Houston Daily

University of Houston researchers have developed a new X-ray imaging method that can capture three types of image contrast in a single exposure. This advancement is expected to improve the detection and monitoring of diseases such as cancer and lung conditions, while also offering potential benefits for industrial applications.

The research team, led by physics researcher Jingcheng Yuan and Mini Das, Moores professor at UH’s Cullen College of Engineering and College of Natural Sciences and Mathematics, created a system that provides more detailed diagnostic information without the need for multiple exposures or complex mechanical movement. Their findings will be published in the journal Optica.

Traditional X-ray and CT imaging rely on attenuation contrast, which shows how tissues absorb X-rays. While this method works well for identifying bones or large density differences, it is less effective at detecting early-stage cancers or subtle changes in microstructures like those found in lungs. Newer methods that try to address these limitations often require complicated equipment and longer exposure times, resulting in higher radiation doses.

“A lot of the methods being explored often need long imaging time because they require a system component to be moved multiple times — often over 10 or 20 times — to make these multiple image contrast,” said Das.

To address these challenges, the University of Houston team designed a patent-pending system using physics-based models. The configuration allows three types of contrast—attenuation, differential phase, and dark field—to be obtained from one X-ray exposure by placing a single slatted plate between the source and detector.

Differential phase contrast shows how X-rays bend as they pass through materials, making boundaries and structural variations easier to see. Dark field imaging reveals how small-angle X-rays scatter from microstructures, which can help identify features such as lung air pockets or microscopic defects in materials.

Das noted that dark-field imaging could be especially useful for diagnosing lung diseases like chronic obstructive pulmonary disease (COPD), where current techniques struggle to detect microstructural changes. It may also assist with tracking changes in lung cancer during treatment.

“We know there will be benefit, but how much that will help clinicians diagnose, detect and follow up for therapy monitoring is an open avenue right now,” she said.

The new method offers several advantages: it produces images quickly without motion artifacts; it reduces radiation dose—a benefit particularly important for children and small animals; and its cost-effective design can be integrated into existing X-ray and CT systems with minor modifications. The research team plans to adapt the technology for small-animal studies and explore clinical uses such as lung imaging and low-dose breast cancer screening.

“We expect that this will become practical, translatable,” Das said.

In addition to medical applications, this technique could impact industries needing internal defect detection or microstructure analysis—for example, petroleum exploration or real-time monitoring of engineered components’ chemical or structural changes.

Das has previously advanced imaging methods involving photon-counting detectors with novel algorithms for precise 3D visualization. Her work was inspired by her early experience developing breast CTs when she realized traditional mammography’s limited ability to detect certain cancers due to poor contrast mechanisms.

“This is the modality that millions of women are using today for breast screening around the world,” Das said. “I realized that this is really a big problem, so when I came to Houston for my position, one of my goals was to try to change this to see how we can contribute to this field by combining physics, optics and engineering.”

Her interdisciplinary research receives funding from agencies including the National Science Foundation, Congressionally Directed Medical Research Programs, and National Institutes of Health. She mentors students across several engineering disciplines. Recently elected as a fellow of Optica for her contributions to the field—and previously named a fellow of SPIE—Das continues her work at the forefront of imaging innovation.

“We know there will be benefit, but how much that will help clinicians diagnose, detect and follow up for therapy monitoring is an open avenue right now."

— Mini Das, UH’s Cullen College of Engineering and College of Natural Sciences and Mathematics