Breast MRI found to be superior for detecting breast cancer in women with dense breasts

According to a study published in Radiologya journal of the Radiological Society of North America (RSNA).

Breast cancer is one of the leading causes of cancer death in women. Approximately 47% of women in the United States have dense breasts, which is an independent risk factor for breast cancer. Women with dense breasts have increased amounts of glandular tissue and fibrous connective tissue and low amounts of fatty breast tissue.

While screening mammography effectively detects up to 98% of cancer in fatty breasts, breast cancer is more easily missed in dense breasts. This results in a negative mammogram, giving patients false reassurance.

Breast cancer masses appear white on a mammogram, and dense tissue also appears white, making it more difficult for radiologists to find breast cancers within dense breast tissue.”

Vivianne Freitas, MD, M.Sc., study co-author, assistant professor at the University of Toronto, Canada, and radiologist in the Joint Department of Medical Imaging in Toronto

An additional test may be required to help detect cancer in women with dense breasts. The four most common complementary imaging tests are manual breast ultrasound, automated breast ultrasound, digital breast tomosynthesis, and breast MRI.

“Our study was designed to evaluate the role of different adjunctive screening tests in women at average or intermediate risk of breast cancer with dense breast tissue who had a negative screening mammogram,” said Dr. Freitas.

To gauge which screening method was most beneficial for women with dense breasts, the researchers conducted a meta-analysis of 22 studies that included 261,233 patients screened for breast cancer. Ten of the studies covered manual breast ultrasound, four studies covered automated breast ultrasound, three studies covered breast MRI, and eight studies reported digital breast tomosynthesis. Of the included patients, 132,166 patients had dense breasts and a negative mammogram.

Risk assessment models have been used to identify patients at medium and intermediate risk of developing breast cancer. In the United States, women with an estimated 12-13% lifetime risk of developing breast cancer are considered average risk. Factors that raise risk to intermediate include having a history of treated breast cancer or previous breast biopsies with high-risk lesions. High-risk patients, with a lifetime risk of 20% or greater, were excluded from the study because the benefit of breast MRI is already established in high-risk populations.

The meta-analysis showed that of the 132,166 patients with dense breasts, a total of 541 breast cancers not initially detected on mammography were detected with adjunctive screening methods. Breast MRI was the superior detection method and was able to detect even the smallest cancer. Excluding MRI, there was no significant difference between the other adjunctive detection methods.

“MRI is far superior in terms of cancer detection compared to manual ultrasound, automated ultrasound, and digital breast tomosynthesis,” said Dr. Freitas. “Our results on the role of MRI in adjunctive screening will allow stakeholders to guide healthcare policy in this setting and direct further research.”

While the results demonstrate the efficacy of breast MRI in detecting cancer, more research is needed.

“Before we can advocate for a broader application of breast MRI in these women, further evaluation of the cost-effectiveness of breast MRI compared to other techniques, the effect on mortality reduction , etc,” said Dr. Freitas. “Currently, the availability and cost of breast MRI remain the biggest barrier to widespread implementation.”

“Adjunctive screening for breast cancer in women with dense breasts and negative mammography: a systematic review and meta-analysis”. They collaborated with Dr. Freitas Heba Hussein, MD, Ph.D., Engy Abbas, MD, Sareh Keshavarsi, Ph.D., Rouhi Fazelzad, MD, Karina Bukhanov, MD, Supriya Kulkarni, MD, Frederick Au, MD, Sandeep Ghai, MD, and Abdullah Alabousi, MD