Role of 3D Tomography in Breast Cancer
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Breast Cancer
- Sponsor
- University of Rochester
- Enrollment
- 150
- Locations
- 1
- Primary Endpoint
- Correlation between mammography and breast CT on lesion detection
- Status
- Completed
- Last Updated
- 12 years ago
Overview
Brief Summary
The primary aim of this pilot study is to define the role of dedicated cone beam breast computed tomography in breast cancer imaging. This research is a prelude of a more comprehensive clinical trial that may follow.
Investigators
Eligibility Criteria
Inclusion Criteria
- •All women, age 40 or older, who are scheduled for biopsy after classification as BI-RADS 4/5 and have had a screening or diagnostic full-field digital mammography (FFDM) exam are eligible to participate, except for exclusions noted below.
- •Able to provide informed consent.
Exclusion Criteria
- •Women less than 40 years old
- •Pregnant women
- •Lactating women
- •Woman who have had bilateral mastectomies
- •Women with physical limitations that may prohibit resting prone on the exam table, such as, but not limited to: frozen shoulder, recent heart surgery, pace maker
- •Women who are unable to tolerate study constraints, frail or unable to cooperate
- •Women with large breasts that cannot be accommodated within the field of view of the CT system
- •Women who have received radiation treatments to the thorax for malignant and nonmalignant conditions, such as (but not limited to)
- •Treatment for enlarged thymus gland as an infant
- •Irradiation for benign breast conditions, including breast inflammation after giving birth
Outcomes
Primary Outcomes
Correlation between mammography and breast CT on lesion detection
Time Frame: 2 years
There are two specific aims of this pilot study. One specific aim is to determine if the lesions that are detected by mammography and referred for biopsy, are visible with breast CT. The other specific aim is to determine if there is a correlation between CT numbers and malignancy, in particular for soft tissue (solid masses) abnormalities and to determine if image processing techniques improve correlation between CT numbers and malignancy.