Artificial Intelligence in Mammography-Based Breast Cancer Screening
Keywords
Abstract
Dates
Last Verified: | 06/30/2020 |
First Submitted: | 11/05/2019 |
Estimated Enrollment Submitted: | 11/05/2019 |
First Posted: | 11/07/2019 |
Last Update Submitted: | 07/13/2020 |
Last Update Posted: | 07/15/2020 |
Actual Study Start Date: | 07/31/2020 |
Estimated Primary Completion Date: | 11/30/2023 |
Estimated Study Completion Date: | 05/31/2024 |
Condition or disease
Intervention/treatment
Other: mammography
Phase
Eligibility Criteria
Sexes Eligible for Study | Female |
Sampling method | Probability Sample |
Accepts Healthy Volunteers | Yes |
Criteria | Inclusion Criteria: - Women who had undergone standard mammography including craniocaudal (CC) and mediolateral oblique (MLO) views.. - Histopathology-proven diagnosis is available for patients with breast malignancy, including invasive breast cancer, carcinoma in situ, and borderline lesion et al. - As reference standard of benign nature, results from pathology or clinical long-term follow-up (>=2 years) examinations are available for cases without breast malignancy. Exclusion Criteria: - Patients with concurring lesions on mammograms that may influence subsequent AI post-process. - Patients without available pathologic diagnosis or long-term follow-up (>=2 years) examinations. - Patients who had undergone breast surgical intervention (e.g. lumpectomy and mammoplasty) prior to first mammography. - Patients diagnosed with other kinds of malignancy, concurrent with metastasis or infiltration/invasion to breast. |
Outcome
Primary Outcome Measures
1. area under curve (AUC) [3 years]
2. accuracy [3 years]
3. sensitivity [3 years]
4. specificity [3 years]