NCT05443672

Multi-center Study of Deep Learning AI in Breast Mass

A Multi-center Study of Breast Mass Screening and Diagnosis Using Deep Learning AI-based on Real-time Ultrasound Examination

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,122 (estimated)
• Sponsor: Cancer Institute and Hospital, Chinese Academy of Medical Sciences · Academic / Other
• Sex: Female
• Age: —
• Healthy volunteers: Not accepted

Summary

This multi-center study intends to evaluate the value of the detection and differential diagnosis of breast mass using deep learning AI-based real-time ultrasound examination.

Detailed description

As the most common cancer expected to occur all over the world, extensive population screening plays a very important role in the early diagnosis and prognosis of the breast cancer. X-ray and ultrasound are the most commonly used screening methods, and ultrasound is especially important for Asian women with dense breasts. However, ultrasound is greatly affected by the operator's skill and experience, and the diagnostic accuracy varies greatly. Artificial intelligence (AI) is a new method emerging in recent years, active in many medical fields and can effectively improve the diagnostic efficiency. However, previous researches on the application of AI in ultrasound are focused on single or multi-modality static ultrasound images. This multi-center study intends to evaluate the value of the detection and differential diagnosis of breast mass using deep learning AI-based real-time ultrasound examination.

Conditions

• Breast Neoplasms

Interventions

Type	Name	Description
DEVICE	Yizhun BUSMS	During the breast scanning, Yizhun BUSMS uses different color box to identify the breast lesion, and the box color indicates the risk grade of the lesion.

Timeline

• Start date: 2021-08-12
• Primary completion: 2022-08-31
• Completion: 2023-08-31
• First posted: 2022-07-05
• Last updated: 2022-07-05

Locations

1 site across 1 country: China