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Digital Mammography: Computer-Aided Breast Cancer Diagnosis

This study is ongoing, but not recruiting participants.
Sponsor:
Information provided by (Responsible Party):
Heang-Ping Chan Ph.D, University of Michigan
ClinicalTrials.gov Identifier:
NCT00732433
First received: August 7, 2008
Last updated: June 12, 2012
Last verified: June 2012
History of Changes
  Purpose

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 Intervention
Breast Cancer
Breast Abnormalities
 Procedure: digital mammography

Study Type: Interventional
Study Design: Allocation: Non-Randomized
Intervention Model: Single Group Assignment
Masking: Open Label
Primary Purpose: Diagnostic
Official Title: Digital Mammography: Computer-Aided Breast Cancer Diagnosis

Resource links provided by NLM:

U.S. FDA Resources

Further study details as provided by University of Michigan:

Primary Outcome Measures:
  • 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. ] [ Designated as safety issue: No ]

Estimated Enrollment: 500
Study Start Date: June 2000
Estimated Study Completion Date: August 2015
Estimated Primary Completion Date: August 2015 (Final data collection date for primary outcome measure)
Arms Assigned Interventions
Experimental: A. Procedure: digital mammography
Using non-invasive digital mammography with computer aided programs to screen, detect and characterize breast lesions/cancer.

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.

  Eligibility

Ages Eligible for Study:   18 Years to 80 Years
Genders Eligible for Study:   Female
Accepts Healthy Volunteers:   No
Criteria

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
  Contacts and Locations
Please refer to this study by its ClinicalTrials.gov identifier: NCT00732433

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

No publications provided

Responsible Party: Heang-Ping Chan Ph.D, Principal Investigator, University of Michigan
ClinicalTrials.gov Identifier: NCT00732433     History of Changes
Other Study ID Numbers: 2000-0227, NIH (CA 95153)
Study First Received: August 7, 2008
Last Updated: June 12, 2012
Health Authority: United States: Institutional Review Board

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

ClinicalTrials.gov processed this record on May 21, 2013