Digital pathology: Flensburg's professor revolutionizes cancer diagnostics!

Digital pathology: Flensburg's professor revolutionizes cancer diagnostics!

Flensburg, Deutschland - The Flensburg University of Applied Sciences has launched an important project on digital pathology, which was made by Prof. Dr. Marc Aubreville is managed. The German Research Foundation (DFG) promotes this project, which aims to improve diagnostics through the use of artificial intelligence (AI) and to develop new AI-based surgical techniques. Aubreville, which has been working at the university since summer 2024, refers to the support that digital pathology offers pathology by identifying striking tissue samples that indicate malignant tumors.

Aubreville explained that AI should not take over the diagnosis itself, but can help pathologists identify difficult to identify areas in tissue samples. His research work in the field of digital pathology began during his doctorate, in which he achieved first success in the detection of breast cancer in dogs. These successes led to human tissue samples to the transferability of his algorithm. Aubreville is currently working with partners from Berlin and Vienna to collect extensive data to optimize algorithms. The Flensburg University of Applied Sciences offers him a practical research environment that enables a close connection to teaching.

progress of artificial intelligence in pathology

The use of artificial intelligence in pathology is becoming increasingly important. For example, the Ärzteblatt that enables increasing digitization to learn. However, the implementation of these technologies is still at the very beginning, and randomized prospective studies are missing that show the actual benefits. There are first indications that pathologists can make computer support faster and more precisely. In a pilot study on the diagnosis of breast cancer, the sensitivity of micrometastases improved when an algorithm was used for support.

The digital transformation in pathology, however, has not yet advanced far advanced compared to other imaging disciplines. In Germany, Whole Slide Scanner are rarely used for routine diagnostics, which is due to high costs and concerns about security. While AI algorithms prove to be precise tools to differentiate between tumors and healthy tissue, there are challenges in implementation, including the lack of digitized sample material and the necessary high investment costs. Future prospective and randomized studies are needed to evaluate the benefits of AI in the pathology.