MRI is the best way to detect breast cancer in patients with dense breasts and a negative mammogram

According to a meta-analysis published in Radiology.

Researchers found that breast MRI detected more cancers than other supplemental imaging modalities.

The researchers assessed data from 22 studies involving 261,233 patients, and 120,081 of those patients had dense breasts and negative mammograms.

Continue reading

The researchers examined the cancer detection rate, the positive predictive value of recall, and the positive predictive value of biopsies performed for 4 additional imaging modalities in patients with dense breasts and a negative mammogram result. The imaging modalities evaluated were breast MRI, portable breast ultrasound, automated breast ultrasound and digital breast tomosynthesis.

Breast MRI had a significantly higher additional cancer detection rate per 1000 screens (1.54; 95% CI 0.74 to 2.33; P < 0.001), compared with portable breast ultrasound (-0.35; 95% CI, -0.77 to 0.08; P = 0.11), automated whole breast ultrasound (-0.26; 95% CI, -1.07 to 0.56; P = 0.53) and digital breast tomosynthesis (-0.14; 95% CI, -0.58 to 0.29; P = 0.51).

MRI also showed a numerically higher positive predictive value of recall and a positive predictive value of biopsies performed, compared to the other imaging modalities, but these results were not statistically significant.

The positive predictive value of recall was 27.7 for MRI, 18.2 for portable breast ultrasound, and 17.4 for automated breast ultrasound. The positive predictive value of the biopsies performed was 34.3 for MRI, 9.1 for portable breast ultrasound and 22.8 for automated breast ultrasound.

“The pooled data showed that MRI was the best additional imaging modality in women at average or intermediate risk for breast cancer with dense breasts and a cancer-negative mammogram,” the researchers concluded.

Reference

Hussein H, Abbas E, Keshavarzi S, et al. Additional screening for breast cancer in women with dense breasts and negative mammograms: a systematic review and meta-analysis. Radiology. Posted January 31, 2023. doi:10.1148/radiol.221785