Despite the transformation digital pathology has brought to microscopic diagnosis, the grossing room remains relatively empty of technological advancements. The 'state of gross pathology technology' initiative aims to define a framework and open the conversation for incorporating new digital technologies in grossing laboratories. Following his talk at PathVisions 2026, Dennis Strenk joins us to discuss the challenges and opportunities of adopting digital grossing.
Why has the gross room remained less digitized than other areas of pathology?
There are several reasons, but the most important is that grossing differs fundamentally from many other parts of the pathology workflow. The gross room handles physical, three-dimensional specimens that vary considerably in size, shape, orientation, texture, and clinical context. The person examining the specimen must integrate visual, tactile, anatomical, and clinical information while making decisions in real time. That level of variability is difficult to digitize. By comparison, digitizing glass slides is less complex because they are standardized in size and format.
Mindset is another factor. Grossing was long regarded as a preliminary step needed to reach the “important” part: the diagnosis. However, there is growing recognition that the quality of grossing can directly affect diagnostic accuracy. At my institution, we emphasize to residents that much of the information needed for staging comes from the gross specimen.
The answer is not simply to digitize the gross room. The more useful questions are which aspects of grossing technology can improve and how those tools can be introduced without disrupting the professional judgment that makes gross examination valuable.
What are the main trends shaping digital grossing, and which technologies are having the greatest impact?
I group current trends into three categories: intake, integration, and intelligence. Intake technologies document the specimen; integration brings that information together in an accessible form; and intelligence applies computational tools and AI to the data.
Most innovation currently falls within the intake category. This includes digital photography with advanced annotation tools and the growing use of specimen radiography. New technologies can also make lymph nodes easier to identify, while advances in three-dimensional imaging offer additional ways to document specimens.
Gross-description tools are developing as well. Voice-recognition software now supports more advanced templates and commands, while smart templates can adapt to the information entered. Structured data formats may also improve the consistency and accessibility of gross findings.
These technologies help document the specimen, but the next step is extracting useful information from those records. The data can inform the current case while also supporting research, quality improvement, and drug development.
How can digital infrastructure modernize the grossing room and connect specimen examination more effectively with downstream diagnostic workflows?
The gross room should not be viewed as an isolated step before the “real” pathology workflow begins. It is the first major opportunity to capture information about a specimen.
A digitally enabled gross room could create a more efficient flow of information from the intact specimen through the entire pathology process. This requires interoperability – the integration category I mentioned earlier. Images, measurements, annotations, sampling details, and other observations must remain linked to the specimen and accessible throughout the workflow, rather than being trapped in a standalone camera or workstation.
This is where digital infrastructure could have the greatest effect. Instead of asking how to place a camera in the gross room, we should ask how to create a connected information pathway from the specimen to the finished slide. A digital camera can improve documentation, but an integrated digital grossing system could improve the entire workflow.
Where could imaging, digital workstations, and computational tools improve measurement, documentation, and diagnostic consistency?
Measurement is an obvious opportunity. Digital imaging could make measurements more reproducible and quantify features that are difficult to estimate consistently. Some clinically important percentages are still estimated visually from gross specimens, including findings that may influence treatment. There may be more accurate ways to assess them.
Documentation is another important area. Rather than relying entirely on narrative descriptions, laboratories could capture structured information linked directly to specimen images. Annotations could identify lesions, margins, and section locations, preserving these details as part of the specimen record.
Simple computational tools could also automate small, repetitive tasks. At my institution, for example, we developed a tool that calculates the number of cassettes required for a prostate transurethral resection specimen. Similar tools could save time and improve consistency across the grossing workflow.
However, consistency does not mean replacing professional judgment with an algorithm. The aim should be to provide better information to the person making the decision.
How might digital grossing reduce cognitive burden and repetitive work while preserving professional judgment and oversight?
This is one area where technology could have an immediate impact.
Grossing involves considerable repetitive cognitive work, including measurement, documentation, specimen identification, tracking, calculations, photography, dictation, and recalling staging requirements. These tasks are important, but they do not always require the full attention of an experienced pathologists’ assistant or pathologist.
If technology can perform some of them reliably, professionals can focus on work that requires expertise: recognizing anatomy, interpreting the clinical context, identifying unusual findings, selecting appropriate tissue samples, and managing specimens that do not follow typical patterns.
I do not see the future as AI grossing instead of a pathologists’ assistant. Rather, technology could manage the parts of the workflow to which it is well suited, while the pathologists’ assistant remains responsible for decisions requiring professional judgment.
The central principle is that the human professional must be able to understand, question, and override the technology – and remain ultimately responsible for the result.
What factors determine whether these technologies can be adopted successfully across academic, community, and resource-limited laboratories?
The first question should always be: What problem are we trying to solve? A technology may be impressive but still offer little value if it does not address a meaningful laboratory need.
Cost is an important consideration, but it is only one part of adoption. Leadership support may have an even greater influence, making a clear business case essential. Reliable IT support is also critical, particularly when introducing software-based tools.
The effect on workflow must be evaluated carefully. New technology should make processes faster, more accurate, or both. If it introduces additional steps and delays, it may not be the right solution. Laboratories therefore need to test new tools within their own workflows before adopting them.
I am particularly interested in small technologies that solve specific problems within an integrated system. Not every laboratory needs a fully automated gross room. A simple tool that saves time and improves accuracy may provide considerable value. Technology should fit the laboratory’s staff and processes rather than requiring the entire service to reorganize around it.
The best approach will vary by setting. Academic centers often have the expertise and resources to pilot new tools. Community laboratories may have simpler workflows but less IT and staffing support, so technologies must require minimal setup. In resource-limited settings, cost and infrastructure are often the main constraints, making small, focused tools a practical starting point.
How do you expect the grossing room to evolve over the next five years, and what could this mean for turnaround times, diagnostic quality, and patient care?
Over the next five years, I expect change to come less from a single transformative technology and more from the gradual convergence of several tools. These may include more advanced imaging, digital documentation, computational and AI-assisted analysis, closer integration with laboratory information systems, and greater automation of repetitive physical and cognitive tasks.
The gross room could become a more data-rich environment. Rather than producing only a written description and selected tissue blocks, it could generate a structured digital record containing images, measurements, annotations, sampling details, and other information that remains connected to the case throughout the pathology workflow.
These developments may improve turnaround times, but the greater opportunities are consistency and quality. Better specimen tracking, standardized measurements, clearer sampling records, and less repetitive work could allow pathologists’ assistants and pathologists to focus on decisions that require their expertise.
Modernization should not be pursued for its own sake. Every change must provide a meaningful benefit for the patient. The future is not a gross room without pathologists’ assistants or pathologists, but one in which they have better information, better tools, and more time to apply their professional judgment.
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