Researchers at Karolinska Institutet have developed a method based on artificial intelligence for histopathological diagnosis and grading of prostate cancer. The AI-system has the potential to solve one of the bottlenecks in today\u2019s prostate cancer histopathology by providing more accurate diagnosis and better treatment decisions. The study shows that the AI-system is as good at identifying and grading prostate cancer as world-leading uro-pathologists.
\n\u201cOur results show that it is possible to train an AI-system to detect and grade prostate cancer on the same level as leading experts,\u201d says Martin Eklund, associate professor at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet who led the study. \u201cThis has the potential to significantly reduce the workload of uro-pathologists and allow them to focus on the most difficult cases.\u201d
\nA problem in today\u2019s 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 significant potential to use the AI-technology to increase the reproducibility of the pathological assessments.
\nTo train and test the AI system, the researchers digitized more than 8000 biopsies taken from some 1200 Swedish men in the ages of 50\u201369 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 study was conducted in collaboration with researchers at Tampere University in Finland.
\nThe findings showed that the AI-system was almost near-perfect in determining whether a sample contained cancer or not, as well as in estimating the length of the cancer tumour in the biopsy. When it comes to determining the severity of the prostate cancer, the so-called Gleason score, the AI system was on par with the international experts.
\n\u201cWhen it comes to grading the severity of the prostate cancer, the AI is in the same range as international experts, which is very impressive, and when it comes to diagnostics, to determine whether or not it is cancer, the AI is simply outstanding,\u201d says Lars Egevad, professor in pathology at Karolinska Institutet and co-author of the study.
\nThe initial findings are promising but more validation is needed before the AI system may be rolled out broadly in clinical practice, according to the researchers. That is why a multicenter study spanning nine European countries is currently underway with completion slated by the end of 2020. That study, which is financed by EIT Health, aims to train the AI-system to recognize cancer in biopsies taken from different laboratories, with different types of digital scanners and with very rare growth patterns. In addition, a randomized study starting in 2020 will examine how the AI-model may be implemented in Sweden\u2019s health care system.
\n\u201cAI-based evaluation of prostate cancer biopsies could revolutionize future health care,\u201d says Henrik Gr\u00f6nberg, professor in cancer epidemiology at Karolinska Institutet and head of the Prostate Cancer Center at St G\u00f6ran Hospital in Stockholm. \u201cIt has the potential to improve the diagnostic quality, and thereby secure a more equitable care at a lower cost.\u201d Karolinska Institute<\/p>\n","protected":false},"excerpt":{"rendered":"
Researchers at Karolinska Institutet have developed a method based on artificial intelligence for histopathological diagnosis and grading of prostate cancer. The AI-system has the potential to solve one of the bottlenecks in today\u2019s prostate cancer histopathology by providing more accurate diagnosis and better treatment decisions. The study shows that the AI-system is as good at […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[35],"tags":[],"_links":{"self":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/702"}],"collection":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/comments?post=702"}],"version-history":[{"count":0,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/702\/revisions"}],"wp:attachment":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/media?parent=702"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/categories?post=702"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/tags?post=702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}