In this MEDICA-tradefair.com interview, Professor Jürgen Popp explains why conventional frozen section biopsies often tend to overlook tumor tissue, describes the new diagnostic procedure and the three imaging techniques it combines and envisions the future of cancer care.
Professor Popp, what is the conventional surgical procedure for removing a tumor? How can this method be improved?
Prof. Jürgen Popp: To answer your question, I would like to focus on the head and neck area. It is relatively easy for surgeons to identify and remove a full-fledged tumor. It is much more problematic to identify tumor margins. What’s more, various environmental factors – including diet, alcohol consumption or smoking – often lead to inflammation surrounding the tumor in the head and neck area or other parts of the mucous membrane. This makes it more difficult to delineate them from a developing tumor. In most cases, surgeons resort to frozen section diagnostics. They take a biopsy, freeze it, cut it and stain it with hematoxylin and eosin (HE). However, there is a high probability that we overlook or miss tumor tissue with this traditional frozen section procedure. That's because when it comes to frozen material, the quality of this type of staining is not as good the quality of histological stains. For the latter, the biopsy is embedded in formalin before it is cut and stained. Embedding biopsies in formalin renders entirely different and better stain results. Having said that, a biopsy has to first be sent to the lab for analysis by a pathologist, which typically takes between two to eight days. Unfortunately, this means that between 15 and 20 percent of patients have to return to the hospital after tumor removal because more tumor tissue was subsequently detected. Needless to say, this is a considerable psychological burden on patients. Another concern is scar tissue that forms within one to two weeks after the first surgery, which makes tumor localization even more difficult. That’s why we need a rapid analysis method with the lowest possible error rate.