Ibex Medical Analytics announced today that a study of its Galen Breast diagnostic solution delivered positive outcomes.
Tel Aviv, Israel-based Ibex designed its Galen platform to support pathologists in diagnosing breast, prostate, and gastric biopsies.
Galen uses AI and machine learning technology based on hundreds of thousands of image samples scanned from biopsy slides through digital pathology.
The AI technology provides accuracy, speed and objectivity, Ibex said in a news release. It aims to improve the quality of diagnosis, user experience, operational efficiency and patient outcomes.
Galen Breast, which holds CE mark approval, is generally available to laboratories and hospitals across Europe.
In a blinded, multi-site clinical study in France and Maccabi Healthcare Services in Israel, Galen Breast produced strong outcomes. The study evaluated the performance of pathologists who used Ibex AI for diagnosing breast biopsies. It compared them to pathologists who used only a microscope across multiple types of breast cancer. Those types included invasive and in-situ carcinoma. It also featured rare subtypes, such as metaplastic, mucinous and other types of breast cancer.
Results demonstrated high accuracy and utility for Galen Breast. Ibex said it established the platform’s potential for improving the quality of diagnosis compared to microscopes alone. Dr. Judith Sandbank, director of the Pathology Institute at Maccabi Healthcare Services and a principal investigator for the study, will present full results at the European Congress of Pathology which takes place in Basel, Switzerland, between Sept. 3 and Sept. 7.
“We are excited to announce this milestone results and enable breast pathologists to further adopt AI into their routine diagnosis of breast biopsies, following excellent outcomes in a clinical study,” said Chaim Linhart, co-founder and CTO of Ibex at Ibex Medical Analytics. “We believe that AI has an essential role to play in pathology and cancer diagnosis, extending beyond cancer detection to ultimately support pathologists across most of the diagnostic pathway, as demonstrated by the scope of clinical features available with Galen Breast, as well as the expansion toward automated quantification and scoring of breast biomarkers.”