It’s been a long time coming. Nearly a decade has passed since ATL took a serious run at advancing the medical art of breast cancer diagnosis. The company, long-since absorbed by Philips Healthcare, developed a novel algorithm designed for its Ultramark 9 HDI, later adapted for its HDI 3000 and 5000.
It’s been a long time coming. Nearly a decade has passed since ATL took a serious run at advancing the medical art of breast cancer diagnosis. The company, long-since absorbed by Philips Healthcare, developed a novel algorithm designed for its Ultramark 9 HDI, later adapted for its HDI 3000 and 5000.
The goal was to eliminate the need for at least some biopsies. In an effort to reach it, ATL took on the arduous task of a premarket approval application with the FDA, which required conducting and analyzing the results from clinical trials to prove the value of its algorithm.
ATL didn’t reach its goal, but it did help raise the industry standard for ultrasound breast imaging. Previously, the modality provided a reliable, albeit simplistic, way to distinguish between cysts and solid masses, as ultrasonic waves either passed through or created a shadow behind the two different types of lesions.
Since then, advances in transducer technology and processing algorithms have elevated ultrasound to new levels of performance. As important, ATL’s pioneering efforts raised the collective consciousness about breast imaging that now is translating into research such as the work done at the University of Michigan in Ann Arbor.
The research, which will be published in the November issue of Radiology, showed that 3D power Doppler ultrasound allowed radiologists to distinguish between malignant and benign breast masses. The researchers found that faster blood flow indicated the presence of cancer when examining 78 women who were scheduled for biopsy of a suspicious breast mass. Results from 3D Doppler exams were compared with those from biopsies.
When combined with age-based assessment and gray-scale visual analysis, 3D Doppler showed 100% sensitivity in identifying cancerous tumors and 86% specificity in excluding benign tumors.
This may be only the beginning of what could be a flood of results in the coming years. At the RSNA meeting, we’ll see more progress in breast tissue analysis. It will not all come from ultrasound. But ultrasound will be among those leading the way, thanks in large part to ATL.
FDA Clears AI-Powered Ultrasound Software for Cardiac Amyloidosis Detection
November 20th 2024The AI-enabled EchoGo® Amyloidosis software for echocardiography has reportedly demonstrated an 84.5 percent sensitivity rate for diagnosing cardiac amyloidosis in heart failure patients 65 years of age and older.
FDA Clears Updated AI Platform for Digital Breast Tomosynthesis
November 12th 2024Employing advanced deep learning convolutional neural networks, ProFound Detection Version 4.0 reportedly offers a 50 percent improvement in detecting cancer in dense breasts in comparison to the previous version of the software.