Summary: Researchers have developed an AI-driven digital pathology platform that enables fully automated, rapid, and accurate analysis of lung cancer tissue, offering new insights into diagnosis and patient treatment.
Takeaways:
- Advanced AI Algorithms: The platform utilizes newly developed AI algorithms to digitize and analyze lung cancer tissue, enhancing diagnostic accuracy and speed.
- Personalized Treatment Insights: The AI-driven analysis provides pathologists with molecularly specific information, paving the way for personalized therapy options for lung cancer patients.
- Global Validation Study: The research team plans to validate the platform’s broad applicability through collaboration with pathological institutes in Germany, Austria, and Japan.
A team of researchers created a digital pathology platform based on artificial intelligence, which uses new algorithms developed by the team and enables fully automated analysis of tissue sections from lung cancer patients.
The platform, created by researchers from the University of Cologne’s Faculty of Medicine and University Hospital Cologne—led by Yuri Tolkach, MD, and Professor Reinhard Büttner, MD—makes it possible to analyse digitized tissue samples on the computer for lung tumours more quickly and accurately than before. The study ‘Next generation lung cancer pathology: development and validation of diagnostic and prognostic algorithms’ has been published in the journal Cell Reports Medicine.
Identification and Treatment of Lung Cancer
Lung cancer is one of the most common tumors/cancers in humans and has a very high mortality rate. Today, the choice of treatment for patients with lung cancer is determined by pathological examination. Pathologists can also identify molecularly specific genetic changes that allow for personalized therapy. Over the past few years, pathology has undergone a digital transformation.
As a result, microscopes are no longer needed. Typical tissue sections are digitized and then analyzed on a computer screen. Digitalization is crucial for the application of advanced analytical methods based on artificial intelligence. By using artificial intelligence, additional information about the cancer can be extracted from pathological tissue sections – something that would not be possible without AI technology.
“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 Tolkach from the Institute of General Pathology and Pathological Anatomy at University Hospital Cologne, who led the study.
In order to prove the broad applicability of the platform, the research team will conduct a validation study together with five pathological institutes in Germany, Austria, and Japan.
Featured image: The image shows how the algorithm processes the typically coloured tissue section (left) and creates a map in which different types of tissue can be seen in different colors (the algorithm identifies all tissue types that can be found in tissue sections). Blue is the tumor, in this case an adenocarcinoma of the lung. Orange in the vicinity of the tumor is the peritumoural tissue = microenvironment of the tumor with immune cells. Photo: Yuri Tolkach
