C. Patients signed written informed consent for contrast ultrasound

Exclusion criteria

Exclusion criteria: A. The pathological or clinical diagnosis is not clear; B. Imaging data missing or incomplete;

Design outcomes

Primary

MeasureTime frame
sensitivity;specificity;accuracy;

Secondary

MeasureTime frame
positive predictive value;negavtive predictive value;

Countries

China

Contacts

Public ContactWei Wang

The First Affiliated Hospital of Sun Yat-Sen University

wangw73@mail.sysu.edu.cn+86 20 8776 5183

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026