Automated Strategy for Tissue Analysis in Anatomic Pathology: Fiducial Marker Integration and Multisurface Tissue Comparison

In anatomic pathology laboratories, several processes are still manual. Automated solutions can help standardizing the fabrication/processing of paraffin-embedded tissue blocks (PETBs) for a reliable and more effective diagnosis, in accordance with the requirement to work with unique and heterogeneous biological samples. We present a novel and automated approach to introduce a fiducial marker within PETBs, serving as a reliable reference point. This would assist the clinician in identifying specific regions of biological tissue in paraffin-embedded tissue blocks and paraffin-free tissue slices, in case the patient requires further laboratory analysis on that tissue portion to indicate a tailored treatment (e.g., oncological treatment). Two automated platforms are integrated into the conventional anatomic pathology workflow, according to the proposed strategy. The first one, named 'Indexing', involves the insertion of a fiducial marker into tissue-free areas within PETBs. The second one, named 'Virtual marker reconstruction', is based on image analysis and virtually reconstructs the fiducial marker on the paraffin-free tissue slice. An algorithm that analyzes the similarity of the tissue was also developed to assist in the traceability of the biological tissue along its processing from the embedding to the post-staining phase. Together, these platforms could assist the work of anatomopathologists avoid errors and support the final diagnosis in a future automated laboratory. Note to Practitioners - This research addresses a specific challenge encountered in anatomic pathology laboratories. The manual procedures involved in the fabrication and processing of paraffin-embedded tissue blocks highlight the pressing need for continuous verification and traceability at various stages of tissue processing and analysis. A lack of proper traceability poses challenges for anatomopathologists, leading to difficulties in managing the accurate identification of tissue blocks and slices, which contain unique biological tissues. This deficiency may lead to delayed or inaccurate diagnoses, with severe consequences for patients. We propose an innovative solution that focuses on two automated platforms that can seamlessly integrate into an anatomic pathology laboratory, and provide a way to correctly recognize and monitor biological tissue all along different procedures.