Danaher’s chief medical officer, Maximilian Schmid, says ‘infrastructure is there’ to push forward whole slide imaging.
Based on discussions at the recent Association for Diagnostics & Laboratory Medicine’s (ADLM) 2025 conference and observations from other sources, digital pathology trends continue to show sluggish adoption by clinical laboratories and anatomic pathology practices in the US. However, proponents of whole slide imaging say now is a prime opportunity to integrate the technology with a patient-centric care approach.
At least 65 vendors at the ADLM 2025 exhibitor hall indicated that their products touched whole slide imaging or digital pathology, showing this area is a hot focus for sellers.
Based on its customers, Leica has one of the largest installation bases of digital pathology scanners in the world. From that perspective, the technology is available, yet obstacles remain.
“The infrastructure is there,” said Maximilian Schmid, MD, chief medical officer at Danaher Diagnostics. “How do we bring it to the patients?”
Danaher Corporation, which held a press briefing at ADLM 2025, is parent company to Leica.
ADLM 2025 took place in Chicago July 27-31at McCormick Place. (Photo credit: Scott Wallask.)
Labcorp Report Notes Costs as a Barrier
Anyone who has followed the slow progression of digital pathology knows adoption from the diagnostic lab industry has been lukewarm. In 2024, Labcorp released a report about clinical laboratory trends that indicated cost remained a hurdle to further use of digital pathology scanners and software. Based on a survey of 115 US-based pathologists, lab managers, and lab directors, the report concluded that just 33% of respondents had started orplanned to implementdigital pathologyin lab workflows.
“Industry adoption of digital pathology has been slower than expected, largely due to high initial costs,” Deborah Sesok-Pizzini, MD, MBA, chief medical officer at Labcorp, told Today’s Clinical Lab at the time. That publication is a partner brand to Dark Daily.
Digital Pathology Trends are Rosier in Europe
Leica has been able to convey a message to its customers that despite the initial costs, the return on investment for digital pathology is high in terms of more accurate diagnoses and quicker processes, Schmid said.
“When I look ahead 10 years, digital pathology will be as normal to labs as H&E staining,” he predicted, referring to common hematoxylin and eosin stains.
He added that while Labcorp’s study reflected US trends, digital pathology adoption is stronger elsewhere, based on what Danaher and Leica see with customers.
“Europe seems to be a little bit ahead in terms digitization,” including with whole-slide imaging, he noted. However, even in the US, “academic medical centers are moving very fast in this direction.”
Schmid’s assertion about Europe is supported by other sources. For example, a business case published in July 2024 by the UK’s National Health Service (NHS) for Wales indicated that Northern Ireland and Scotland had near-fully digitized cellular pathology programs for the NHS, and England was building up its network. Wales was seen as trailing behind these countries.
“The national move towards scanning of histological material for primary diagnosis and more recently, the adoption of artificial intelligence (AI)/computational pathology to improve the accuracy, reliability and quality of reports, means that most pathologists, especially new trainees who are already using digital technology, will, in the future, choose to work in departments where digital technology will enhance and underpin their diagnosis thus benefiting the quality of patient care,” the NHS Wales business case paper stated.
Computational Pathology’s Growing Role
Computational pathology—in other words, the use of data science, information, and digital technologies for laboratory medicine—is a key to moving precision medicine forward via digital pathology, said Nicole Selenko-Gebauer, MD, MBA, group vice president and chief innovation officer at Danaher Diagnostics.
“We need to complement technology-driven focuses” with a patient-centric approach, Selenko-Gebauer added.
Even in 2022, The Dark Report had alerted its readers to the promise of computational pathology, noting Mayo Clinic Laboratories’ early success in launching related clinical assessment goals based on digital pathology and artificial intelligence. (If you’re not a Dark Report subscriber, check out our 14-day free trial.)
Taken at that viewpoint, digital pathology trends related to patient care will be an important milestone for the technology.
“A pivotal moment will be the clinical utilization of digital pathology—that it works and is accurate,” Schmid said.
Hello primary diagnosis of digital pathology images via artificial intelligence! Goodbye light microscopes!
Digital pathology is poised to take a great leap forward. Within as few as 12 months, image analysis algorithms may gain regulatory clearance in the United States for use in primary diagnosis of whole-slide images (WSIs) for certain types of cancer. Such a development will be a true revolution in surgical pathology and would signal the beginning of the end of the light microscope era.
A harbinger of this new age of digital pathology and automated image analysis is a press release issued last week by Ibex Medical Analytics of Tel Aviv, Israel. The company announced that its Galen artificial intelligence (AI)-powered platform for use in the primary diagnosis of specific cancers will undergo an accelerated review by the Food and Drug Administration (FDA).
FDA’s ‘Breakthrough Device Designation’ for Pathology AI Platform
Ibex stated that “The FDA’s Breakthrough Device Designation is granted to technologies that have the potential to provide more effective treatment or diagnosis of life-threatening diseases, such as cancer. The designation enables close collaboration with, and expedited review by, the FDA, and provides formal acknowledgement of the Galen platform’s utility and potential benefit as well as the robustness of Ibex’s clinical program.”
