New Imaging Technique Combines Ultrasound and Optical Tomography for Faster, Enhanced Scans

The technique employs detectors for acoustic waves on the body's surface to gather acoustic wave intensity data. This data enables the creation of images of various optical properties of tissues, including absorption and diffusion, that hold critical information about the location and stage of cancerous tissue. Now, researchers are on a mission to improve medical imaging using the new QPAT technique.

Developing QPAT poses a major challenge due to insufficient acoustic wave measurements on the body's surface. This shortage can compromise image quality and lead to inaccurate diagnosis of cancerous tumors. To overcome this hurdle, a multidisciplinary team led by University of Texas at Arlington (Arlington, TX, USA) is working to significantly develop and improve the QPAT imaging technique using an innovative combination of game theory, statistical sensitivity analysis, and gradient-free optimal control methods. This approach aims to address the lack of acoustic wave measurements, stabilize computational algorithms, and recalibrate them. The goal is to achieve high-contrast and high-resolution images, thereby elevating the precision and effectiveness of the QPAT technique.

“QPAT is robust because it uses information from two types of imaging techniques and has the potential to provide high-quality images. It can tell us so much more about what’s going on under the skin,” said Souvik Roy, mathematics assistant professor at the University of Texas at Arlington. “By providing better images, doctors will be able to make more accurate diagnoses in shorter time frames. This will lessen anxiety for patients as well as decrease costs for the health care industry by reducing the need for repeated scans.”

“We hope to facilitate a safe start to research on imaging human subjects using QPAT,” Roy added. “Our ultimate goal is helping patients get better and develop more accurate images in a shorter time frame. These enhanced scans should help doctors and patients make better health care treatment decisions. Down the line, we know this will improve outcomes, reduce patient anxiety and be highly cost-effective.”

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