Screening performance with MR imaging and mammography depends on breast cancer risk category.
Screening performance in breast screening is dependent on risk category, according to a study published in the journal, Radiology.
Researchers from the Netherlands evaluated the real-life performance of a breast cancer screening program for women with different categories of increased breast cancer risk with multiple follow-up rounds, from Jan. 1, 2003, to Jan. 1, 2014.
The researchers evaluated screening MR imaging and mammography for women who had an increased risk of breast cancer. Risk category, age, recall for workup of screening-detected abnormalities, biopsy, and histopathologic diagnosis were recorded. Recall rate, biopsy rate, positive predictive value of recall, positive predictive value of biopsy, cancer detection rate, sensitivity, and specificity were calculated for first and follow-up rounds.
The results provided 8,818 MR and 6,245 mammographic examinations performed in 2,463 women. There were 170 documented cancers among the examinations and of these, there were 129 screening-detected cancers, 16 interval cancers, and 25 cancers discovered at prophylactic mastectomy. The researchers noted that the overall sensitivity including cancers discovered at mastectomy was 75.9 percent, while it was 90 percent if those cancers were excluded.
For carriers of the BRCA1 mutation, the sensitivity for was lowest at 66.1 percent when including cancers in prophylactic mastectomy specimens and 81.3 percent when not including these cancers. Specificity was higher at follow-up, at 96.5 percent than it was in first rounds, when it was 85.1 percent. Specificity was high for both MR imaging, at 97.1 percent and mammography, at 98.7 percent. Positive predictive value of recall and positive predictive value of biopsy were lowest in women who had only a family history of breast cancer.
The researchers concluded that screening performance was dependent on risk category, with sensitivity lowest in carriers of the BRCA1 mutation. They noted that the specificity of high-risk breast screening improved at follow-up rounds.
Emerging AI Algorithm Shows Promise for Abbreviated Breast MRI in Multicenter Study
April 25th 2025An artificial intelligence algorithm for dynamic contrast-enhanced breast MRI offered a 93.9 percent AUC for breast cancer detection, and a 92.3 percent sensitivity in BI-RADS 3 cases, according to new research presented at the Society for Breast Imaging (SBI) conference.
Could AI-Powered Abbreviated MRI Reinvent Detection for Structural Abnormalities of the Knee?
April 24th 2025Employing deep learning image reconstruction, parallel imaging and multi-slice acceleration in a sub-five-minute 3T knee MRI, researchers noted 100 percent sensitivity and 99 percent specificity for anterior cruciate ligament (ACL) tears.