The deal will enable Crosscope’s digital pathology platform to layer around Clarapath’s histology automation hardware, a combination that could improve quality and efficiencies in diagnostic services for future customers, according to a Clarapath press release.
Clarapath’s goal with its products is to automate certain manual processes in histology laboratories, while at the same time reducing variability in how specimens are processed and produced into glass slides. In an exclusive interview with Dark Daily, Eric Feinstein, CEO and President at Clarapath said he believes the resulting data about these activities can drive further changes.
“A histotechnologist turns a microtome wheel and makes decisions about a piece of tissue in real time,” noted Feinstein, who will speak at the Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management on April 25-26 in New Orleans. “All of that real-time data isn’t captured. Imagine if we could take all of that data from thousands of histotechnologists who are cutting every day and aggregate it. Then you could start drawing definitive conclusions about best practices.”
“Clarapath’s foundation is about creating consistency and standardizing steps in histology—and uncovering the data that you need in order to accomplish those goals as a whole system,” Eric Feinstein (above), CEO and President at Clarapath told Dark Daily. “A histology lab’s workflow—from when the tissue comes in to when the glass slide is produced—should all be connected.” Many processes in histology and anatomic pathology continue to be manual. Automated solutions can contribute to improved productivity and reducing variability in how individual specimens are processed. (Photo copyright: Clarapath.)
Details Behind Clarapath’s Deal to Acquire Crosscope
As part of its acquisition, Clarapath of Hawthorne, New York, has retained all of Crosscope’s employees, who are located in Mountain View, California, and Bombay, India. Financial terms of the deal were not disclosed.
Clarapath’s flagship histology automation product is SectionStar, a tissue sectioning and transfer system designed to automate inefficient and manual activities in slide processing. The device offers faster and more efficient sample processing while reducing human involvement. Clarapath expects SectionStar be on the market in 2023. The company is currently taking pre-orders.
Meanwhile, Crosscope developed Crosscope Dx, a turnkey digital pathology solution that provides workflow tools and slide management as well as AI and machine learning to assist pathologists with their medical decision-making and diagnoses.
Adoption of Digital Pathology and Automation Can Be Challenging
Digital pathology has experienced growing popularity in the post-COVID-19 pandemic world. This is not only because remote pathology case reviews have become increasingly acceptable to physicians but also because of the ongoing shortages in clinical laboratory staffing.
“A pain point today for clinicians and laboratories is labor. That’s across the board,” Feinstein said. “We can help solve that with SectionStar.”
Feinstein does not believe adoption of digital pathology and histology automation is proceeding slowly, but he does acknowledge barriers to healthcare organizations installing the technologies.
“There are lots of little things that—from a workflow perspective—people have outsized expectations about,” he explained. “Clinicians and administrators are not used to innovating in a product sense. They may be innovating on how they deliver care or treatment pathways, but they’re not used to developing an engineering product and going through alpha and beta stages. That makes adopting new technology challenging.”
Medical laboratory managers and pathologists interested in pursuing histology automation and digital pathology should first determine what processes are sub-optimal or would benefit from the standardization hardware and software can offer. Being able to articulate those gains can help build the case for a return on investment to decision-makers.
Another resource to consider: Feinstein will speak about innovations for remote histology laboratory workers at the upcoming Executive War College for Clinical Laboratory, Diagnostics, and Pathology Management on April 25-26 in New Orleans. His session is titled, “Re-engineering the Classic Histology Laboratory: Enabling the Remote Histotechnologist with New Tools That Improve Productivity, Automate Processes, and Protect Quality.”
Though smartphone apps are technically not clinical laboratory tools, anatomic pathologists and medical laboratory scientists (MLSs) may be interested to learn how health information technology (HIT), machine learning, and smartphone apps are being used to assess different aspects of individuals’ health, independent of trained healthcare professionals.
The issue that the Cedars Sinai researchers were investigating is the accuracy of patient self-reporting. Because poop can be more complicated than meets the eye, when asked to describe their bowel movements patients often find it difficult to be specific. Thus, use of a smartphone app that enables patients to accurately assess their stools in cases where watching the function of their digestive tract is relevant to their diagnoses and treatment would be a boon to precision medicine treatments of gastroenterology diseases.
