Precision Pathology: A New Frontier for Diagnostic Pathology

In recent years, the field of pathology has undergone a remarkable transformation, driven by advancements in technologies and our growing understanding of diseases at a molecular level. One such technology is digital pathology which enables the digitization of histopathology slides, creating vast repositories of digital images that can be analysed, shared, and utilised for research, education and diagnostic purposes. Advanced image analysis algorithms and machine learning techniques are being employed to extract valuable information from these images, aiding pathologists in making more accurate and efficient diagnoses. Precision pathology represents a shift in the way we diagnose, classify, and treat diseases. A key area of focus in precision pathology, is the utility of digital pathology and artificial intelligence as well as integration of genomic information into diagnostic and treatment decisions. By analysing the DNA and RNA profiles of tumours, researchers can identify specific genetic mutations, gene expression patterns, and molecular signatures that guide personalised treatment strategies. This can be effectively combined with AI-powered algorithms to create a “PRECISE” pathology diagnosis leading to customized treatments for individual patients, these insights allow for targeted therapies, resulting in better patient outcomes and reduced side effects. This collection of articles aims to explore the exciting developments and opportunities that precision pathology brings to the forefront of healthcare. It will delve into topics such as genomics, proteomics, and computational-enabled precise pathology diagnostics, which are revolutionizing the way we analyse and interpret pathology specimens and data. We hope that the articles featured in this collection will not only deepen your understanding of precision pathology but also inspire further research and collaboration, propelling us toward a future where personalized and targeted medicine becomes the standard of care.