Pathology plays a critical role in cancer care, encompassing the development of new treatments, diagnosis, staging, grading of disease, and clinical decision-making. While histopathological slides of tissue biopsies using hematoxylin and eosin staining and immunohistochemical staining remain central to this process, the rise of precision medicine testing is placing greater demands on pathology labs. Health care organizations globally are grappling with ways to address these challenges, mainly due to the declining number of individuals choosing pathology as a specialty. Additional challenges include the rising incidence of cancer, increased testing rates, and the growing complexity of testing. In this evolving landscape, artificial intelligence is emerging to revolutionize pathology, meeting these demands and improving patient outcomes.
Digitalization and AI in pathology
Many research and clinical labs aim to enhance workflow efficiency and improve analytical quality by digitalizing processes to address the growing demand amid limited resources. This approach leverages computational resources to reduce the burden on individual pathologists, enabling them to focus their expertise where it is most impactful. Following the evolutionary path of radiological and cardiological imaging, pathologists have embraced digital pathology and AI as a significant step forward in histopathology. This also aims to enhance communication between specialists across the health care spectrum, both within pathology and beyond. The goal is to achieve faster, more consistent quality diagnoses.
Central to the evolution of digital pathology is whole slide imaging, which uses high-resolution scanners to capture and digitally stitch together microscopy images of tissue samples. Images can be taken at varying magnifications, offering insights from tissue morphology and immune invasion to nuclear identity and biomarker localization. Beyond its cartographic analog, WSI can provide 3D insights by altering image focus along a tissue’s z-axis (z-stacking), essential for characterizing the tumor microenvironment.
Advantages of digital pathology
One key advantage of digitalization is that it facilitates remote consultation and telepathology. It allows pathologists to easily connect with colleagues for opinions on patient biopsies and enables research collaborators to share and discuss experimental findings. It also helps centralize the analysis of samples taken at different locations within a health care network.
While physical slides may degrade over time due to environmental factors such as light and temperature or administrative challenges like mislabeling or breakage, WSI digitally preserves them within an archive. This allows for analysis years after their original retrieval and, if desired, connection to other patient information, such as electronic health records.
A forward-thinking company in this area is Hamamatsu. Their advanced digital pathology solutions, including high-resolution WSI scanners, are helping pathologists in their work diagnosing cancer. The tools enhance workflow efficiency, provide diagnostic accuracy, and are designed for interoperability with other digital pathology and laboratory information systems, ensuring seamless integration into existing workflows and reduced diagnosis turnaround times.
Laura Pagano, vice president at Hamamatsu Corp., commented on the impact of their solution: “Time is critical for patients and clinicians when awaiting a diagnosis. Our slide scanner digital pathology products are revolutionizing the diagnostic process, enabling fast turnaround times, more efficient workflows, and more collaboration among pathologists worldwide. We are committed to facilitating the adoption of this transformative technology to help pathologists improve patient care and patient outcomes for every patient and, ultimately, anywhere in the world.”
While WSI offers pathologists a wealth of information, providing a richer picture of a tissue sample, this abundance can also overwhelm the analytical process. For example, because WSI involves scanning an entire microscope slide to create a high-resolution digital image, this process increases the amount of data by providing more cells to analyze. This can complicate the analysis process for pathologists who need to focus on specific, clinically relevant regions of interest of the tissue sample. This is where advances in AI offer possible solutions.
Douglas Clark, MD, chief pathologist of the companion diagnostics division at Agilent, remarked on the advances AI can present: “With an extensive career as a practicing pathologist and wide-ranging experience in the field, I see immense potential in integrating AI with digital pathology. Whole slide images contain vast information, and AI empowers pathologists to harness this wealth of data to enhance their diagnoses. It also opens the door to developing superior IHC-based companion diagnostics that are even more predictive of patient responses. Furthermore, AI has the potential to streamline pathology workflows, from analyzing stained slides to delivering accurate diagnoses. By leveraging AI, we can improve diagnostic accuracy and reduce turnaround times.”
He added, “Industry collaborations are one of the key driving forces behind advancements in digital pathology. These partnerships foster innovation, accelerate the development of cutting-edge diagnostic tools, and ensure that groundbreaking technologies are seamlessly integrated into clinical practice. Together, we are revolutionizing the field of pathology and transforming patient care on a global scale.”
AI algorithms and their benefits
Trained digital pathology algorithms such as those from Visiopharm can automate various steps in the analysis process, such as identifying and quantifying different cell types and nuclear morphologies within a tissue, defining regions of tumor versus nontumor, highlighting immune infiltration, indicating the location and intensity of immunohistochemical stains and biomarkers, and enumerating mitotic status and other features that inform a pathologist’s interpretation of a slide. Quantifying these key characteristics allows pathologists to focus their energies and expertise on a more detailed, qualitative analysis of ROIs. In this way, AI doesn’t replace the pathologist but facilitates their efforts, creating what has been described as augmented intelligence.
Digital pathology, incorporating AI, is transforming the landscape of cancer diagnostics. By leveraging AI to analyze complex tissue samples, pathologists can deliver faster and more accurate diagnoses, ultimately improving patient care. A global commitment is required to drive innovation in pathology, ensuring health care providers have the resources to meet increasing cancer care demands.