Video from RSNA 2019: How is AI changing digital breast tomosynthesis?
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How is the use of artificial intelligence (AI) changing the interpretation of Digital Breast Tomosynthesis (DBT) exams? In this video from RSNA 2019, Rodney Hawkins, vice president of product management for iCAD, discusses the advantages of using ProFound AI for Digital Breast Tomosynthesis, the first and only FDA-cleared software for DBT with AI.

The move from 2D to 3D mammography offers major benefits in terms of improved detection of breast cancer. But 3D mammography also creates new challenges for breast centers, especially given the much higher data volumes that must be analyzed -- leading to longer study interpretation times. But ProFound AI for DBT can help.

RSNA 2019 to offer a look at progress of AI and DBT
What if you took two of the most exciting technologies in medical imaging and put them together? That's the promise behind the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT). The upcoming RSNA 2019 meeting will offer an excellent look at the progress being made in integrating AI with DBT.

While AI is being applied to various imaging modalities, it appears to be a perfect match for DBT. Also known as 3D mammography, DBT offers a number of improvements over traditional 2D full-field digital mammography (FFDM) in terms of cancer detection, but it also presents unique challenges that lend themselves well to AI, such as higher radiation dose and longer interpretation times.

Artificial Intelligence in Breast Cancer Screening: How the World's First and Only Deep-Learning Solution for Digital Breast Tomosynthesis Is Enhancing Patient Care
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Although the power of artificial intelligence (AI) has only been harnessed in recent years, it is increasingly being leveraged in healthcare, specifically within the field of radiology. One area within this realm where it is well-positioned to make a significant impact is in breast cancer detection, especially as digital breast tomosynthesis (DBT), or 3D mammography, continues to grow rapidly in adoption.

While 3D mammography offers a number of benefits to patients, such as improved cancer detection and fewer false positives and unnecessary recalls, it yields an exponential increase of images compared to 2D mammography, thus substantially increasing the daily workload for clinicians. For example, a radiologist reviewing 100 cases per day with 2D would typically review 400 images per day, whereas a radiologist reading 100 cases per day with DBT would be required to read almost 30,000 images per day.

AI is poised to make DBT even better
While some hurdles still need to be overcome, the use of artificial intelligence (AI) to analyze digital breast tomosynthesis (DBT) images is already showing great promise, according to some of the earliest users of the technology. These early adopters say the combination of AI and DBT is producing benefits for both radiologists and patients.

The rapid adoption of DBT, also known as 3D mammography, has advantages in the early detection of breast cancer, such as higher sensitivity and lower recall rates compared with traditional 2D mammography. But DBT also has created challenges, such as more images for radiologists to interpret, representing a considerable increase in interpretation workload.