“All surgical pathologists should recognize that, once the FDA begins to review and clear algorithms capable of using digital pathology images to make an accurate primary diagnosis of cancer, their daily work routines will be forever changed,” stated Robert L. Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report. “Essentially, as FDA clearance is for use in clinical care, pathology image analysis algorithms powered by AI will put anatomic pathology on the road to total automation.
“Clinical laboratories have seen the same dynamic, with CBCs (complete blood counts) being a prime example. Through the 1970s, clinical laboratories employed substantial numbers of hematechnologists [hematechs],” he continued. “Hematechs used a light microscope to look at a smear of whole blood that was on a glass slide with a grid. The hematechs would manually count and record the number of red and white blood cells.
“That changed when in vitro diagnostics (IVD) manufacturers used the Coulter Principle and the Coulter Counter to automate counting the red and white blood cells in a sample, along with automatically calculating the differentials,” Michel explained. “Today, only clinical lab old-timers remember hematechs. Yet, the automation of CBCs eventually created more employment for medical technologists (MTs). That’s because the automated instruments needed to be operated by someone trained to understand the science and medicine involved in performing the assay.”
Primary Diagnosis of Cancer with an AI-Powered Algorithm
Surgical pathology is poised to go down a similar path. Use of a light microscope to conduct a manual review of glass slides will be supplanted by use of digital pathology images and the coming next generation of image analysis algorithms. Whether these algorithms are called machine learning, computational pathology, or artificial intelligence, the outcome is the same—eventually these algorithms will make an accurate primary diagnosis from a digital image, with comparable quality to a trained anatomic pathologist.
How much of a threat is automated analysis of digital pathology images? Computer scientist/engineer Ajit Singh, PhD, a partner at Artiman Ventures and an authority on digital pathology, believes that artificial intelligence is at the stage where it can be used for primary diagnosis for two types of common cancer: One is prostate cancer, and the other is dermatology.
On June 17, Ajit Singh, PhD (above), Partner at Artiman Ventures, will lead a special webinar and roundtable discussion for all surgical pathologists and their practice administrators on the coming arrival of artificial intelligence-powered algorithms to aid in the primary diagnosis of certain cancers. Regulatory approval for such solutions may happen by the end of this year. Such a development would accelerate the transition from light microscopes to a fully digital pathology workflow. Singh is shown above addressing the 2018 Executive War College. (Photo copyright: The Dark Report.)
“It is now possible to do a secondary read, and even a first read, in prostate cancer with an AI system alone. In cases where there may be uncertainty, a pathologist can review the images. Now, this is specifically for prostate cancer, and I think this is a tremendous positive development for diagnostic pathways,” he added.
Use of Digital Pathology with AI-Algorithms Changes Diagnostics
Pathologists who are wedded to their light microscopes will want to pay attention to the impending arrival of a fully digital pathology system, where glass slides are converted to whole-slide images and then digitized. From that point, the surgical pathologist becomes the coach and quarterback of an individual patient’s case. The pathologist guides the AI-powered image analysis algorithms. Based on the results, the pathologist then orders supplementary tests appropriate to developing a robust diagnosis and guiding therapeutic decisions for that patient’s cancer.
In his interview with The Dark Report, Singh explained that the first effective AI-powered algorithms in digital pathology will be developed for prostate cancer and skin cancer. Both types of cancer are much less complex than, say, breast cancer. Moreover, the AI developers have decades of prostate cancer and melanoma cases where the biopsies, diagnoses, and downstream patient outcomes create a rich data base from which the algorithms can be trained and tuned.
This webinar is organized as a roundtable discussion so participants can interact with the expert panelists. The Chair and Moderator is Ajit Singh, PhD, Adjunct Professor at the Stanford School of Medicine and Partner at Artiman Ventures.
The panelists (above) represent academic pathology, community hospital pathology, and the commercial sector. They are:
Because the arrival of automated analysis of digital pathology images will transform the daily routine of every surgical pathologist, it would be beneficial for all pathology groups to have one or more of their pathologists register and participate in this critical webinar.
The roundtable discussion will help them understand how quickly AI-powered image analysis is expected be cleared for use by the FDA in such diseases as prostate cancer and melanomas. Both types of cancers generate high volumes of case referrals to the nation’s pathologists, so potential for disruption to long-standing client relationships, and the possible loss of revenue for pathology groups that delay their adoption of digital pathology, can be significant.
On the flip side, community pathology groups that jump on the digital pathology bandwagon early and with the right preparation will be positioned to build stronger client relationships, increase subspecialty case referrals, and generate additional streams of revenue that boost partner compensation within their group.
Also, because so many pathologists are working remotely, Dark Daily has arranged special group rates for pathology practices that would like their surgical pathologists to participate in this important webinar and roundtable discussion on AI-powered primary diagnosis of pathology images. Inquire at info@darkreport.com or call 512-264-7103.
