Professional Rahim Hassanally frequently supports efforts to raise breast cancer awareness, and below shares how new automated cancer screenings help tackle the disease earlier.
Rahim Hassanally was born and raised in Dallas, Texas and attended Southern Methodist University, earning a degree in Political Science and English. Today, he’s a savvy businessman in the automotive industry who is passionate about breast cancer awareness.
“Breast cancer is a devastating disease that doesn’t discriminate based on age, and it leaves women and families feeling hopeless too often,” says Rahim Hassanally. “However, thanks to breakthroughs in cancer research and screenings––like recent advancements in automated breast ultrasound systems––doctors can restore their hope.”
In 2016 alone, the American Cancer Society registered over 245,000 new breast cancer patients in the country. The rising prevalence of the disease has increased demand for automated breast ultrasound systems (ABUS). This new technology replaces typical hand-held ultrasounds for breast screenings with unique benefits.
At the core of ABUS are high-frequency sound waves, but these devices also receive 3-D volumetric images. The transducer used in automated breast ultrasound systems is able to conduct an automatic scan of the targeted areas, which nearly eliminates operator dependency and degrees of human error. Additionally, Rahim Hassanally tells us, the new examination technique can perform cancer screenings much faster than traditional ultrasounds.
“Though these cancer screening systems are relatively new, they’ve already made a tremendous impact on how fast and thorough ultrasounds return critical data, allowing doctors and physicians to understand and address cancer with more precision and speed,” says Rahim Hassanally. “And instead of taking picture after picture to obtain accurate readings of patients’ tissue, newer devices within the last couple of years are able to create 3D-images that provide much more insightful data.”
The FDA approved the first ever automated breast ultrasound system in 2012, which was created by GE/U-Systems for enhanced screenings. Earlier models were able to capture many 2D images to relay back to doctors, about 2000 images on average, but it consumed a lot of time. Newer models rely on an advanced computer-aided detection system that runs on deep learning algorithms. The result is either single imaging that can highlight specific parts for enhanced observation or else a complete and accurate 3D model.
“We are gaining the power to detect breast cancer more thoroughly and quickly than ever before,” says Rahim Hassanally. “And now we’ve developed technology that uses full-film digital mammography to detect cancer down to the densest tissues, empowering medical professionals everywhere to view patients’ conditions with incredible precision.”