Cooperation to accelerate adoption of AI-powered digital pathology

Cooperation to accelerate adoption of AI-powered digital pathology

Ibex’s Galen platform adds AI-powered cancer detection, case prioritization, grading and other productivity-enhancing insights. Users have reported significant improvements in diagnostic efficiency, with 27% reduction in time-to-diagnosis compared to conventional microscope viewing, 1- to 2-day reductions in total turnaround time, and 37% productivity gain3. In addition to cancer, the AI platform supports pathologists in the accurate grading, as well as detection and diagnosis of multiple clinical features, such as tumor size, perineural invasion, high-grade PIN (Prostatic Intraepithelial Neoplasia) and more. The accuracy level of Galen Prostate for cancer detection was the highest level reported in the field, with a sensitivity rate of 98.46%, specificity of 97.33% and an AUC of 0.991 4. When used as an automated ‘second read,’ the platform alerts pathologists when discrepancies between their diagnosis and the AI algorithm’s findings are detected, providing a safety net against error or misdiagnosis, previously reported as high as 12%5, and increasing overall quality of care. “We have been using Philips’ IntelliSite Pathology Solution together with Ibex’s Galen platform as part of our routine practice since 2020, and this ‘second read’ implementation has already helped us improve our diagnostic quality,” said Delphine Raoux, MD, pathologist and Head of Innovation Technologies at Medipath, the largest network of private pathology labs in France. “The work we presented recently showed that Ibex’s AI platform can further provide significant productivity gains when used during primary diagnosis and helps us reduce total turnaround time. This is an important step forward as we look for new technologies that can help meet an increasing demand for pathology services and could enable seamless remote reading of biopsies in times of Covid restrictions.”

Philips digital pathology solution is a comprehensive turnkey solution that helps to speed and simplify access to histopathology information across cancer care and beyond, supports full-scale digitization of histology in pathology labs and lab networks, and help increases workflow efficiency. At the heart is Philips IntelliSite Pathology Solution, which comprises an ultra-fast pathology slide scanner, an image management system and display6, which includes advanced software tools to manage slide scanning, image storage, case review, and the sharing of patient information. By fully digitizing post-sample-preparation histopathology, it facilitates the streamlining of pathology workflows and enables the connectivity needed between multi-disciplinary teams and specialties when making complex cancer diagnosis and treatment decisions, from early detection and precision diagnosis through to precision treatment and predictable outcomes.

Through breakthrough innovations and partnerships, Philips integrates intelligence and automation into its Precision Diagnosis portfolio, including smart diagnostic systems, integrated workflow solutions that transform departmental operations, advanced informatics that provides diagnostic confidence, and care pathway solutions that allow medical professionals to tailor treatment to individual patients. By developing and integrating these AI-enabled applications, the company aims to enhance the ability to turn data into actionable insights and drive the right care in the right sequence at the right time.

1 Galen Prostate is CE marked and approved in additional territories. Galen Prostate is not FDA approved and is for Research Use Only (RUO) in the United States. 

2 Survey with 52 physicians in Europe, 2018. Results are specific to the institution where they were obtained and may not reflect the results achievable at other institutions.

Raoux D, et al, Novel AI Based Solution for Supporting Primary Diagnosis of Prostate Cancer Increases the Accuracy and Efficiency of Reporting in Clinical Routine

The Lancet Digital Health, Aug 2020, Pantanowitz et al, An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study

Laifenfeld D et al, Performance of an AI-based cancer diagnosis system in France’s largest network of pathology institutes

6 The display is part of the medical device in the United States.

Source: Philips

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