Histopathology images are microscopic views of specially prepared and stained slices of tissue, allowing doctors to study tissues at the cellular level. The examination of these images is known as histopathology, a field combining the study of tissues (histology) and disease (pathology). This analysis is the gold standard for diagnosing many conditions, including cancer, by revealing cellular changes invisible to the naked eye. The information from these images guides doctors in determining the best course of treatment for a patient.
From Tissue Sample to Digital View
The journey from a patient’s tissue to a viewable image is a multi-step process designed to preserve the tissue’s microscopic architecture. It begins with collecting a tissue sample through a biopsy or surgical procedure. To prevent decay, the tissue is immediately placed in a preservative solution, typically 10% neutral buffered formalin, in a process called fixation. This chemical bath stabilizes the proteins and structures within the cells for analysis.
Once fixed, the tissue specimen is trimmed and placed into a labeled plastic cassette. The sample then undergoes processing, starting with dehydration, where it is immersed in progressively stronger concentrations of alcohol to remove all water. A clearing agent like xylene is then used to remove the alcohol, preparing the tissue for embedding with molten paraffin wax. This wax hardens into a solid block, providing support to cut extremely thin sections.
Using a microtome, a technician slices the wax-embedded tissue into sections a few micrometers thick. These sections are then transferred onto glass microscope slides. Because cells are naturally transparent, the tissue must be stained to make its components visible. The most common staining method is Hematoxylin and Eosin (H&E), where Hematoxylin colors cell nuclei purplish-blue and Eosin stains the cytoplasm and connective tissue in shades of pink. The prepared slide can then be viewed under a light microscope or scanned by a whole-slide imaging (WSI) system to create a digital file.
Decoding the Cellular Landscape
When a pathologist examines a histopathology image, their analysis focuses on identifying deviations from a healthy state by evaluating several features. A primary consideration is the overall tissue architecture, which refers to how cells are organized to form tissues. In a healthy organ, this arrangement is orderly, but in diseased tissue, this structure can be disrupted or disorganized.
The pathologist then looks closer at cellular morphology—the size, shape, and appearance of individual cells. They assess whether the cells are uniform or vary significantly, a condition known as pleomorphism. Pathologists also examine nuclear features such as size, shape, and how darkly the nucleus absorbs the stain (hyperchromasia), as these are altered in cancerous cells.
By combining these observations, pathologists distinguish between normal and abnormal findings. For example, they can identify inflammation by spotting an accumulation of white blood cells. They can also detect cell death (necrosis) or see features associated with diseases like tuberculosis. In cancer diagnosis, the degree to which cancerous cells deviate from normal cells helps determine the tumor’s aggressiveness.
Diagnostic Applications
The interpretation of histopathology images is the basis for definitive diagnoses across many medical fields, with its most well-known application in oncology. When a tumor is biopsied, analysis determines if it is benign or malignant. For cancerous tumors, the image provides information on the cancer type, its grade, and can offer clues about how the cancer might respond to certain treatments.
Beyond cancer, histopathology is used to identify a wide array of other conditions. It is used to diagnose inflammatory diseases such as Crohn’s disease or autoimmune disorders like lupus by revealing characteristic inflammation patterns. Infectious diseases can also be identified, either by seeing the microorganism directly or by recognizing the cellular damage it causes, such as spotting bacteria, fungi, or viral inclusions.
Histopathology also extends to monitoring patient health over time. After an organ transplant, biopsies are periodically examined to look for signs of rejection. For patients undergoing treatment for a disease, subsequent tissue samples can show if the therapy is successfully reducing inflammation or eliminating cancerous cells, making it a valuable tool for guiding medical management.
The Impact of Computational Pathology
The field of pathology is undergoing a transformation driven by advances in digital imaging and computer science, creating computational pathology. This began with whole-slide imaging (WSI), a technology that digitizes an entire glass slide at microscopic resolution. These high-resolution images can be easily stored, shared for remote consultations, and archived for long-term study without the physical degradation that affects glass slides.
This shift to digital pathology has paved the way for integrating artificial intelligence (AI) into the diagnostic workflow. AI algorithms, based on deep learning, are trained on vast datasets of histopathology images to perform analytical tasks. These tools can assist pathologists by automatically detecting and highlighting suspicious areas on a slide, such as small clusters of cancer cells that might be missed by the human eye, which improves efficiency.
AI is also capable of performing precise quantitative analysis that is difficult for humans to do consistently. These algorithms can count specific types of cells, measure the size and shape of nuclei, or quantify the extent of certain tissue patterns. Research has shown that AI can even predict genetic mutations or patient prognosis from the visual data in an H&E stained image. These tools are not intended to replace pathologists but to augment their expertise, leading to more objective and reproducible diagnoses.