News | Artificial Intelligence | December 09, 2019

Philips and Paige Team Up to Bring Artificial Intelligence (AI) to Clinical Pathology diagnostics

AI-based cancer assessment tools are poised to help pathologists improve speed and accuracy of cancer diagnostics, ultimately leading to better patient care

AI-based cancer assessment tools are poised to help pathologists improve speed and accuracy of cancer diagnostics, ultimately leading to better patient care

December 9, 2019 — Philips and Paige, a leader in computational pathology, announced a strategic collaboration to deliver clinical-grade artificial intelligence (AI) applications to pathology laboratories. These AI technologies, starting with Paige Prostate, aim to help pathologists identify, quantify and characterize cancer in tissue samples and make precise diagnoses more efficiently. This may, ultimately, positively impact pathologist’s workflow and treatment planning for patients.

Pathologists play a crucial role in the detection and diagnosis of a broad range of diseases, including cancer. The increasing number of cancer cases in the aging population, and rapid advances in personalized medicine have resulted in significant increases in the complexity of pathology diagnostics and the workload imposed on pathologists. Digital images of tissue samples make it possible for pathologists to easily diagnose these samples on a computer display using advanced imaging analysis and workflow software.

Paige’s technology has demonstrated promising results, and the collaboration aims to deliver this kind of technology into routine clinical practice. Several pathology laboratories have already converted their glass slide-based workflow to digital, using the clinically approved digital pathology solution from Philips. Once digital images are available, the CE marked Paige Prostate software is applied automatically to detect and localize prostate cancer. This technology provides pathologists with valuable information they can use in their evaluation of prostate biopsies.

“We want to empower pathologists with the latest computational pathology solutions to enhance the diagnosis and treatment of cancer,” said Marlon Thompson, Business Leader of Digital and Computational Pathology at Philips. “Through our open digital pathology platform approach, we team up with leading computational pathology solution providers, such as Paige, to create the ultimate end-to-end oncology workflow for our customers.”

“Pathology is transforming into a digital discipline and holds a strong promise for using AI solutions to aid, streamline, and enhance decision-making,” said Leo Grady, CEO of Paige. “Together with digital pathology providers, starting with Philips, one of the leaders in the clinical digital pathology space, we want to convert this promise into a clinical reality that supports pathologists and their patients.”

Philips IntelliSite Pathology Solution in combination with Paige Prostate aims to provide an intuitive digital & computational pathology workflow experience. Philips plans to offer the CE-marked Paige Prostate to European pathology labs in 2020. AI solutions for other markets and additional disease areas are expected to follow suit. Visit www.philips.com/digitalpathology and  https://paige.ai. for more information.

 

Related Content

Infervision's newly FDA approved CT lung AI application sets a new standard
News | Artificial Intelligence | July 10, 2020
July 10, 2020 — Infervision announced U.S.

Image courtesy of GE Healthcare

Feature | Mobile C-Arms | July 08, 2020 | By Melinda Taschetta-Millane
Moblie C-arms have seen several advances over the past de
At the American Association of Physicists in Medicine (AAPM) 2019 meeting, new artificial intelligence (AI) software to assist with radiotherapy treatment planning systems was highlighted. The goal of the AI-based systems is to save staff time, while still allowing clinicians to do the final patient review. 
Feature | Treatment Planning | July 08, 2020 | By Melinda Taschetta-Millane
At the American Association of Physicists in Medicine (AAPM) 201
A 3-D ultrasound system provides an effective, noninvasive way to estimate blood flow that retains its accuracy across different equipment, operators and facilities, according to a study published in the journal Radiology.

Volume flow as a function of color flow gain (at a single testing site). For each row the color flow c-plane and the computed volume flow are shown as a function of color flow gain. The c-plane is shown for four representative gain levels, whereas the computed volume flow is shown for 12–17 steps across the available gain settings. Flow was computed with (solid circles on the graphs) and without (hollow circles on the graphs) partial volume correction. Partial volume correction accounts for pixels that are only partially inside the lumen. Therefore, high gain (ie, blooming) does not result in overestimation of flow. Systems 1 and 2 converge to true flow after the lumen is filled with color pixel. System 3 is nearly constant regarding gain and underestimates the flow by approximately 17%. Shown are mean flow estimated from 20 volumes, and the error bars show standard deviation. Image courtesy of the journal Radiology

News | Ultrasound Imaging | July 01, 2020
July 1, 2020 — A 3-D ultrasound
R2* maps of healthy control participants and participants with Alzheimer disease. R2* maps are windowed between 10 and 50 sec21. Differences in iron concentration in basal ganglia are too small to allow visual separation between patients with Alzheimer disease and control participants, and iron levels strongly depend on anatomic structure and subject age. Image courtesy of Radiological Society of North America

R2* maps of healthy control participants and participants with Alzheimer disease. R2* maps are windowed between 10 and 50 sec21. Differences in iron concentration in basal ganglia are too small to allow visual separation between patients with Alzheimer disease and control participants, and iron levels strongly depend on anatomic structure and subject age. Image courtesy of Radiological Society of North America

News | Magnetic Resonance Imaging (MRI) | July 01, 2020
July 1, 2020 — Researchers using magnetic...
Imaging Artificial Intelligence (AI) provider Qure.ai announced its first US FDA 510(k) clearance for its head CT scan product qER. The US Food and Drug Administration's decision covers four critical abnormalities identified by Qure.ai's emergency room product.
News | Artificial Intelligence | June 30, 2020
June 30, 2020 — Imaging Artificial Intelligence (AI) provider Qure.ai announced its first US FDA 510(k) clearance for