Digital Mammography: Computer-Aided Breast Cancer Diagnosis

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT00732433
Recruitment Status : Active, not recruiting
First Posted : August 12, 2008
Last Update Posted : September 7, 2017
Information provided by (Responsible Party):
Heang-Ping Chan Ph.D, University of Michigan

Brief Summary:
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.

Condition or disease Intervention/treatment Phase
Tumors, Breast Procedure: digital mammography Not Applicable

Detailed 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.

Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 500 participants
Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Diagnostic
Official Title: Digital Mammography: Computer-Aided Breast Cancer Diagnosis
Study Start Date : June 2000
Estimated Primary Completion Date : January 2020
Estimated Study Completion Date : January 2020

Resource links provided by the National Library of Medicine

U.S. FDA Resources

Arm Intervention/treatment
Experimental: digital mammogram

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.

Procedure: digital mammography
Using non-invasive digital mammography with computer aided programs to screen, detect and characterize breast lesions/cancer.

Primary Outcome Measures :
  1. 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. ]

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

Ages Eligible for Study:   18 Years to 80 Years   (Adult, Senior)
Sexes Eligible for Study:   Female
Accepts Healthy Volunteers:   No

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT00732433

United States, Michigan
University of Michigan Health System
Ann Arbor, Michigan, United States, 48109
Sponsors and Collaborators
University of Michigan
Principal Investigator: Heang-Ping Chan, Ph.D. University of Michigan

Responsible Party: Heang-Ping Chan Ph.D, Principal Investigator, University of Michigan Identifier: NCT00732433     History of Changes
Other Study ID Numbers: 2000-0227
First Posted: August 12, 2008    Key Record Dates
Last Update Posted: September 7, 2017
Last Verified: September 2017

Additional relevant MeSH terms:
Breast Neoplasms
Neoplasms by Site
Breast Diseases
Skin Diseases