Founded in 2011 by this episode’s guest, Lorcan Sherry, along with co-founder John Waller, OracleBio entered the digital pathology market with a unique value proposition – to be a contract research organization for tissue image analysis and help other organizations in their biomarker discovery work.
Pathology News is excited to announce that NationWide Laboratories, a UK-based UKAS Accredited Testing Laboratory committed to making a positive impact on one health by lending its innovative technology, and laboratory services to the digital pathology market are now included in the Pathology News Technology Buyers’ Guide with a detailed company showcase and product page. As a dedicated service provider, NationWide Laboratories offers a broad skill base of highly qualified pathologists and laboratory scientists, extending its services beyond the scope of the veterinary industry. With NationWide Laboratories as your partner, you’ll feel supported and looked after. Please contact NationWide Laboratories for more details.
Paige has been awarded the opportunity to provide, if chosen, artificial intelligence applications to leading NHS Trust labs through PathLAKE Plus, a consortium dedicated to driving AI innovation in pathology for the UK. Through the digitization of five major NHS laboratories and the formation of a computational pathology hub, PathLAKE aims to ensure that the UK is in prime position to leverage the full value of NHS pathology data to drive economic growth in health-related AI. With Paige becoming part of this computational pathology hub, 5 NHS Trust labs are now able to acquire Paige’s diagnostic AI applications to support their clinical decision-making and bring enhanced efficiency to their labs. These applications include the CE-IVD and UKCA marked Paige Prostate Suite and Paige Breast Suite. Paige represents one of only three vendors to receive this award, and the only vendor for the Lymph Node Metastasis Use Case, where Paige Breast Lymph Node has been qualified for use. This achievement not only demonstrates the high performance of Paige’s technology, but allows us to expand our reach within the UK to ultimately help pathologists help more patients. Paige and the PathLAKE Plus AI Project share a common goal of supporting pathologists through the introduction of cutting-edge AI technologies, with the ultimate aim of helping improve patient lives. We are thrilled that PathLAKE has awarded Paige the opportunity to potentially work directly with their group of NHS Trust Labs, as we believe we are the right partner to support digital transformation in pathology and bring unparalleled confidence to clinical decision making.
In a new study, researchers at the University of Texas at Dallas, USA, developed a new extended depth of field (EDOF) method for mosaic hyperspectral images. The team evaluated the performance of two fast EDOF methods and found that band-based EDOF provided the best quality reconstruction, highest speed, and lowest number of deconvolutions. The researchers believe that EDOF holds promise for accelerating whole-slide imaging (WSI). The study findings were presented at SPIE Medical Imaging 2023, which took place in San Diego on February 19–23. Hyperspectral imaging (HSI) is a c...
Human Bytes are entering a strategic partnership with US-based Paige.AI, Inc. (“Paige”) to bring their leading end-to-end digital pathology solution and clinical AI applications to Denmark and Sweden.The field of pathology is facing a growing number of challenges with increased lab testing, a growing number of cancer cases, and a reduced workforce – these challenges can only be addressed by taking the leap into the digital age. Whole slide scanners, digital worklists, advanced viewers, and AI technologies have all been developed to streamline and enhance pathology workflows.The comprehensive digital pathology solution from Paige delivers seamless integration, advanced whole slide image viewing, and access to a wide range of powerful AI applications that can revolutionize pathology workflows and increase diagnostic confidence for pathologists everywhere.“We are proud to have worked with leading healthcare systems and partners across the US and UK to advance the adoption of digital pathology and AI to support pathologists in their challenging but critical role in the cancer care continuum. We see Denmark and Sweden as a natural next frontier for continuing this global transformation, with the ultimate goal of improving patient outcomes,” said Andy Moye CEO at Paige. “Human Bytes is the right strategic partner to help us unlock this potential.”Paige’s open platform and deep partnerships with industry-leading scanner and LIS vendors makes Paige one of the most robust and easily integrated solutions on the market. The cloud storage options offer a scalable deployment model, where each scanner, department, or workflow can be connected gradually. This stepwise deployment is significantly faster than traditional implementation, and significantly accelerates the path to value, eliminating risk in procurement.The lion’s share of Paige’s value creation comes from adding the AI modules on-top, with Paige’s industry-leading AI products for prostate and breast cancer. Paige’s AI applications increase efficiency and confidence, especially across some of the more challenging aspects of cancer diagnosis such as grading. Their AI module for prostate, Paige Prostate Detect, has been found in high-profile studies to deliver a Negative Predictive Value of 100%, enabling pathologists to more quickly sign out non-suspicious tissue samples in the future, significantly increasing efficiencies.The introduction of digital pathology also opens a whole new diagnostic opportunity with biomarkers. From the first H&E-stained tissue sample, Paige’s biomarker AI applications can uncover new information that is not currently visible to the human eye through a microscope. Paige today has HER2Complete™which received CE-IVD and UKCA designations to identify patients with expression of HER2 in breast cancer.“It is a great honor to be given the opportunity to represent Paige in some Nordic countries. With their native cloud platform dedicated for pathology, driving adoption will be a catalyst for revolutionizing pathology in the coming years,” said Ulrik Therkildsen CEO at Human Bytes. “We are especially excited about the opportunity to deploy Paige gradually, significantly reducing costs and economic risks for the customers. We expect the AI modules to be a game-changer in achieving better patient outcomes and improving health economics.”SOURCE: Paige
