Light microscopy is still considered the gold standard in pathology even though acceleration of technical progress in diagnostic disciplines, has enormously increased during recent years. Digital pathology (DP) is the integrated use of technology to assist in the creation, sharing, and exchange of information, including data and images, and to support the complex workflow, which ranges from receipt of study material to submission of the final report. DP can also improve diagnostic reliability and reproducibility: in certain cases, computers can fulfill tedious tasks more objectively and more rapidly. DP can be considered as one of the very first attempt in the field of applied artificial intelligence (AI). AI has a great potential as a data-driven DP approach, indeed its use in DP is referred to as the third major revolution in pathology after the introduction of immunohistochemistry in the 1980s and molecular pathology in the 1990s. Aim of our project is to build a DP network among four Pathology Units. The DP network will support second opinion consultation between pathologists from the four Units making available different expertise. The archival library of digital slides will permit remote learning both for medical students and pathology residents; it could help in the scientific exchange with colleagues in multidisciplinary tumor board (MTB) conferences. Real time frozen section intraoperative consultation from specialists at other institutions could also be possible thus reducing the risk of diagnostic errors and pitfalls. Archival digitized cases could provide an excellent source of datasets for the development and training of AI.
DP will open up to new diagnostic possibilities and with real-time integration in existing clinical infrastructures will allow telemedical applications, automated image evaluations with benefits both in the patient care and in medical education.
DP will open up to new diagnostic possibilities. Differentiated work processes of DP with real-time integration in existing clinical infrastructures will allow a practical and widely accepted implementation of DP based on international standards. Telemedical applications of DP, automated image evaluations, or three-dimensional views are developed and will be validated for specific purposes. It can be anticipated that patient care will benefit as much as medical education - directly and indirectly.