This trial is active, not recruiting.

Condition tumors, breast
Treatment digital mammography
Sponsor University of Michigan
Start date June 2000
End date September 2015
Trial size 500 participants
Trial identifier NCT00732433, 2000-0227


The purpose of this study is to develop computer programs to assist radiologists in finding breast cancer on mammograms and to compare the computer's accuracy of detecting cancers on direct digital and film mammograms.

United States No locations recruiting
Other countries No locations recruiting

Study Design

Intervention model single group assignment
Masking open label
Primary purpose diagnostic
Digital mammography is a non-invasive imaging technique to obtain an x-ray image of the breast. Two-view digital mammogram of the breast with a lesion that has been recommended for biopsy during the subject's regular clinical care. The digital mammogram is then analyzed by a computer program.
digital mammography
Using non-invasive digital mammography with computer aided programs to screen, detect and characterize breast lesions/cancer.

Primary Outcomes

Using computer aided programs to assist in detection and characterization of breast lesions in digital mammography.
time frame: Research scan will be completed at the time of scheduled clinical visit.

Eligibility Criteria

Female participants from 18 years up to 80 years old.

Inclusion Criteria: - Females who have been scheduled for mammographic exams. - Females who have been recommended for work-up or biopsy due to a suspicious finding on their mammogram. - Females who can give informed consent. Exclusion Criteria: - No subject under 18 years of age

Additional Information

Official title Digital Mammography: Computer-Aided Breast Cancer Diagnosis
Principal investigator Heang-Ping Chan, Ph.D.
Description To develop a computer-aided diagnosis (CAD) system for full field digital mammography (FFDM) using advanced computer vision techniques and to evaluate the effects of CAD on interpretation of digital mammograms (DMs). This system will assist radiologists with the four most important areas in mammographic interpretation: (1) detection of masses, (2) classification of masses, (3) detection of microcalcifications, (4) classification of microcalcifications. The proposed approach is distinctly different from previous approaches in that image information from two-view and bilateral mammograms will be fused with that from the single-view mammogram to improve lesion detection and characterization.
Trial information was received from ClinicalTrials.gov and was last updated in June 2015.
Information provided to ClinicalTrials.gov by University of Michigan.