Digital pathology comes with much promise to improve diagnostic work, but uptake has been slower than anticipated. This raises the question: what might convince the die-hard microscope fans to switch to digital pathology workflows?
We posed this question to DevikaGholap, Chief Product Officer at OptraSCAN. Here, she shares her insights into the evolving market of digital slide scanning technology – and why cost, quality control, and user experience are key.
What do you see as the biggest barriers to wider adoption of digital pathology?
Cost is probably the biggest barrier. Ultimately, we are asking laboratories to replace, or at least augment, a microscope that might cost a few thousand dollars with digital pathology scanners and systems that can cost many times more. That gap is significant, and it makes the business case for adoption difficult for many laboratories.
The second barrier is habit. Pathologists are accustomed to working at a microscope – physically moving the slide and using the controls to zoom in and out. Moving to a digital interface is a very different experience, so there is inevitably an adjustment period.
But I think that will change as the workforce changes. Residents and pathology students are increasingly being trained using digital pathology, and those entering practice are actively looking for laboratories where digital workflows are already established. As that generation moves into the workforce, I think we’ll see adoption accelerate considerably.
How much of the transition to digital pathology is about changing established working habits?
It’s a significant part of it. From an outsider’s perspective, seeing pathologists hunched over a microscope all day can seem unusual, but when that’s how you’ve always worked, it feels completely natural. Even something as simple as using your hands to zoom in and out becomes part of that learned hand-eye coordination.
Digital pathology changes that interaction. Instead of looking through an eyepiece and physically manipulating the microscope, you’re viewing the entire image on a screen and navigating it with a mouse or other controls. That takes some adjustment.
But habits evolve alongside technology. We’re already hearing pathologists and technicians asking for particular types of mouse or scroll functionality because that is what they have become accustomed to using. I think we’re in the middle of that transition now.
It will take time. But as more people adopt digital pathology, those habits will continue to change. Hopefully, we’ll eventually reach the point where the digital workflow feels completely natural – and going back to a microscope feels like the unfamiliar option.
How do you see AI changing whole-slide imaging and the role of the scanner?
I see scanning technology evolving to a point where the hardware and AI work hand in hand. Rather than scanning an image first and analyzing it afterwards, the two processes could happen in parallel. As the scanner captures the image, algorithms could begin analyzing it at the same time, so that by the time the image is available to the pathologist, some preliminary analysis has already been completed.
In some ways, that mimics what happens at the microscope. The eyes are viewing the sample while the brain is simultaneously interpreting what it sees. I think digital pathology needs to move towards that same model, where scanning and analysis are not separate processes.
The next step is triage. The system could potentially categorize cases based on that initial analysis – for example, separating normal from abnormal samples or tumor from non-tumor cases. Instead of coming to an unsorted worklist, the pathologist could start with a set of cases that has already undergone preliminary analysis and triage.
As pathology becomes increasingly automated, how important is quality control at the point of scanning?
One of the big challenges in digital pathology is “garbage in, garbage out.” If you start with a poor-quality slide, you’re likely to generate a poor-quality image, and any analytics you run on that image may not perform as intended. When you’re digitizing and automating a workflow, the quality of what goes in really matters.
That’s why we’re seeing slide and image quality control become a foundational feature of scanning technology. Algorithms can assess not only whether the resulting image is in focus and of sufficient quality, but also aspects of the tissue or sample preparation itself.
Traditionally, laboratories might perform manual QC on a selection of slides or images. Increasingly, that process can be automated. Once the slides have been scanned, QC algorithms can identify images that meet the required quality standards and flag those that don’t. You can then add another layer by identifying problems originating from tissue or sample preparation.
Building that intelligence into the scanner means much of this filtering can happen before a human needs to become involved. For me, that’s an important part of the case for digital pathology: automating tasks that don’t necessarily require expert input and allowing pathologists, technicians, and laboratory managers to focus their time on the cases and decisions where their expertise really matters.
What needs to change to make digital pathology more accessible to laboratories?
Cost has to come down. That was actually one of the reasons we entered this industry: we felt there was an opportunity to control costs and offer scanning technology at a price point that could make adoption more accessible.
I can’t speak for other vendors, but I do think affordability needs to become a greater focus across the industry. If scanner manufacturers can reduce the cost of these technologies, one of the biggest barriers to implementation becomes significantly smaller.
There is clearly an appetite for digital pathology. The challenge is making the technology economically viable for more laboratories. If the industry can address that, I think we’ll see many more labs willing and able to make the transition.
Looking ahead, what will be needed to realize the full potential of digital pathology?
We’ve seen enormous progress in scanning technology. There are now many high-quality scanners on the market, and I think we’re reaching a point where aspects of the hardware – optics, imaging, robotics, and mechanics – are becoming increasingly commoditized. That’s a positive development because laboratories have far more choice than they once did.
It’s becoming a little like the microscope market: there isn’t just one option capable of delivering high-quality results. There are multiple vendors and technologies for laboratories and academic institutions to consider according to their needs.
I think the next stage is about what we do with that technology. Digital pathology still has tremendous potential, but realizing it will require industry, academia, and end users to work together. Vendors need to continue listening to laboratories and developing technology around their needs, while laboratories need opportunities to evaluate, adopt, and help shape those technologies.
There is a lot of room for this field to grow. If we can build strong partnerships and mutual trust between industry, academia, and the laboratory community, I think we can move digital pathology forward together.
Newsletters
Receive the latest pathologist news, personalities, education, and career development – weekly to your inbox.
