Abstract
Background: Digital pathology is an innovative medicine diagnostic tool that enables histopathological slides to be digitized, analyzed, and communicated using whole-slide imaging (WSI). The fusion of digital microscopy and artificial intelligence (AI) technologies is transforming existing workflows, improving diagnostic accuracy, speed, and reproducibility in pathology practice.
Objective: The objectives of the current study are to determine clinical utility, diagnostic reproducibility, and work-place effectiveness of digital pathology platforms compared to conventional microscopy for histopathologic diagnosis.
Methods: Whole-slide images digitally and glass slides representing various organ systems were compared. Pathologists measured diagnostic concordance, turnaround time, and user satisfaction, while AI-assisted image analysis was applied for computerized measurement of some parameters.
Results: Digital pathology achieved 95% concordance in diagnosis with traditional microscopy. It enhanced turn-around time of reporting and case-sharing productivity by a large margin. Quantitative morphometry of cells and tumor grading accuracy were enhanced by AI-based analysis.
Conclusion: Digital pathology is a paradigm change in the area of histopathological diagnosis. Through the assistance of AI-based analysis, it provides faster, standardized, and reproducible report diagnosis, paving the way to the era of precision pathology and targeted therapy.
Keywords: Digital pathology, Whole-slide imaging, Artificial intelligence, Histopathology, Diagnostic accuracy, Virtual microscopy, Image analysis, Workflow efficiency, Precision medicine, Computational pathology