Despite being commonly considered the leading option for breast cancer diagnosis, mammograms are routinely being outpaced in several categories by ultrasounds, which can render a more accurate breast tissue image for younger women as well as individuals with denser tissue. Moreover, ultrasounds are the less expensive option and do not require the use of radiation.
Working to make ultrasound use even more convenient and speedy, San Francisco-based startup iSono Health has introduced its portable Atusa system, which leverages machine learning AI to render whole-breast images in mere minutes. “Clinicians and women worldwide need high-quality breast imaging that is accessible and efficient at scale without the need for highly skilled operators,” said iSono Co-Founder and Chief Executive Officer Dr. Maryam Ziaei. “The portable and automated Atusa system stands alone in comparison to other ultrasound offerings in promising to address that need.”
The FDA recently gave a green light to the technology, which can be activated by clinicians – without requiring any oversight by specially trained technologists – with just the push of a button. While manual probing usually takes 10 to 15 minutes, whole-breast volume scans performed by Atusa take only around a minute per side. Completed scans instantly produce 2D images of breast tissue, and then Atusa’s AI is put to work generating computer or tablet-accessible 3D images that give physicians radial, coronal, sagittal, and transverse views of the tissue, which aid in lesion identification.