The US is entering a new era of cancer care, with diagnoses expected to exceed 2 million cases annually. Technologies such as multicancer early detection, liquid biopsy, and precision medicine are enabling earlier detection while increasing pathologists’ involvement in testing. As a result, laboratories face rising case volumes, more follow-up testing, and increasingly complex reimbursement challenges.
Here, Shakti Ramkissoon, Senior Vice President of Enterprise Oncology at Labcorp, discusses laboratory workforce challenges and how digital pathology can support the diagnostic pathway while prioritizing patient care.
As earlier cancer detection brings more patients into the diagnostic pathway, how will this affect pathologists’ workloads?
Early cancer detection is good for patients. It is something we have pursued for a long time: using advanced technology to improve care and outcomes while making testing more widely available. The sooner we find a cancer, the better.
However, earlier detection also creates challenges for pathologists. More patients will enter the diagnostic pathway, often with subtle or borderline lesions that may not have been biopsied in the past. This will increase both specimen volumes and the number of complex biopsies and diagnostic workups.
The pathologist’s role will therefore continue to evolve. Diagnosis will increasingly require us to combine morphology with molecular profiling, germline testing, and other investigations. We will then need to bring those findings together into a clear, accessible report that oncologists can use when discussing care with their patients.
Early detection does not simply mean more specimens. It means more complex diagnostic decisions and greater involvement for pathologists across the patient’s care pathway.
How can laboratories adopt new cancer detection technologies while helping pathologists keep pace with growing demand?
This will require careful thought. Laboratories are very good at introducing new tests, but we should not treat every innovation as simply another assay. Each test creates its own workflow, from ordering and specimen collection through analysis, reporting, integration with the electronic medical record, and clinical interpretation.
In the past, laboratories may have focused on developing and launching the assay itself. We now need to design the supporting workflow at the same time, so the test can be incorporated into daily pathology practice without creating unnecessary complexity. Automation, digital case management, and interoperability between systems will be increasingly important.
Tissue stewardship is another key consideration. Earlier detection is likely to produce smaller lesions and biopsies, leaving a limited amount of tissue for testing. Laboratories will need to determine which tests to perform, in what order, and how to combine the results to reach a diagnosis. We should therefore validate not only the test but also the entire workflow around it.
How can digital pathology and remote slide reading help address workforce shortages and increase diagnostic capacity?
Digital pathology is particularly exciting because it can remove some of the barriers built into traditional pathology workflows. One important benefit is the ability to separate specialist expertise from geography. Experts may be concentrated in particular cities or institutions, and accessing their input has traditionally required laboratories to package and ship glass slides. Digitization allows cases to be shared quickly with pathologists specializing in areas such as soft tissue tumors, brain tumors, or hematologic malignancies, wherever they are located.
Digital pathology could also support distributed workflows. Cases might be shared across locations and time zones to improve turnaround times while balancing workloads around the needs of pathologists and patients. The digital slide can move without having to transport the patient, specimen, or expert.
It also offers greater flexibility. Some pathologists will value the digital tools and AI algorithms that can be applied to whole-slide images, while others may benefit from being able to review cases remotely rather than being tied to a microscope or fixed location. This flexibility could help retain experienced pathologists and attract medical students seeking a modern, technology-enabled career. Digital technology is already part of everyday life, so it is natural for pathology practice to evolve alongside it.
How can AI, digital pathology, and genomic testing improve diagnostic accuracy and patient care?
Digital pathology, genomics, and AI are developing as separate forces, but they will be most powerful when brought together. Today, these technologies often remain disconnected: one laboratory may use an AI algorithm, another may have digital pathology, and genomic testing may be sent elsewhere.
Digital pathology creates computable images from which reproducible features can be extracted. Genomics provides insight into the molecular biology of the tumor, while AI can support pattern recognition, quantification, and other tasks that are important but difficult to perform consistently. Clinical context must also be included, drawing relevant patient information from electronic health records into the diagnostic workup.
The future is an integrated approach combining morphology, molecular and genomic findings, and clinical information. AI is less about replacing pathologists than supporting their judgment. Specimen quality, patient history, and previous therapies will still require professional interpretation. The future is not AI versus the pathologist; it is the pathologist with access to richer information and a greater role as a consultant to clinicians and patients.
What impact could these technologies have on diagnostic turnaround times?
We recently surveyed oncologists, and one of their main concerns was turnaround time. That is not surprising: clinicians need to make treatment decisions, patients are anxious, and everyone wants to provide reliable information as quickly as possible.
From a pathology and laboratory medicine perspective, however, turnaround time should be considered across the entire diagnostic pathway. It is not simply the interval between receiving a specimen and issuing a result. Delays can occur when information is incomplete, a case is placed on hold, or a report is filed in an electronic medical record where the clinician cannot easily find it.
As new technologies and tests are introduced, laboratories must consider the whole journey from order to result. Reports should reach the appropriate clinician promptly and present the findings in a form that a busy provider can readily interpret and act upon.
How can laboratories overcome barriers such as cost, reimbursement, and system integration when introducing new diagnostics?
Reimbursement is probably one of the pathologists’ least favorite topics because it is rarely covered in medical school, residency, or fellowship. It often happens in the background, and many of us only begin to understand its complexity once we enter practice.
What I have learned is that reimbursement and workflow integration cannot be treated as downstream problems. Developing a test first and considering payment only after launch does not work. Cost, reimbursement, and implementation should be addressed throughout the test’s life cycle, beginning at the concept and research-and-development stages.
A reimbursement strategy should therefore develop alongside the assay. By launch, laboratories should have analytical validation, clinical validation, and published evidence that can support adoption by clinicians and coverage decisions by payers. Evidence may also be needed to secure inclusion in clinical guidelines.
Innovation succeeds when scientific validity, clinical value, reimbursement, and workflow integration are considered together. These discussions need to move much earlier in the development process. It represents a shift in approach and gives pathologists several new areas to understand.
How do you expect the pathologist’s role to change over the next five years?
There has been considerable discussion about the shortage of pathologists and the limited number of people entering the field. However, advances in data, technology, automation, and AI could change how pathology is practiced over the next five years and beyond.
Pathologists may move from primarily describing disease to integrating its biology over time. Morphology will remain foundational, whether a slide is reviewed by a pathologist alone or with AI support. However, pathologists will increasingly need to combine histology with molecular profiling, germline findings, digital pathology, digital biomarkers, and measurable residual disease testing. This information must then be presented clearly to busy clinicians and patients, and pathologists are well positioned to do that.
Earlier cancer detection and an aging population are also likely to increase case volumes at a time when oncologists face their own workforce pressures. Pathologists can support them by bringing complex information together and making it easier to interpret and act upon.
AI could also take over repetitive but necessary tasks, such as counting features across multiple high-power fields, with greater consistency and reproducibility. This would allow pathologists to focus on understanding the patient, discussing findings with clinical teams, and ensuring that diagnostic data are communicated effectively.
Pathology has always included a consultative element, but this will become an even more important part of the profession’s future.
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