Breast Imaging

Breast imaging includes imaging modalities used for breast cancer screenings and planning therapy once cancer is detected. Mammography is the primary modality used. Mammogram technology is moving from 2D full-field digital mammography (FFDM) to breast tomosynthesis, or 3D mammography, which helps reduce false positive exams by allowing radiologists to look through the layers of tissue. Overlapping areas of dense breast tissue on 2D mammograms appear similar to cancers and 3D tomo helps determine if suspect areas are cancer or not. About 50% of women have dense breast tissue, which appears white on mammograms, the same as cancers, making diagnosis difficult. Radiologists use the Breast Imaging Reporting and Data System (BI-RADS) scoring system to define the density of breast tissue. Many states now require patients to be notified if they have dense breasts so they understand their mammograms might be suboptimal and they should use supplemental imaging that can see through the dense areas. This includes tomosythesis, breast ultrasound, automated breast ultrasound (ABUS), breast MRI, contrast enhanced mammography and nuclear imaging, including positron emission mammography (PEM).

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Synthetic MRI measures predict breast cancer treatment responses, according to new research

Researchers suggested that the quantitative measures derived from synthetic MRI exams could be used to help guide treatment decisions for breast cancer patients.

Surveillance breast MRI

Surveillance breast MRI findings linked with future second cancer

The new research focused specifically on associations between background parenchymal enhancement—a known risk factor for breast cancer, visualized on surveillance MRI exams—and secondary breast cancers.

breast cancer mammography mammogram

MR-directed enhanced mammography detects more malignancies than MR-directed ultrasound

MRI-directed contrast enhanced mammography could serve as a useful stand-alone or complimentary tool for biopsy planning when suspicious lesions are detected. 

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Minority women are more likely to delay or forego follow-up breast imaging, study reveals

Nearly 20% of the women included in the study did not complete their follow-up imaging at all, and out of the 3,648 women who did adhere to additional imaging, 23.3% delayed their exams beyond the recommended 60-day period.

Is stopping antithrombotic therapy prior to image-guide breast biopsy really necessary?

Experts arrived at this conclusion after comparing incidents of hematoma between patients who did and did not receive antithrombotic therapy prior to their procedure.

COVID's impact on breast radiology trainees represents a 'critical workforce issue'

The authors of the new study noted that, even before the pandemic, consultant breast radiologists were among the most in-demand specialists. The loss of interest in it as a specialty due to COVID will inevitably pose further challenges for recruitment.

Example of an artificial intelligence (AI) app store on the Sectra website, where Sectra PACS users can select the AI algorithms they want that are already integrated into the Sectra System. Other vendors have followed a similar approach to AI developed by many smaller vendors they partner with.

VIDEO: Development of AI app stores to enable easier access

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains how radiology vendors have developed AI app stores to make it easier to access new FDA cleared AI algorithms.
 

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains artificial intelligence (AI) for radiology. Dreyer also holds the positions of vice chairman of radiology at Massachusetts General Hospital, chief data science and information officer for the departments of radiology for both Massachusetts General Hospital and Brigham and Women's Hospital.

VIDEO: Where will radiology AI be in 5 years?

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains 5 developments to watch for in radiology artificial intelligence (AI).

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