Adding contrast media to high-energy digital mammography studies can generate clearer images of difficult-to-spot breast masses. The use of contrast and digital subtraction algorithms led to results similar in clarity to breast MR in a small investigational study by German researchers.
Adding contrast media to high-energy digital mammography studies can generate clearer images of difficult-to-spot breast masses. The use of contrast and digital subtraction algorithms led to results similar in clarity to breast MR in a small investigational study by German researchers.
Dr. Felix Dietmann and colleagues at Charite Hospital in Berlin performed high-energy digital mammography on 10 women with 12 suspicious lesions before contrast administration and 60, 120, and 180 seconds after. Contrast imaging revealed all 12 lesions, three of which had been missed on the unenhanced views.
Despite the ease of identifying the lesions, the process lacks MR's ability to characterize masses based on contrast uptake and washout curves. In the study population as well as subsequent cases, Dietmann found that malignancies, fibroadenomas, and other masses all showed enhancement without a consistent pattern.
The technique may, however, have two advantages: To maximize the effectiveness of the contrast, the imagers used much less breast compression than they would need for a standard mammogram, improving patient comfort. The improved visibility of masses may also make biopsy procedures more accurate while keeping the process cheaper and simpler than using MR guidance.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
Mammography-Based AI Abnormality Scoring May Improve Prediction of Invasive Upgrade of DCIS
April 9th 2024Emerging research suggests that an artificial intelligence (AI) score of 75 or greater for mammography abnormalities more than doubles the likelihood of invasive upgrade of ductal carcinoma in situ (DCIS) diagnosed with percutaneous biopsy.
Mammography Study: AI Improves Breast Cancer Detection and Reduces Reading Time with DBT
April 3rd 2024An emerging artificial intelligence (AI) model demonstrated more than 12 percent higher specificity and reduced image reading time by nearly six seconds in comparison to unassisted radiologist interpretation of digital breast tomosynthesis (DBT) images.