“This app takes out the guesswork by using AI—not patient input—to process the images (of bowel movements) taken by the smartphone,” said gastroenterologist Mark Pimentel, MD (above), Executive Director of Cedars-Sinai’s Medically Associated Science and Technology (MAST) program and principal investigator of the study, in a news release. “The mobile app produced more accurate and complete descriptions of constipation, diarrhea, and normal stools than a patient could, and was comparable to specimen evaluations by well-trained gastroenterologists in the study.” (Photo copyright: Cedars-Sinai.)
Pros and Cons of Bristol Stool Scale
In their paper, the scientists discussed the Bristol Stool Scale (BSS), a traditional diagnostic tool for identifying stool forms into seven categories. The seven types of stool are:
Type 1: Separate hard lumps, like nuts (difficult to pass).
Type 2: Sausage-shaped, but lumpy.
Type 3: Like a sausage, but with cracks on its surface.
Type 4: Like a sausage or snake, smooth and soft (average stool).
Type 5: Soft blobs with clear cut edges.
Type 6: Fluffy pieces with ragged edges, a mushy stool (diarrhea).
Type 7: Watery, no solid pieces, entirely liquid (diarrhea).
But even with the BSS, things can get murky for patients. Inaccurate self-reporting of stool forms by people with IBS and diarrhea can make proper diagnoses difficult.
“The problem is that whenever you have a patient reporting an outcome measure, it becomes subjective rather than objective. This can impact the placebo effect,” gastroenterologist Mark Pimentel, MD, Executive Director of Cedars-Sinai’s Medically Associated Science and Technology (MAST) program and principal investigator of the study, told Healio.
Thus, according to the researchers, AI algorithms can help with diagnosis by systematically doing the assessments for the patients, News Medical reported.
30,000 Stool Images Train New App
To conduct their study, the Cedars-Sinai researchers tested an AI smartphone app developed by Dieta Health. According to Health IT Analytics, employing AI trained on 30,000 annotated stool images, the app characterizes digital images of bowel movements using five parameters:
BSS,
Consistency,
Edge fuzziness,
Fragmentation, and
Volume.
“The app used AI to train the software to detect the consistency of the stool in the toilet based on the five parameters of stool form, We then compared that with doctors who know what they are looking at,” Pimentel told Healio.
AI Assessments Comparable to Doctors, Better than Patients
According to Health IT Analytics, the researchers found that:
AI assessed the stool comparable to gastroenterologists’ assessments on BSS, consistency, fragmentation, and edge fuzziness scores.
AI and gastroenterologists had moderate-to-good agreement on volume.
AI outperformed study participant self-reports based on the BSS with 95% accuracy, compared to patients’ 89% accuracy.
Additionally, the AI outperformed humans in specificity and sensitivity as well:
Specificity (ability to correctly report a negative result) was 27% higher.
Sensitivity (ability to correctly report a positive result) was 23% higher.
“A novel smartphone application can determine BSS and other visual stool characteristics with high accuracy compared with the two expert gastroenterologists. Moreover, trained AI was superior to subject self-reporting of BSS. AI assessments could provide more objective outcome measures for stool characterization in gastroenterology,” the Cedars-Sinai researchers wrote in their paper.
“In addition to improving a physician’s ability to assess their patients’ digestive health, this app could be advantageous for clinical trials by reducing the variability of stool outcome measures,” said gastroenterologist Ali Rezaie, MD, study co-author and Medical Director of Cedars-Sinai’s GI Motility Program in the news release.
The researchers plan to seek FDA review of the mobile app.
Opportunity for Clinical Laboratories
Anatomic pathologists and clinical laboratory leaders may want to reach out to referring gastroenterologists to find out how they can help to better serve gastro patients. As the Cedars-Sinai study suggests, AI smartphone apps can perform BSS assessments as good as or better than humans and may be useful tools in the pursuit of precision medicine treatments for patient suffering from painful gastrointestinal disorders.
Fujifilm acquired Inspirata’s Dynamyx digital pathology technology and business while GE Healthcare announced a partnership with Tribun Health in Europe
Clinical pathology laboratories, especially in the US, have been slow to adopt digital imaging systems. But recent industry deals suggest that the market may soon heat up, at least in the eyes of vendors. These collaborators may hope that, by integrating diagnostic data, the accuracy and productivity of anatomic pathologists will improve while also shortening the time to diagnosis.
