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Gus Iversen, Editor in Chief | July 17, 2025
An investigational breast imaging system that combines photoacoustic and ultrasound technologies has shown early promise in clinical testing, producing clear, AI-enhanced 3D images in under a minute without the need for painful breast compression.
Detailed in a study published in IEEE Transactions on Medical Imaging, the system, called OneTouch-PAT, was developed by researchers at the University at Buffalo in collaboration with Roswell Park Comprehensive Cancer Center and Windsong Radiology. It uses a standing, contact-based scan method that aims to improve comfort and eliminate operator variability through full automation.
The team tested OneTouch-PAT on 61 patients with breast cancer and four healthy volunteers. According to the study, the system effectively visualized key breast cancer subtypes, including Luminal A, Luminal B, and triple-negative breast cancers. It operates by interleaving photoacoustic and ultrasound scans, then applying a deep learning algorithm to enhance image resolution and contrast.
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“Our system, which is called OneTouch-PAT, combines advanced imaging, automation, and artificial intelligence — all while enhancing patient comfort,” said Jun Xia, Ph.D., a biomedical engineering professor at the University at Buffalo and the study’s corresponding author. “More work is needed before it can be used in clinical settings, but we’re excited about OneTouch-PAT’s potential to augment current imaging methods and help fight this terrible disease.”
OneTouch-PAT’s dual imaging approach could prove particularly valuable for women with dense breast tissue, where conventional mammography often struggles. While ultrasound can improve detection in dense tissue, it is more susceptible to false positives and is reliant on operator skill. The automated nature of OneTouch-PAT aims to address those limitations.
The study received funding from the National Institutes of Health. Researchers are planning further trials with a broader patient population, including those with benign lesions, and are working to enhance the system’s imaging speed and accuracy through hardware and software improvements.
