Professor Hao Xin's DARPA Contract to Advance Bomb Detection and Breast Cancer Screening

The kind of mayhem caused by homemade explosives, both domestically and overseas, likely will involve high-tech systems that can identify concealed bombs from a distance. With a recent $1.5 million U.S. Department of Defense award, University of Arizona researchers will adapt their breast cancer imaging research for detection of embedded explosives.

Electrical and computer engineering professor Hao Xin, principal investigator on the Defense Advanced Research Projects Agency, or DARPA, award, says the same advanced technology he and his colleagues have been creating for early breast cancer detection is now being developed to rapidly detect explosives in opaque, or nontransparent, materials.

"We started our research in 2009 with no funding but kept working because we knew it would make a huge difference," said Xin, director of the UA Millimeter Wave Circuits and Antennas Laboratory. "Eventually we had some internal funding, and here we are today."

The types of materials often used to conceal explosive devices -- mud and meat, for example -- share a trait with breast tissue: high water content, which makes it difficult to identify objects or abnormalities using existing ultrasound or microwave imaging techniques. Ultrasound images show a clear shape, but the properties cannot be delineated. Microwave images have contrast, but shapes are not clear.

The new hybrid technology will combine the advantages of high-contrast microwave imaging with high-resolution ultrasound imaging to detect improvised explosive devices, or IEDs. The technology also mitigates the harmful radiation effects of traditional X-ray imaging and works without making contact with the material in which the explosive is concealed.

"We take advantage of both technologies and avoid the disadvantages to increase detection specificity," said Xin.

The 18-month renewable contract, titled Thermoacoustic Imaging and Spectroscopy Method for Explosive Detection at Standoff, sends microwaves into a target, which locally heats up distinct objects or tissues differently, then the quick thermal expansion generates an ultrasound image that is identified using a novel spectroscopic process.

Joining forces with Xin are his co-investigator, Russell Witte, assistant professor of radiology, biomedical engineering and optical sciences, and a member of the University of Arizona Cancer Center; Raytheon Company; the National Institute of Standards and Technology, or NIST; and a handful of exemplary graduate students and graduate research assistants. One of those graduate students, Xiong Wang, recently was awarded the IEEE Antennas and Propagation Society PhD award for work in this imaging area. Raytheon Company is lending its expertise in IEDs as well as contributing a critical piece of equipment, a portable microwave power amplifier.

"A large research university like the UA allows people across disciplines to collaborate with industry on projects like this that have the potential to save lives on many fronts," said Xin.

Like bomb detection, breast cancer detection has seen myriad advancements in recent years, with a number of competing technologies emerging, but none has overcome the challenges associated with identifying the specific properties of abnormal tissue.

Breast cancer is the most common cancer among women and second only to lung cancer in leading causes of cancer death among women. With better screening and improved treatment, survival rates have improved steadily over the last 23 years, according to the National Institutes of Health. Nevertheless, the track record for breast cancer detection remains inadequate. Mammography, today’s gold standard for breast cancer imaging, fails to detect breast cancer in as much as 25 percent of cases where it is later confirmed. And, breast cancer is indicated in about one in eight tissue biopsies following abnormal mammograms, according to various scholarly and medical sources.

"The new research and imaging technique will help us better identify abnormalities in tissue and could significantly reduce the need for diagnostic biopsies, increase the rates of early breast cancer detection, and improve treatment outcome," said Xin.