In the press release, Fujifilm stated that 85% of US healthcare organizations use analog systems for pathology. That compares with 86% in Europe and 90% in Asia, the company stated.
“Acquiring Inspirata’s digital pathology business allows Fujifilm to be an even stronger healthcare partner—bridging a technological gap between pathology, radiology, and oncology to facilitate a more collaborative approach to care delivery across the enterprise,” said Fujifilm CEO and president Teiichi Goto in the press release.
The press release cited data from Signify Research, a healthcare technology marketing data firm that is predicting the global market for digital pathology systems would double from $320 million in 2021 to $640 million by 2025.
Fujifilm previously had a deal with Inspirata to sell the Dynamyx system exclusively in the UK, Italy, Spain, Portugal, Belgium, the Netherlands, and Luxembourg, an August press release noted.
“A $320 million global industry in 2021 projected to reach $640 million by 2025, the rising number of cancer cases and the demonstrated benefits of digital pathology are fueling significant demand and market growth in the hospital and pharmaceutical industries,” said Henry Izawa (above), president and CEO, Fujifilm Healthcare Americas Corporation, in a press release. “These evolving clinical needs fuel Fujifilm’s investment and innovation in the digital revolution, and we look forward to introducing Dynamyx and its host of unique features and benefits to our Synapse customers and prospects as we strive to enable more efficient medical diagnosis and high-quality care.” (Photo copyright: LinkedIn.)
In announcing their new collaboration, GE Healthcare and Tribun Health said the integration of their systems—Edison Datalogue and the Tribun Health suite—would foster collaboration between pathologists and clinicians by providing a consolidated location for imaging records. This capability is especially important in oncology, they said.
“The oncology care pathway is one of the most complex with multiple steps involving a variety of specialists, complex tools, frequent decisions, and large data sets,” said GE Healthcare CEO of Enterprise Digital Solutions Nalinikanth Gollagunta in a GE press release. “With this digital pathology collaboration, we continue our journey towards simplifying the oncology care pathway with improved data management, the digitization of pathology, and streamlined data access.”
Tribun Health, based in Paris, France, offers a digital pathology platform that incorporates a camera system, artificial intelligence (AI)-based analysis, remote collaboration, and storage management, plus integration with third-party automation apps.
GE Healthcare claims that Edison Datalogue has the largest share of the Vendor Neutral Archive (VNA) market. That term refers to image archiving systems that use standard formats and interfaces instead of proprietary formats. They are an alternative to the more widely used Picture Archiving and Communications Systems (PACS) used in medical imaging.
The collaboration between the companies “is probably a strategic move to position GE as an integrator of imaging data and digital pathology data in oncology,” said Robert Michel Editor-in-Chief of Dark Daily and its sister publication The Dark Report.
GE’s History with Dynamyx
This is not GE Healthcare’s first foray into digital pathology. In fact, the company had a major hand in launching the very Dynamyx system that Fujifilm recently acquired.
In “GE Healthcare Sells Omnyx to Inspirata,” The Dark Report interviewed Inspirata CEO Satish Sanan who at that time said the acquisition would allow his company to offer “a fully integrated, end-to-end digital pathology solution” in Canada and Europe. But GE Healthcare chose to end the partnership in 2016, citing regulatory uncertainty and variable global demand. Two years later, GE sold Omnyx to Inspirata.
GE Healthcare’s new collaboration with Tribun Health shows that the company “still recognizes the value of the pathology data in cancer diagnosis and wants to be in a position to manage that digital pathology data,” Michel said.
Fujifilm’s Plans
Fujifilm said it will incorporate Dynamyx into its Synapse Enterprise Imaging suite, which includes VNA, Radiology PACS, and Cardiology PACS. “Future releases of Dynamyx will also create opportunities for Fujifilm to support pharmaceutical and contract research organizations with toxicity testing data management for drug development,” the company stated in the press release.
With its recent moves into digital pathology, Fujifilm will be taking on major competitors including Philips, Danaher, and Roche, MedTech Dive reported.
Clinical laboratories and point-of-care settings may have a new diagnostic test if this novel handheld device and related technology is validated by clinical trials
Efforts to develop breath analyzers that accurately identify viral infections, such as SARS-CoV-2 and Influenza, have been ongoing for years. The latest example is ViraWarn from Opteev Technologies in Baltimore, Maryland, and its success could lead to more follow-up PCR tests performed at clinical laboratories.
