Feature | May 30, 2013

First Large-Scale U.S. Study Validates the Benefits of 3-D Mammography

Houston-based researchers document the value of 3-D mammography as a breast cancer screening technology.

First Large-Scale U.S. Study Validates the Benefits of 3-D Mammography

May 30, 2013 — A recently published clinical study conducted at TOPS Comprehensive Breast Center in Houston, Texas, demonstrates that 3-D mammography (breast tomosynthesis) significantly reduces unnecessary recalls while simultaneously increasing cancer detection.

The study, "Implementation of Breast Tomosynthesis in a Routine Screening Practice: An Observational Study," was led by Stephen L. Rose, M.D., and published in the June issue of the American Journal of Roentgenology (AJR). 

The study examined the use of Hologic's 3-D mammography in conjunction with 2-D mammography. The researchers found that 3-D mammography:

  • Reduced recall rates by 37 percent;
  • Increased the detection of cancers by over 30 percent; and
  • Increased the detection of invasive cancers by more than 50 percent.

 

Instead of viewing all the complexities of the breast tissue in a flat image as with a traditional mammogram, 3-D mammography uses multiple low-dose images to create a 3-D view of the breast. 3-D mammography allows the doctor to examine 3-D breast images layer-by-layer.

The 2010 through 2012 study population included 13,856 women who received conventional 2-D mammography screening exams prior to the introduction of Hologic's 3-D mammography technology (breast tomosynthesis) and 9,499 women who received a 3-D mammography screening exam. Images in both time periods were interpreted by six radiologists with an average 12 years of reading experience.  

"We are finding cancerous breast tumors as small as two to three millimeters," Rose said. "We are finding cancer earlier and this will allow us to reduce the amount of treatment patients need."  Rose projects that as 3-D mammography becomes the standard breast cancer screening tool the size of tumors found will get smaller, and accuracy of deciding between benign and cancerous tumors will improve.

    For more information: www.breasttomo.com

 

Related Content

In a demonstration on the exhibit floor of the SBI symposium, Koios software identified suspicious lesions in ultrasound images

In a demonstration on the exhibit floor of the SBI symposium, Koios software identified suspicious lesions in ultrasound images. Photo by Greg Freiherr

Feature | Artificial Intelligence | April 19, 2019 | By Greg Freiherr
Commercial efforts to develop...
Videos | Breast Imaging | April 18, 2019
In a keynote lecture at the Society of Breast Imaging (SBI)/American College of Radiology (ACR) 2019 Symposium, ...
Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer

Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer. Permission to publish provided by DenseBreast-info.org

Feature | Breast Imaging | April 18, 2019 | By Greg Freiherr
When planning a screening program to detect the early signs of breast cancer, age is a major consideration.
iCAD Appoints Stacey Stevens as President
News | Radiology Business | April 16, 2019
iCAD Inc. recently announced that Stacey Stevens has been named president. As president, Stevens will have expanded...
compressed breast during mammography.
360 Photos | 360 View Photos | April 16, 2019
A 360 view of a simulated breast compression for a...
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images

A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Artificial Intelligence | April 12, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
This image depicts ABUS images with QVCAD results

This image depicts ABUS images with QVCAD results.

Feature | Breast Imaging | April 12, 2019
Imaging Technology News spoke with Bob Foley, vice president of sales and marketing of QView Medical, Inc.,
Uterine Fibroid Embolization Safer and as Effective as Surgical Treatment
News | Interventional Radiology | April 05, 2019
Uterine fibroid embolization (UFE) effectively treats uterine fibroids with fewer post-procedure complications compared...