Melinda Taschetta-Millane, Editorial Director
Melinda Taschetta-Millane, Editorial Director
Blog | Melinda Taschetta-Millane, Editorial Director | Breast Imaging | October 09, 2019

Advancements in Breast Cancer Detection

Image by laurixnh from Pixabay

Image by laurixnh from Pixabay 

Breast cancer has affected our patients, our mothers, our sisters, our colleagues, our friends … and ourselves. In this issue, we help support the message started years ago with National Breast Cancer Awareness Month and discuss the progress that has been made in the fight for a cure.

National Breast Cancer Awareness Month got its start in 1985 as a partnership between the American Cancer Society (ACS) and a leading manufacturer of oncology drugs as a commemorative campaign to raise awareness of breast cancer. Thirty-four years later, it is still a topic on the forefront of women’s health. The campaign has helped increase awareness, strongly encouraging monthly self-exams and annual mammograms. In 1993, President Bill Clinton declared the third Friday in October to be National Mammography Day, and urged clinics to offer special discounts to encourage women to get screened.

According to BreastCancer.org, “In 2019, an estimated 268,600 new cases of invasive breast cancer are expected to be diagnosed in women in the U.S., along with 62,930 new cases of in situ breast cancer. About 2,670 new cases of invasive breast cancer are expected to be diagnosed in men in 2019.” So, where do we stand today with technological advancements to help detect, treat and prevent this disease? And can artificial intelligence (AI) help?

As Greg Freiherr stated in his online-exclusive article, “AI Algorithm Detects Breast Cancer in MR Images,” the use of smart algorithms has the potential to make healthcare more efficient, and he noted a study that Sarah Eskreis-Winkler, M.D., presented on at the Society of Breast Imaging’s (SBI) annual meeting. She presented data that an algorithm trained using deep learning (DL) can reliably identify breast tumors in MR images, and stated that “in doing so, the algorithm has the potential to make radiology more efficient.” You can read the full article here: https://bit.ly/2ky92Zv.

And recently, iCAD Inc. announced MedTech Breakthrough, an independent organization that recognizes the top companies and solutions in the global health and medical technology market, selected the ProFound AI platform as the winner of its “Best New Radiology Solution” award in the 2019 MedTech Breakthrough Awards program. This solution, for digital breast tomosynthesis (DBT), is the first U.S. Food and Drug Administration (FDA)-cleared artificial intelligence solution that supports breast cancer detection in DBT. It is trained to detect malignant soft tissue densities and calcifications, and helps radiologists in breast cancer detection.

These are by far not the only examples of where breast cancer detection technology is headed. Visit ITNonline’s Women’s Health channel for a more comprehensive list of the various methods and technologies being made available to help advance this field. The future of breast cancer therapy is changing thanks to these advancements. Radiologists, you are making a difference in improving patient outcomes.

Welcome

The ITN team would also like to welcome Diane Vojcanin as vice president, group publisher, healthcare group, and Andreja Slapsys, integrated media consultant for the Midwest/West. Diane has been with parent company Scranton Gillette Communications for 14 years, having held a number of key roles, including her most recent position as vice president, group publisher of Furniture, Lighting & Decor, an award-winning brand she created. She also served as vice president of custom media, creative services and marketing, and was recognized as one of an elite group of “Top Women in Media” by FOLIO: magazine in 2018. Andreja will be a familiar face to some, having worked with ITN earlier in her career. She most recently held the role of custom media consultant for the company. Please help us welcome them into the world of radiology.

 

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