“Breath is one of the most appealing non-invasive sample types for diagnosis of infectious and non-infectious disease,” said Opteev in its FDA Pre-EUA application. “Exhaled breath is very easy to provide and is less prone to user errors. Breath contains a number of biomarkers associated with different ailments that include volatile organic compounds (VOCs), viruses, bacteria, antigens, and nucleic acid.”
Further clinical trials and the FDA Pre-EUA are needed before ViraWarn can be made available to consumers. In the meantime, Opteev announced that the CES (Consumer Electronic Show) had named ViraWarn as a 2023 Innovation Award Honoree in the digital health category.
“ViraWarn is designed to allow users an ultra-fast and convenient way to know if they are spreading a dangerous respiratory virus. With a continued increase in COVID-19 and a new surge in RSV and influenza cases, we’re eager to bring ViraWarn to market so consumers can easily blow into a personal device and find out if they are positive or negative,” said Conrad Bessemer (above), Opteev President and Co-Founder, in a news release.
Opteev is a subsidiary of Novatec, a supplier of machinery and sensor technology, and a sister company to Prophecy Sensorlytics, a wearable sensors company.
The ViraWarn breath analyzer uses a silk-based sensor that “traces the electric discharge of respiratory viruses coupled with an artificial intelligence (AI) processor to filter out any potential inaccuracies,” according to the news release.
Here is how the breath analyzer (mouthpiece, attached biosensor chamber, and attached printed circuit board chamber) is deployed by a user, according to the Opteev website:
The user turns on the device and an LED light indicates readiness.
The user blows twice into the mouthpiece.
A carbon filter stops bacteria and VOCs and allows virus particles to pass through.
As “charge carriers,” virus particles have a “cumulative charge.”
Electrical data are forwarded to the AI processor.
The AI processer delivers a result.
Within 60 seconds, a red signal indicates a positive presence of a virus and a green signal indicates negative one.
“The interaction of the virus with a specially designed liquid semiconductive medium, or a solid polymer semiconductor, generates changes in the conductivity of the electrical biosensor, which can then be picked up by electrodes. Such electrical data can be analyzed using algorithms and make a positive or negative call,” explains an Opteev white paper on the viral screening process.
While the ViraWarn breath analyzer can identify the presence of a virus, it cannot distinguish between specific viruses, the company noted. Therefore, a clinical laboratory PCR test is needed to confirm results.
Other Breath Tests
Opteev is not the only company developing diagnostic tests using breath samples.
For clinical laboratory managers and pathologists, Opteev’s ViraWarn is notable in breath diagnostics development because it is a personal hand-held tool. It empowers people to do self-tests and other disease screenings, all of which would need to be confirmed with medical laboratory testing in the case of positive results.
Further, it is important to understand that consumers are the primary target for this novel diagnostic device. This is consistent with investor-funding companies wanting to develop testing solutions that can be used by consumers. At the same time, a device like ViraWarn could be used by clinical laboratories in their patient service centers to provide rapid test results.
Google designed the suite to ease radiologists’ workload and enable easy and secure sharing of critical medical imaging; technology may eventually be adapted to pathologists’ workflow
Clinical laboratory and pathology group leaders know that Google is doing extensive research and development in the field of cancer diagnostics. For several years, the Silicon Valley giant has been focused on digital imaging and the use of artificial intelligence (AI) algorithms and machine learning to detect cancer.
Now, Google Cloud has announced it is launching a new medical imaging suite for radiologists that is aimed at making healthcare data for the diagnosis and care of cancer patients more accessible. The new suite “promises to make medical imaging data more interoperable and useful by leveraging artificial intelligence,” according to MedCity News.
In a press release, medical technology company Hologic, and healthcare provider Hackensack Meridian Health in New Jersey, announced they were the first customers to use Google Cloud’s new suite of medical imaging products.
“Hackensack Meridian Health has begun using it to detect metastasis in prostate cancer patients earlier, and Hologic is using it to strengthen its diagnostic platform that screens women for cervical cancer,” MedCity News reported.
