Russian Federation has created AI to help predict lung cancer metastases

Scientists at Sechenov University have developed a neural network to detect lymphovascular invasion, i.e. the penetration of cancer cells into blood vessels, in lung tissue samples of adenocarcinoma. This tumor develops in cells that secrete mucus and other bodily fluids. The development will make it possible to more accurately and quickly determine the risks of developing metastases and, if necessary, change the patient's therapy regimen.

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This will make diagnostics more efficient and allow early detection of diseases, experts say

With lymphovascular invasion, cancer cells are detected inside blood or lymphatic vessels. This is one of the unfavorable prognostic factors of the course of the disease, which requires in some cases the appointment of adjuvant, i.e. additional, therapy. However, the exact detection of invasion is difficult due to possible differences in the assessment of pathologists.

"If the tumor sprouts into the blood vessels, from there it can spread further and form metastases. Therefore, it is important to identify areas of invasion before tumor cells have entered the bloodstream - this allows you to predict the further development of the disease and adjust therapy. However, the interpretation of histologic data may differ from specialist to specialist, and there is a risk of not noticing invasion in time. Our research is aimed at creating a system for automatic assessment of invasion, which will help pathologists to obtain more objective and accurate results," Alexey Faizullin, head of the laboratory of digital microscopic analysis, explained to Izvestia.

The core of the system was a neural network, for training which scientists used 162 histoscans containing 8212 marked vessels by pathologists. The AI proved to be able to identify blood vessels and tumor invasion in them with an accuracy of more than 95%.

Read more in Izvestia's exclusive story:

Close the cell: in the Russian Federation created AI for predicting lung cancer metastases