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

According to a study published in , breast MRI was superior in detecting breast cancer in women with dense breasts compared to other common supplemental screening methods. RadiologyJournal 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 a higher amount of glandular and fibrous connective tissue and a lower amount of adipose tissue in their breasts.

Screening mammography is effective in detecting up to 98% of cancers in fatty breasts, but breast cancers in dense breasts are more likely to be missed. This results in a negative mammogram and gives the patient a false sense of security.

Breast cancer masses appear white on mammograms, and dense tissue also appears white, making it difficult for radiologists to detect breast cancer within dense breast tissue.”

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

Women with dense breasts may need additional screening to help detect cancer. Her four most common supplemental imaging tests are handheld breast ultrasound, automated breast ultrasound, digital breast tomosynthesis, and breast MRI.

“Our study was designed to assess the role of different supplemental screening tests in women with negative screening mammograms and dense breast tissue at average or intermediate breast cancer risk,” Dr. Freitas said. said.

To determine which screening modalities were most beneficial for women with dense breasts, researchers performed a meta-analysis of 22 studies involving 261,233 patients screened for breast cancer. Ten studies reported on handheld breast ultrasound, four on automated breast ultrasound, three on breast MRI, and eight on digital breast tomosynthesis. Of the included patients, 132,166 patients had dense breasts and negative mammograms.

Risk assessment models have been used to identify patients at average and intermediate risk of developing breast cancer. In the United States, a woman whose lifetime risk of developing breast cancer is estimated at 12-13% of hers is considered average risk. Moderately increasing risk factors include prior breast cancer treatment and previous breast biopsies with high-risk lesions. High-risk patients with a lifetime risk of ≥20% were excluded from the study. This is because the benefits of breast MRI have already been established in high-risk populations.

A meta-analysis showed that among 132,166 patients with dense breast, a total of 541 breast cancers initially missed by mammography were detected by complementary screening modalities. Breast MRI was an excellent screening method and was able to detect even the smallest cancers. Except for MRI, there were no significant differences between other complementary screening modalities.

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

This result demonstrates the efficacy of breast MRI in cancer detection, but further research is needed.

“We need to further evaluate the cost-effectiveness, mortality reduction, etc. of breast MRI compared to other techniques before advocating broader application of breast MRI in these women,” Dr. Freitas said. Stated. “To date, the availability and cost of breast MRI remain the biggest barriers to widespread implementation.”

“Supplemental Breast Cancer Screening in Women with Dense Breasts and Negative Mammography: A Systematic Review and Meta-Analysis.” Dr. Freitas collaborated with Heba Hussein, MD, Engie Abbas, MD, Saleh Keshavarsi, Ph.D., and Rohi Fazerzad. M.D., Karina Bukhanov, M.D., Supriya Kulkarni, M.D., Frederik Au, M.D., and Dr. Sandeep. Ghai, MD, and Abdullah Alabousi, MD