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    Photoacoustic Microscopy Used to Image Cancer Cells

    Article obtained from Photonics RSS Feed.

    Researchers at the California Institute of Technology (Caltech) are investigating ways in which to better image cancer cells by using photoacoustic microscopy (PAM), a technique that incorporates laser light to induce ultrasonic vibrations, which can then be used to image cells, blood vessels, and tissues.

    Lihong Wang, professor of medical engineering and electrical engineering, and professor Jun Zou, of Texas A&M University, are using PAM to improve on an existing technology for measuring the oxygen-consumption rate (OCR).

    Currently, many cancer cells are taken and each placed into individual “cubbies” filled with blood. Cells with higher metabolisms will use up more oxygen and will lower the blood oxygen level, a process that is monitored by a tiny oxygen sensor placed inside each cubby.

    A scanned image of a grid containing one cancer cell and some blood inside each colored box. The color of the boxes indicates the amount of oxygen dissolved in the blood. Courtesy of Caltech.
    Wang’s improved version uses PAM instead of sensors to measure the oxygen level in each cubby. He does this with laser light that is tuned to a wavelength that the hemoglobin in blood absorbs and converts into vibrational energy — sound. As a hemoglobin molecule becomes oxygenated, its ability to absorb light at that wavelength changes, making Wang able to determine how oxygenated a sample of blood is by “listening” to the sound it makes when illuminated by the laser. He calls this single-cell metabolic photoacoustic microscopy, or SCM-PAM.

    In a new paper, Wang and his co-authors show that SCM-PAM represents a huge improvement in the ability to assess the oxygen-consumption rate of cancer cells. Using individual oxygen sensors to measure OCR limited researchers to analyzing roughly 30 cancer cells every 15 minutes. Wang’s SCM-PAM improves that by two orders of magnitude and allows researchers to analyze around 3000 cells in about 15 minutes. 

    “We have techniques to improve the throughput further by orders of magnitude, and we hope this new technology can soon help physicians make informed decisions on cancer prognosis and therapy,” Wang said.

    Cancer cells are generally much more metabolically active than healthy cells, and some insights into a cancer cell’s behavior can be gleaned by analyzing its metabolic activity. But getting an accurate assessment of these characteristics has proven difficult for researchers. Several methods, including PET scans, fluorescent dyes, and contrasts have been used, but each has drawbacks that limit their usefulness.

    This method, like those previously mentioned, has weaknesses, though. To get a meaningful sample size of metabolic data for cancer cells would require researchers to embed thousands of sensors into a grid. Additionally, the presence of the sensors within the cubbies can alter the metabolic rates of the cells, causing the collected data to be inaccurate.

    The researchers’ paper, titled “Label-Free High-Throughput Single-Cell Photoacoustic Microscopy of Intratumoural Metabolic Heterogeneity,” was published online April 1 by Nature Biomedical Engineering. Wang’s co-authors are Pengfei Hai and Toru Imai of Washington University in St. Louis and Caltech; Song Xu of Texas A&M University, College Station; Ruiying Zhang of Washington University in St. Louis; and Rebecca L. Aft of Washington University School of Medicine and John Cochran Veterans Hospital.  

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    Apr, 05 2019 |

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