Portable Laser-Based Scanning Device Detects Critical Biomarkers | Research & Technology | July 2022

LITTLE ROCK, Ark., July 27, 2022 — Researchers at the University of Arkansas for Medical Sciences (UAMS) reported advancements to the previously developed Cytophone device. In the current work, the researchers integrated a miniature multispectral laser diode array, time-color coding, and high-speed, time-resolved signal processing into the instrument, which is a photoacoustic device originally designed for early detection of cancer cells,

Described in 2019, Cytophone uses laser beams and sound waves to noninvasively scan circulating blood for melanoma cells, and complete scans of a person’s entire blood volume in a matter of hours. According to findings published in 2019, Cytophone was shown to be about 1000× more sensitive than existing technologies used to detect circulating cancer cells.

The latest version of the device uses the newly integrated features to provide greater portability and specificity than the original patented platform. The multispectral laser diodes encompass wavelengths ranging from 630 to 1650 nm. The time-color-coding mode enables multicolor, in vivo flow cytometry of multiple targets.


Scientific Reports recently published the research findings of co-authors Vladimir Zharov (right) and James Y. Suen. The researchers published advances to the device called Cytophone, a noninvasive, miniature, laser-based blood scanner for disease identification. Courtesy of the University of Arkansas for Medical Sciences.


To identify abnormal cells circulating through the body, the multicolor laser diode array is directed at veins or arteries near the wrist. The abnormal cells absorb the light, generating acoustic waves that are detected with small ultrasound transducers attached to the skin.

The researchers used two-color (808 nm/915 nm) laser diodes to demonstrate spectral identification of white and red blood clots, melanoma cells with melanin, and malaria with hemozoin nanocrystals as biomarkers. Using confocal photothermal and fluorescent microscopy, they identified infected cells from a malaria murine model and a cultured human malaria parasite in vitro within 4 h after parasite invasion.

In the recent study, the platform enabled the researchers to detect malaria — although data obtained in earlier tests, as well as in previously published results using conventional lasers, indicated that the Cytophone platform could be used for the label-free diagnosis of melanoma, blood disorders, stroke, and other diseases. The device overcomes the limitations of conventional lasers, particularly the use of photoacoustic flow cytometry with solid lasers.

“Our latest findings demonstrate that a highly accurate portable device is achievable, which is especially significant for resource-poor countries fighting diseases like malaria,” Zharov said. “This was made possible by exciting breakthroughs in laser diode and digital technologies for counting the acoustic signals from individual biomarkers at different wavelengths for identification of diseases with different spectral fingerprints.”

The results could encourage interest in collaborating with the team on the development and application of the portable device for disease detection, the researchers said.

“Someday, we believe this technology with small, cost-effective lasers will translate to a wearable device the size of a smartwatch or bracelet,” said professor James Y. Suen

“More work needs to be done, but the progress in laser diodes with color numbers higher than in the natural rainbow spectrum make this a promising technology for the identification of different malaria strains,” said Sunil Parikh, MD, and associate professor of epidemiology at Yale University.

Suen and Zharov established the spinoff company, CytoAstra LLC, through BioVentures LLC at UAMS, to commercialize the patented Cytophone platform initially for detection of circulating melanoma cells.

The research was published in Scientific Reports (www.doi.org/10.1038/s41598-022-11452-w). Previous research was published in Science Translational Medicine (www.doi.org/10.1126/scitranslmed.aat5857).

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