A new advancement in ultrasound technology promises to considerably improve the accuracy of breast cancer detection, particularly for the nearly half of women worldwide with dense breast tissue. Researchers at Johns Hopkins University have developed a method that boosts the ability to distinguish between benign adn possibly cancerous masses, achieving 96% accuracy in a recent study – a substantial leap from the 67% accuracy of customary ultrasound [[1]]. Published today in *Radiology Advances*, the innovation focuses on enhancing signal processing and could lead to fewer unnecessary biopsies and reduced patient anxiety.
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MADRID, 18 Dic. (EUROPA PRESS) –
A new ultrasound technology developed at Johns Hopkins University is demonstrating nearly perfect accuracy in distinguishing between fluid-filled and solid breast masses. Published December 18 in Radiology Advances, the advancement has the potential to reduce unnecessary follow-up tests, painful procedures, and anxiety for patients, particularly those with dense breast tissue.
In a study of 132 patients, radiologists correctly identified breast masses 96% of the time using the new technology, a significant improvement over the 67% accuracy achieved with traditional ultrasound. This is a crucial step forward in breast cancer detection, as accurate diagnosis is key to appropriate treatment and patient care.
“This is important because the benefits of ultrasound in breast cancer detection can be limited by the similar appearance of benign fluid-filled masses and solid masses, which can be cancerous,” explained Muyinatu “Bisi” Bell, a biomedical and electrical engineer at Johns Hopkins specializing in imaging technology.
“Our achievement will transform the landscape of breast cancer diagnosis. Radiologists will be able to have immediate confidence in their diagnoses. And patients won’t be referred for biopsies or invasive procedures when there is greater certainty that a mass is not a cause for concern,” Bell stated.
WHEN IMAGING ALONE ISN’T ENOUGH
Current guidelines recommend that all women over 40 receive mammograms for early breast cancer detection. However, results can be inconclusive for women with dense breast tissue. These patients are often referred for ultrasounds, but this technology also faces challenges with dense tissue.
Ultrasound works by sending sound waves through a probe into the breast. The sound bounces off structures like masses and is recorded. Ideally, the sound travels directly from the mass to the probe. However, dense breast tissue scatters the sound waves before they reach the mass, causing acoustic distortion in the image. A benign cyst filled with fluid, which should appear dark on images, often appears gray inside, mimicking the appearance of a cancerous tumor.
The new method doesn’t change how ultrasounds are produced, but it improves how the signals are processed. Conventional ultrasound relies on the amplitude of signals, converting high and low signals into black, white, or gray. The new method focuses on coherence, meaning the image is based on the similarity of signals to neighboring signals.
WHY ULTRASOUNDS CAN SOMETIMES FAIL
In addition to providing clearer images, the new system makes it easier for radiologists to assign a numerical score to each mass – with only those above a certain threshold considered concerning.
“It’s truly exciting because we’re taking the same ultrasound data, captured through the same process, but modifying the signal processing and achieving a much better interpretation of these images,” Bell said. “When we combine the visual assessment with a numerical score, that’s when the technology really shows the greatest improvement. It eliminates decision fatigue by automating something that would normally require more thought and interpretation.”
A NEW WAY TO INTERPRET WHAT THE BODY IS TELLING US
“The results of this study are important for our specialty, as they suggest this technique may improve our ability to differentiate between solid masses and certain types of cysts that can mimic solid masses on ultrasound,” added co-author Eniola Oluyemi, a diagnostic radiologist at Johns Hopkins Medicine.
“This increased diagnostic certainty can reduce false positives and the need for follow-up and biopsies, providing greater peace of mind to our patients at the time of the initial exam,” she noted.
Existing artificial intelligence can already distinguish between benign and cancerous masses in ultrasound images. The research team believes their innovation, combined with AI, could allow doctors to quickly determine the composition of a mass and whether it is cancerous during an initial ultrasound appointment. Bell also hopes the innovation could eventually be adapted for at-home use as part of a self-breast exam.
