Researchers aim to use method to find minute metastases during surgery
Women undergoing treatment for ovarian cancer are checked for tumor cells that may have spread to surrounding tissues, but current technologies miss very small metastatic areas. Now a laser microscopy technique is able to identify these regions with great accuracy.
Microscopic technologies that use lasers to fire photons at target tissues, and then receive and interpret information about the metabolic and structural characteristics of the tissue are advancing at a rapid rate.
One important use of these microscopes is the ability to non-invasively detect metabolic and structural “signatures” of small micro-metastases from parent tumors that are too small to be picked-up by traditional light microscopy.
Now researchers led by Irene Georgakoudi, Ph.D., Professor, Department of Biomedical Engineering at Tufts University, and Thomas Schnelldorfer, M.D., Ph.D., from Lahey Hospital, Burlington, Massachusetts have combined advanced microscopy and computational analysis with the hope of rapidly pinpointing ovarian metastases in the operating room. The work is reported in the September issue of Biomedical Optics Express1.
“This is extremely high impact work,” says Behrouz Shabestari, Ph.D., Director of the NIBIB Program in Optical Imaging and Spectroscopy. “The ultimate aim of using this technology during surgery—to detect and remove routinely missed metastases—promises to significantly improve surgical outcomes for women being treated for ovarian cancer. Plus, the technology will also be applicable to other types of cancer.”
The multiphoton laser scanning technique involves firing short bursts of laser light at the tissue. The laser light reflects off different components of the tissue, which have different shapes and textures and therefore, emit different signals. The signals are captured by the microscope and are analyzed by algorithms that interpret the differing signals to ultimately pinpoint whether tissues are normal or cancerous.
Combining the laser microscopy and the computations conducted by the algorithms allows the identification of each type of tissue without any sort of chemical labeling or processing of the tissue. This is a critical aspect of the technology because it opens the possibility of using the system in the operating room to scan tissues during surgery, where tiny metastatic areas, not visible with current technologies, could be removed along with removal of the primary ovarian tumor tissue.
The current experiments assess the feasibility of using the microscope during a laparoscopy, a minimally invasive procedure that allows doctors to visualize the peritoneum, the compartment that surround the ovaries. This is a procedure that is used to assess the progression stage of the disease in order to make treatment decisions. So, as a first step, the researchers tested their system on biopsies taken from ovarian peritoneal metastases and the healthy peritoneum of women undergoing laparoscopy and surgery for ovarian cancer.
The research team imaged healthy and diseased biopsies from 8 patients. Remarkably, the technique correctly classified 40 of the 41 images with 11 of 11 correctly classified as metastatic and 29 of 30 classified as healthy. “The results of this study are extremely encouraging,” says Dimitra Pouli, M.D., Ph.D., lead author of the study. “The next steps include verifying our results with a larger sample from a wider variety of patients.”
Another critical aspect of the group’s work is to integrate the microscope into the repertoire of surgical instruments to realize the ultimate goal of analysis of tissues during an operation. This would allow immediate removal of formerly undetectable areas of metastatic cancer.
The work was funded by National Institute of Biomedical Imaging and Bioengineering (NIBIB) (NIBIB- R21 EB023498); the Hellenic Medical Society of New York (Stavros Hartofilis fellowship); and the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) (SAGES 2013 Research Award).
1. Two-photon images reveal unique texture features for label-free identification of ovarian cancer peritoneal metastases. Dimitra Pouli, Elizabeth M. Genega, Travis B. Sullivan, Kimberly M. Rieger-Christ, Valena Wright, Irene Georgakoudi, and Thomas Schnelldorfer. Biomedical Optics Express. Vol. 10, No. 9/ 1 September 2019.