The Clinical Value of an Artificial Intelligence System Using Abbreviated Protocol of Breast MRI Facilitates Classification of Breast Lessions
1 other identifier
observational
800
1 country
1
Brief Summary
This study aims to use a combination of abbreviated protocol and artificial intelligence to automatically identify lesions and make diagnosis without decreasing the diagnostic accuracy of breast cancer, thus enhancing the comfort of patient examination, accelerating the flow of examination and reducing the load of clinical work.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jul 2023
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
March 31, 2023
CompletedFirst Posted
Study publicly available on registry
June 7, 2023
CompletedStudy Start
First participant enrolled
July 1, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
August 1, 2025
CompletedJune 7, 2023
May 1, 2023
1.8 years
March 31, 2023
May 29, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Comparison between the diagnostic performance of【AP breast MRI + AI】 vs. 【Radiologist】, using the pathological results as golden standard,
Comparison of AUC, sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) between【AP breast MRI + AI】 vs. 【Radiologist】, using the pathological results as golden standard,
2 years
Secondary Outcomes (2)
Comparison of the scan time of abbreviated and full protocol
2 years
Comparison of the interpretation time of abbreviated and full protocol
2 years
Eligibility Criteria
The statistical analyses in this study were all descriptive, without any predefined hypotheses. Referring to a recent study\* of artificial intelligence combined with abbreviated protocol MRI to classify benign and malignant non-mass-enhancing lesions in the breast\*, a sample size of 800 cases was taken, which would require 800 patients to be enrolled, based on at least one lesion at the initial consultation of one patient.
You may qualify if:
- Patients with breast lesions detected by ultrasound and mammography that cannot be characterized
- Patients who were consecutively included in our hospital for breast MRI without treatment
- Underwent preoperative full-protocol breast MRI
- Pathological results are available, of which benign lesions can be determined by follow-up
You may not qualify if:
- Poor MRI image quality
- Patients who have been received the biopsy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Fudan Universitylead
- Bayercollaborator
Study Sites (1)
Fudan university Shanghai Cancer Center
Shanghai, Shanghai Municipality, 200032, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Target Duration
- 1 Day
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Director of Radiology
Study Record Dates
First Submitted
March 31, 2023
First Posted
June 7, 2023
Study Start
July 1, 2023
Primary Completion
May 1, 2025
Study Completion
August 1, 2025
Last Updated
June 7, 2023
Record last verified: 2023-05