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

CoronaCare is designed to help healthcare providers track COVID-19 (coronavirus) related symptoms of potentially infected patients. The platform enables communication with patients outside of facility walls and the ability to request the return of high-risk patients for more in-depth care. #COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Coronavirus (COVID-19) | March 27, 2020
March 27, 2020 — PaxeraHealth has spent years building and be
AI vendor Infervision's InferRead CT Pneumonia software uses artificial intelligence-assisted diagnosis to improve the overall efficiency of the radiology department. It is being developed in China as a high sensitivity detection aid for novel coronavirus pneumonia (COVID-19). #COVID19 #coronavirus #SARScov2

AI vendor Infervision's InferRead CT Pneumonia software uses artificial intelligence-assisted diagnosis to improve the overall efficiency of the radiology department. It is being developed in China as a high sensitivity detection aid for novel coronavirus pneumonia (COVID-19).

Feature | Coronavirus (COVID-19) | March 27, 2020 | Jilian Liu, M.D., HIMSS Greater China
An older couple walked into the Hubei Provincial Hospital of Integrated Chinese and Western Medicine near their neigh
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Typical CT imaging features for COVID-19. Unenhanced, thin-section axial images of the lungs in a 52-year-old man with a positive RT-PCR (A-D) show bilateral, multifocal rounded (asterisks) and peripheral GGO (arrows) with superimposed interlobular septal thickening and visible intralobular lines (“crazy-paving”). Routine screening CT for diagnosis or exclusion of COVID-19 is currently not recommended by most professional organizations or the US Centers for Disease Control and Prevention. Image courtesy of RSNA

News | Coronavirus (COVID-19) | March 26, 2020
March 26, 2020 — The Radiological Society of North America (RSNA
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Artificial Intelligence | March 24, 2020
March 24, 2020 — Qure.ai, a leading healthcare...
Instant triage capability could potentially speed up diagnosis of COVID-19 individuals and ensure resources allocated properly.
News | Artificial Intelligence | March 23, 2020
March 23, 2020 — behold.ai announced that its artificial intellige
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Representative examples of the attention heatmaps generated using Grad-CAM method for (a) COVID-19, (b) CAP, and (c) Non-Pneumonia. The heatmaps are standard Jet colormap and overlapped on the original image, the red color highlights the activation region associated with the predicted class. COVID-19 = coronavirus disease 2019, CAP = community acquired pneumonia. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — An arti...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Series CT scans in 35-year-old woman with COVID-19 pneumonia. (a) Scan obtained on illness days 1 showed multiple pure ground-glass opacity (GGO) mainly in right lower lobe. (b) Scan obtained on illness days 5 showed increased extent of GGO and early consolidation. (c) Scan obtained on illness days 11 showed multiple consolidation with almost the same extent. (d) Scan obtained on illness days 15 showed a mixed pattern with a slightly smaller extent, and the perilobular consolidation might suggest the presence of organizing pneumonia. The patient was discharged on illness days 17. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — In a new study pub
Varian received FDA clearance for its Ethos therapy in February 2020. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Feature | Treatment Planning | March 19, 2020 | Dave Fornell, Editor
The traditional treatment planning process takes days to create an optimized radiation therapy delivery plan, but new