Charles Sternberg, Assistant Editor06.01.21
Ibex Medical Analytics, a pioneer in AI-powered cancer diagnostics, has received a CE Mark for the Galen Breast solution for use in supporting pathologists in detection of various types of breast cancer.
The solution is now generally available as Ibex partners with laboratories, hospitals and health systems to implement artificial intelligence (AI) technology into the diagnostic workflow. Galen Breast has already been ordered by multiple labs, including a network-wide deployment at a leading pathology group in Europe.
The CE Mark follows results from a blinded, multi-site clinical study at Institut Curie in France and Maccabi Healthcare Services in Israel. Galen Breast demonstrated very high accuracy in detecting various types of breast cancer, including invasive and in-situ cancers, distinguishing between different types of invasive cancer (e.g., lobular versus ductal carcinoma) and grading of DCIS lesions. These results validate the robustness of Galen Breast and support its adoption by pathology institutes that aim to improve their diagnostic accuracy by enhancing quality control with AI.
Detecting Cancer Accurately and Rapidly
Breast cancer is the most common malignant disease in women worldwide, with over two million new cases each year. As such, accurate and timely diagnosis of breast cancer is instrumental in guiding treatment decisions and improving patient survival rates. Additionally, over the last several years there has been an increase in the number of cancer cases and together with rapid advances in personalized medicine, this has resulted in increases in the complexity of cancer diagnosis. Coupled with a global decline in the number of pathologists, these trends have led to growing workloads imposed on pathology labs and health systems. Clearly, there is a growing need for automated solutions and decision-support tools that help pathologists detect cancer to the utmost accuracy more rapidly, while enabling comprehensive and affordable quality control.
Ibex transforms cancer diagnosis by harnessing unique AI and machine learning technology at an unprecedented scale. Galen Breast is the first AI solution used for detection of breast cancer in pathology. It was developed utilizing AI and machine learning techniques, and was trained on hundreds of thousands of image samples, scanned from biopsy slides digitized using digital pathology. Galen Breast is already deployed in routine clinical practice at multiple pathology labs globally where it is used as a second read application for real-time quality control, helping pathologists improve diagnostic accuracy.
“We are impressed with the successful study outcomes and performance of Galen Breast, which were in near perfect concordance with the consensus diagnosis between pathologists in distinguishing between malignant and benign biopsies, and between invasive and in-situ carcinoma and other histological types,” said Anne Vincent-Salomon, MD, director of Pathology at Institut Curie and the principal investigator in the study. “Our team demonstrated that Ibex’s AI technology goes beyond detecting cancer and provides accurate insights on the type of tumor, the nuclear grading of in situ carcinomas and more. I’m confident that artificial intelligence will support breast pathologists and provide benefit to cancer patients across multiple segments of the diagnostic workflow and look forward to seeing this technology widely adopted in the field.”
“In this age of personalized medicine, getting the most accurate and most precise diagnosis in breast pathology is more important than ever. We look forward to innovative technologies that could offer actionable insights in support of quality diagnosis,” said Stuart Schnitt, MD, chief of Breast Oncologic Pathology at the Dana-Farber/Brigham and Women's Cancer Center and professor of Pathology at Harvard Medical School. “AI has already demonstrated its immense value in helping pathologists improve the quality and efficiency of prostate cancer diagnosis. The outcomes of this breast study strongly demonstrate that Ibex’s technology is well positioned to make a similar impact on breast cancer diagnosis.”
“We are proud to have obtained this milestone CE Mark for our Galen Breast solution” said Daphna Laifenfeld, PhD, chief scientific officer at Ibex Medical Analytics, “The excellent results coming out of this study demonstrate the robustness of our Strong AI technology and enable us to offer pathologists an unprecedented breadth of features. We have secured multiple orders for Galen Breast from leading health systems in Europe, and we look forward to accelerating its deployment in the very near future.”
The solution is now generally available as Ibex partners with laboratories, hospitals and health systems to implement artificial intelligence (AI) technology into the diagnostic workflow. Galen Breast has already been ordered by multiple labs, including a network-wide deployment at a leading pathology group in Europe.
The CE Mark follows results from a blinded, multi-site clinical study at Institut Curie in France and Maccabi Healthcare Services in Israel. Galen Breast demonstrated very high accuracy in detecting various types of breast cancer, including invasive and in-situ cancers, distinguishing between different types of invasive cancer (e.g., lobular versus ductal carcinoma) and grading of DCIS lesions. These results validate the robustness of Galen Breast and support its adoption by pathology institutes that aim to improve their diagnostic accuracy by enhancing quality control with AI.
Detecting Cancer Accurately and Rapidly
Breast cancer is the most common malignant disease in women worldwide, with over two million new cases each year. As such, accurate and timely diagnosis of breast cancer is instrumental in guiding treatment decisions and improving patient survival rates. Additionally, over the last several years there has been an increase in the number of cancer cases and together with rapid advances in personalized medicine, this has resulted in increases in the complexity of cancer diagnosis. Coupled with a global decline in the number of pathologists, these trends have led to growing workloads imposed on pathology labs and health systems. Clearly, there is a growing need for automated solutions and decision-support tools that help pathologists detect cancer to the utmost accuracy more rapidly, while enabling comprehensive and affordable quality control.
Ibex transforms cancer diagnosis by harnessing unique AI and machine learning technology at an unprecedented scale. Galen Breast is the first AI solution used for detection of breast cancer in pathology. It was developed utilizing AI and machine learning techniques, and was trained on hundreds of thousands of image samples, scanned from biopsy slides digitized using digital pathology. Galen Breast is already deployed in routine clinical practice at multiple pathology labs globally where it is used as a second read application for real-time quality control, helping pathologists improve diagnostic accuracy.
“We are impressed with the successful study outcomes and performance of Galen Breast, which were in near perfect concordance with the consensus diagnosis between pathologists in distinguishing between malignant and benign biopsies, and between invasive and in-situ carcinoma and other histological types,” said Anne Vincent-Salomon, MD, director of Pathology at Institut Curie and the principal investigator in the study. “Our team demonstrated that Ibex’s AI technology goes beyond detecting cancer and provides accurate insights on the type of tumor, the nuclear grading of in situ carcinomas and more. I’m confident that artificial intelligence will support breast pathologists and provide benefit to cancer patients across multiple segments of the diagnostic workflow and look forward to seeing this technology widely adopted in the field.”
“In this age of personalized medicine, getting the most accurate and most precise diagnosis in breast pathology is more important than ever. We look forward to innovative technologies that could offer actionable insights in support of quality diagnosis,” said Stuart Schnitt, MD, chief of Breast Oncologic Pathology at the Dana-Farber/Brigham and Women's Cancer Center and professor of Pathology at Harvard Medical School. “AI has already demonstrated its immense value in helping pathologists improve the quality and efficiency of prostate cancer diagnosis. The outcomes of this breast study strongly demonstrate that Ibex’s technology is well positioned to make a similar impact on breast cancer diagnosis.”
“We are proud to have obtained this milestone CE Mark for our Galen Breast solution” said Daphna Laifenfeld, PhD, chief scientific officer at Ibex Medical Analytics, “The excellent results coming out of this study demonstrate the robustness of our Strong AI technology and enable us to offer pathologists an unprecedented breadth of features. We have secured multiple orders for Galen Breast from leading health systems in Europe, and we look forward to accelerating its deployment in the very near future.”