“Google pioneered the use of AI and computer vision in Google Photos, Google Image Search, and Google Lens, and now we’re making our imaging expertise, tools, and technologies available for healthcare and life sciences enterprises,” said Alissa Hsu Lynch (above), Global Lead of Google Cloud’s MedTech Strategy and Solutions, in a press release. “Our Medical Imaging Suite shows what’s possible when tech and healthcare companies come together.” Clinical laboratory companies may find Google’s Medical Imaging Suite worth investigating. (Photo copyright: Influencive.)
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Easing the Burden on Radiologists
Clinical laboratory leaders and pathologists know that laboratory data drives most healthcare decision-making. And medical images make up 90% of all healthcare data, noted an article in Proceedings of the IEEE (Institute of Electrical and Electronics Engineers).
More importantly, medical images are growing in size and complexity. So, radiologists and medical researchers need a way to quickly interpret them and keep up with the increased workload, Google Cloud noted.
“The size and complexity of these images is huge, and, often, images stay sitting in data siloes across an organization,” said Alissa Hsu Lynch, Global Lead, MedTech Strategy and Solutions at Google, told MedCity News. “In order to make imaging data useful for AI, we have to address interoperability and standardization. This suite is designed to help healthcare organizations accelerate the development of AI so that they can enable faster, more accurate diagnosis and ease the burden for radiologists,” she added.
According to the press release, Google Cloud’s Medical Imaging Suite features include:
Imaging Storage: Easy and secure data exchange using the international DICOM (digital imaging and communications in medicine) standard for imaging. A fully managed, highly scalable, enterprise-grade development environment that includes automated DICOM de-identification. Seamless cloud data management via a cloud-native enterprise imaging PACS (picture archiving and communication system) in clinical use by radiologists.
Imaging Lab: AI-assisted annotation tools that help automate the highly manual and repetitive task of labeling medical images, and Google Cloud native integration with any DICOMweb viewer.
Imaging Datasets and Dashboards: Ability to view and search petabytes of imaging data to perform advanced analytics and create training datasets with zero operational overhead.
Imaging AI Pipelines: Accelerated development of AI pipelines to build scalable machine learning models, with 80% fewer lines of code required for custom modeling.
Imaging Deployment: Flexible options for cloud, on-prem (on-premises software), or edge deployment to allow organizations to meet diverse sovereignty, data security, and privacy requirements—while providing centralized management and policy enforcement with Google Distributed Cloud.
First Customers Deploy Suite
Hackensack Meridian Health hopes Google’s imaging suite will, eventually, enable the healthcare provider to predict factors affecting variance in prostate cancer outcomes.
“We are working toward building AI capabilities that will support image-based clinical diagnosis across a range of imaging and be an integral part of our clinical workflow,” said Sameer Sethi, Senior Vice President and Chief Data and Analytics Officer at Hackensack, in a news release.
The New Jersey healthcare network said in a statement that its work with Google Cloud includes use of AI and machine learning to enable notification of newborn congenital disorders and to predict sepsis risk in real-time.
Hologic, a medical technology company focused on women’s health, said its collaboration integrates Google Cloud AI with the company’s Genius Digital Diagnostics System.
“By complementing our expertise in diagnostics and AI with Google Cloud’s expertise in AI, we’re evolving our market-leading technologies to improve laboratory performance, healthcare provider decision making, and patient care,” said Michael Quick, Vice President of Research and Development and Innovation at Hologic, in the press release.
Hologic says its Genius Digital Diagnostics System combines AI with volumetric medical imaging to find pre-cancerous lesions and cancer cells. From a Pap test digital image, the system narrows “tens of thousands of cells down to an AI-generated gallery of the most diagnostically relevant,” according to the company website.
Hologic plans to work with Google Cloud on storage and “to improve diagnostic accuracy for those cancer images,” Hsu Lynch told MedCity News.
Medical image storage and sharing technologies like Google Cloud’s Medical Imaging Suite provide an opportunity for radiologists, researchers, and others to share critical image studies with anatomic pathologists and physicians providing care to cancer patients.
One key observation is that the primary function of this service that Google has begun to deploy is to aid in radiology workflow and productivity, and to improve the accuracy of cancer diagnoses by radiologists. Meanwhile, Google continues to employ pathologists within its medical imaging research and development teams.
Assuming that the first radiologists find the Google suite of tools effective in support of patient care, it may not be too long before Google moves to introduce an imaging suite of tools designed to aid the workflow of surgical pathologists as well.