There are now more than 520 marker-cleared artificial intelligence (AI) medical algorithms available in the United States, according to the U.S. Food and Drug Administration (FDA) as of January 2023. The vast majority of these are related to medical imaging.Here is the breakdown for the number of FDA-cleared algorithms across specialties:• Radiology 396• Cardiology 58• Hematology 14• Neurology 10• Clinical chemistry 7• Ophthalmic 7• Gastroenterology and urology 5• General and plastic surgery 5• Pathology 4• Microbiology 4• Anesthesiology 4• General Hospital 3• Orthopedic 1• Dental 1See the complete list of FDA-cleared algorithms hereThe first AI algorithm was cleared by the FDA in 1995, and fewer than 50 algorithms were approved over the next 18 years. However, the numbers have increased rapidly in the past decade, and more than half of algorithms on the U.S. market were cleared between 2019 to 2022––more than 300 apps in just four years. Last October, the FDA approved 178 new AI and machine learning (ML) systems. That number is expected to grow rapidly into the future, the FDA has said.AI and ML technologies have the potential to transform healthcare by deriving new and important insights from the vast amount of data generated during the delivery of healthcare every day. Medical device manufacturers are using these technologies to innovate their products to better assist healthcare providers and improve patient care, the FDA explained on its website.Medical imaging makes up the majority of FDA-cleared AI algorithms“Artificial intelligence is really good at discerning patterns within the data. There has been a lot of work in the medical imaging space, where AI can really help improve diagnostic capabilities with image recognition,” explained Julius Bogdan, an AI expert and vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America.HIMSS sees the movement toward wider AI adoption as one of the biggest trends in healthcare information technology (IT). The clinical side of AI requires regulatory clearance, and the majority FDA-approved algorithms are imaging related across subspecialties.AI’s high accuracy of pattern recognition has led to a concentration of market approvals on the imaging side. AI can be trained using thousands or tens of thousands in images that show the various presentations of a specific disease, such as ischemic and and hemorrhagic stroke, specific cancers, breast density or coronary shift plaque morphology. Most of the radiology applications focus on specific subspecialty imaging, such as brain, breast, cardiac, lung and stroke imaging.Not surprisingly, several of the cardiology, ophthalmic, surgical, obstetrics/gynecology, gastroenterology and urology, dental and pathology AI systems also involve medical imaging.“Today, we live in that quadrant of things humans can do and humans are supervising,” explained Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute chief science officer. Dreyer also holds the positions of vice chairman of radiology at Massachusetts General Hospital, chief data science and information officer for the departments of radiology for both Massachusetts General Hospital and Brigham and Women’s Hospital“That is all the FDA-approved AI stuff that we see today,” Dreyer said. “Even though all these FDA-approved algorithms are using AI, it is not all what most people think of, where it is making a diagnosis or finding a lesion. There is a big variety in the ways to classify AI.”The areas of AI in imaging include:• Diagnostic aids that can automatically identify critical findings.• Automation of time-consuming functions such as quantification, contouring and auto complete of text in reports.• Workflow improvements and automation.• Data mining applications.• Clinical decision support for next steps in the patient’s care or to ensure imaging exam meets the guidelines.• Modality specific AI to iso-center patients, choosing imaging protocols, or speeding MRI exam time.• AI to enhance image reconstructions to improve image quality resolution unidentify to fix imaging artifacts.• Guidance AI to help imagers get the best possible images, even if they are novice users of the system or are unfamiliar with the anatomy.• Automatic anatomical identification, labeling and contouring of organs or specific types of tissue.
In this third and last episode of the multiplex mini-series with Regan Baird from Visiopharm we look at the considerations when choosing an image analysis software for phenotyping.
In this blog post, you can learn about the latest release of HALO AP®, a CE marked, AI powered and pathologist driven image management platform from Indica Labs. We’ll discuss the new features in HALO AP 2.1, where to find training resources and documentation, and how the upgrade will be rolled out.
We are excited to announce the launch of a new Microglial Activation module for fluorescence (FL) images and an updated brightfield (BF) module! In this blog post, you can learn about some of the new features in these modules, where to find the user guides, and when to expect to upgrade.
In recent years, there has been a massive advancement in the available treatments for colon cancer. To ensure these therapies, such as immunotherapies, are effective, it is important to accurately diagnose the individual patient for providing specifically tailored treatment. Now, researchers have paired artificial intelligence (AI) with infrared (IR) imaging to develop an automated and precise method for diagnosing colon cancer and tailoring treatments to the patient. This label-free and automated technique complements existing methods for analyzing tissue samples. Over the course of the past several years, a research team at the Centre for Protein Diagnostics (PRODI) at Ruhr University Bochum (Bochum, Germany) has been working on creating a new digital imaging method known as label-free IR imaging. This method measures the genomic and proteomic composition of the examined tissue, providing molecular information based on the infrared spectra. The information is then decoded using AI and displayed as false-color images utilizing image analysis methods from the field of deep learning. The PRODI team successfully demonstrated that using deep neural networks, it was possible to effectively determine the microsatellite status, a prognostically and therapeutically relevant parameter, in colon cancer. In this process, the tissue sample passes through a standardized, user-independent, automated process and allows for spatially resolved differential classification of the tumor within an hour. On the other hand, classical diagnostics is used to determine the microsatellite status either through complex immunostaining of various proteins or via DNA analysis. The ever-improving therapy options have made fast and uncomplicated determination of such biomarkers extremely important. Based on IR microscopic data, the researchers modified, optimized, and trained neuronal networks to establish label-free diagnostics. In contrast to immunostaining, the new approach does not need dyes and is much faster than DNA analysis. “We were able to show that the accuracy of IR imaging for determining microsatellite status comes close to the most common method used in the clinic, immunostaining,” said PhD student Stephanie Schörner. Related Links:Ruhr University Bochum
