QCL-based IR Microscopy Performs Rapid Cancer Diagnosis

A quantum cascade laser-based IR microscope was used for the rapid, label-free classification of colorectal cancer tissues.

IR imaging has been shown to be a reliable method for tissue classification. However, the Fourier transform infrared (FTIR) microscopy technique that has been used to date takes a full day to analyze samples; and the time required for analysis has hampered the use of IR imaging in clinical settings.

Researchers from Ruhr-Universität Bochum (RUB) have developed new methods of cancer diagnostics. From left: Claus Kuepper, Frederik Großerüschkamp, Angela Kallenbach-Thieltges, and Klaus Gerwert. Courtesy of RUB, Marquard.

A research team at Ruhr-Universität Bochum (RUB) has deployed an IR microscope with quantum cascade lasers (QCLs), replacing FT with QCL technology. By simplifying the measurement setup through the use of a QCL, the team reduced the time required for analysis from one day to a few minutes. Along with bioinformatical image analysis, the QCL-based IR microscope can perform label-free classification of cancer tissue and can be fully automated.

QCL-based IR microscopes, in contrast to FTIR microscopes, allow the use of a single frequency. Thereby, within very short measuring times, an overview image can be obtained for selecting the region of interest, which can then be analyzed in detail.

The team used QCL-based IR imaging to analyze 110 tissue samples taken from colorectal cancer patients. Results showed 96 percent sensitivity and 100 percent specificity for this label-free method, as compared to histopathology, which is considered the gold standard in routine clinical diagnostics.

“We have . . . reduced the measurement period by a factor of 160,” said researcher Frederik Großerüschkamp.

As a control, the measurements were carried out using two different pieces of equipment, and the analyses were performed by several users, with no effect on results.

“The method is now very fast and reliable and does not depend on a specific device or a specific user," said researcher Angela Kallenbach-Thieltges. "This opens up new avenues for automated classification of tissue samples taken directly from the patient.”

As a next step, larger studies of unmet clinical needs will be addressed. The team believes that this could propel IR-based label-free and automated tissue classification into clinical routines. The new approach could also be used for biomarker search.

The team believes that its work demonstrates that IR imaging is a nondestructive, label-free, and now a rapid technique for tissue classification and biomarker research.

“The results of the study give rise to hope that highly precise therapy is within reach . . . [that] will ultimately prove more successful than traditional approaches,” said researcher Klaus Gerwert.

The research was published in Scientific Reports (doi:10.1038/s41598-018-26098-w).