In a new study, researchers have developed a method based on artificial intelligence (AI) for histopathological diagnosis and grading of prostate cancer.
They found that the AI-system is as good at identifying and grading prostate cancer as world-leading uropathologists.
The AI-system has the potential to solve one of the bottlenecks in today’s prostate cancer histopathology by providing more accurate diagnosis and better treatment decisions.
The research was done by a team at Karolinska Institutet in Sweden and Tampere University in Finland.
A problem in today’s prostate pathology is that there is a certain degree of subjectivity in the assessments of the biopsies.
Different pathologists can reach different conclusions even though they are studying the same samples.
This leads to a clinical problem where the doctors must pick treatment based on ambiguous information.
In this context, the researchers see a big potential to use the AI-technology to increase the reproducibility of the pathological assessments.
To train and test the AI system, the researchers digitized more than 8,000 biopsies taken from some 1,200 Swedish men in the ages of 50-69 to high-resolution images using digital pathology scanners.
About 6,600 of the samples were used to train the AI system to spot the difference between biopsies with or without cancer.
The remaining samples, and additional sets of samples collected from other labs, were used to test the AI system. Its results were also compared against the assessments of 23 world-leading uro-pathologists.
The findings showed that the AI-system was near-perfect in determining whether a sample contained cancer or not, as well as in estimating the length of the cancer tumor in the biopsy.
When it comes to determining the severity of prostate cancer, the so-called Gleason score, the AI system was on par with the international experts.
The team says that it is possible to train an AI-system to detect and grade prostate cancer on the same level as leading experts.
This has the potential to significantly reduce the workload of uro-pathologists and allow them to focus on the most difficult cases.
The lead author of the study is Martin Eklund, an associate professor at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet.
The study is published in the scientific journal The Lancet Oncology.
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