16.09.2024

A new AI-based digital platform, developed by a research team at the University Hospital of Cologne, enables rapid and precise analysis of lung cancer tissue sections. The platform, which is based on advanced algorithms, could significantly improve the quality of diagnostics and provide new insights into the treatment of lung cancer.

A team of researchers from the Faculty of Medicine and the University Hospital of Cologne has developed a digital pathology platform that uses artificial intelligence (AI) to speed up and refine the analysis of tissue samples from lung cancer patients.

Image: Comparison of two tissue sections of a lung, on the left a traditional histological section in pink, on the right a digitized and color-coded tissue section; Copyright: Dr. Yuri Tolkach

The image shows how the algorithm initially processes the typically stained tissue section (left) and creates a map in which different tissue types can be seen in different colors (blue is the tumor, in this case an adenocarcinoma of the lung)

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The importance of digitalization in pathology

Lung cancer is one of the most common and deadliest forms of cancer worldwide. The precise pathological examination of tissue samples is crucial for choosing the appropriate therapy and can reveal specific genetic changes that enable personalized treatment. In recent years, the digitalization of pathology has led to a transformation: Microscopes have been replaced by digital screens on which tissue sections are analyzed. This digitalization is an important step towards the effective use of advanced analytical techniques such as AI.

Advantages of the AI-based platform

Advantages of the AI-based platform

The AI-supported platform of the University Hospital of Cologne offers several advantages:

Automated analysis: the platform enables fast and fully automated analysis of digitized tissue sections, which increases the speed of diagnosis, and reduces the error rate.

Additional information: By using AI, additional information about the cancer can be obtained that could not be collected using conventional methods. This information can help to develop personalized therapeutic approaches.

Development of new clinical tools: We also show how the platform could be used to develop new clinical tools. The new tools can not only improve the quality of diagnosis, but also provide new types of information about the patient’s disease, such as how the patient is responding to treatment,” says Dr. Yuri Tolkach, senior physician and head of the study.

Validation study and future applications

In order to prove the broad applicability of the platform, the research team is planning a validation study in collaboration with five pathology institutes from Germany, Austria and Japan. This study should further confirm the efficiency and accuracy of the platform and pave the way for its use in clinical practice.

MEDICA-tradefair.com; Source: University of Cologne

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