The slow-paced digital evolution of pathology: lights and shadows from a multifaceted board

Objective: The digital revolution in pathology represents an invaluable resource fto optimise costs, reduce the risk of error and improve patient care, even though it is still adopted in a minority of laboratories. Barriers include concerns about initial costs, lack of confidence in using whole slide images for primary diagnosis, and lack of guidance on transition. To address these challenges and develop a programme to facilitate the introduction of digital pathology (DP) in Italian pathology departments, a panel discussion was set up to identify the key points to be considered. Methods: On 21 July 2022, an initial conference call was held on Zoom to identify the main issues to be discussed during the face-to-face meeting. The final summit was divided into four different sessions: (I) the definition of DP, (II) practical applications of DP, (III) the use of AI in DP, (IV) DP and education. Results: Essential requirements for the implementation of DP are a fully tracked and automated workflow, selection of the appropriate scanner based on the specific needs of each department, and a strong commitment combined with coordinated teamwork (pathologists, technicians, biologists, IT service and industries). This could reduce human error, leading to the application of AI tools for diagnosis, prognosis and prediction. Open challenges are the lack of specific regulations for virtual slide storage and the optimal storage solution for large volumes of slides. Conclusion: Teamwork is key to DP transition, including close collaboration with industry. This will ease the transition and help bridge the gap that currently exists between many labs and full digitisation. The ultimate goal is to improve patient care

Lymphoma and the Kidney: A Kidney Biopsy Teaching Case

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Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP)

The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis led to increased interest in applying DP workflows. However, despite this revolutionary transition, real world data suggest that a fully digital approach to the histological workflow has been implemented in only a minority of pathology laboratories. The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation to identify: (a) the scope and the boundaries of the DP transformation; (b) how to introduce automation to reduce errors; (c) how to introduce appropriate quality control to guarantee the safety of the process and (d) the hardware and software needed to implement DP systems inside the pathology laboratory. The European Society of Digital and Integrative Pathology (ESDIP) provided consensus-based recommendations developed through discussion among members of the Scientific Committee. The recommendations are thus based on the expertise of the panel members and on the agreement obtained after virtual meetings. Prior to publication, the recommendations were reviewed by members of the ESDIP Board. The recommendations comprehensively cover every step of the implementation of the digital workflow in the anatomic pathology department, emphasizing the importance of interoperability, automation and tracking of the entire process before the introduction of a scanning facility. Compared to the available national and international guidelines, the present document represents a practical, handy reference for the correct implementation of the digital workflow in Europe.publishedVersio

Clinical audit; freehand renal biopsy, still a suitable method?

Introduction: Freehand renal biopsy represents a valid alternative to the most widespread ultrasonography-guided technique, although some concerns can derive from the possible increased complication rate and lower adequacy rate. Objectives: In the present audit study, efficacy of freehand method have been established through the analysis of 328 consecutive renal biopsies in 322 patients, instead the safety of the procedure was assessed in 196 patients. Patients and Methods: We retrospectively reviewed hospital databases of all patients who underwent a percutaneous renal biopsy over an 18 years’ period at Santa Marta and Santa Venera hospital in Acireale. Results: The procedure led to a definitive diagnosis in the majority of cases (98.48%), being uninformative only in 5 out of 328 cases (1.52%). Comparing these results against a Proforma, resulting from analysis of best literature reports for the items studied, adverse event rates were similar. Conclusion: Freehand renal biopsy resulted a good option to obtain renal tissue, without serious side effects. We argue about safety and we prefer to reserve this invasive procedure to selected cases, avoiding renal biopsy if biochemical and instrumental data allow a definitive diagnosis as well as in high risk patients. Our policy protects patients from the adverse effects that can result from kidney biopsy

Monoclonal Gammopathy of Renal Significance: A Molecular Middle Earth between Oncology, Nephrology, and Pathology

Background: The renal biopsy represents a cornerstone in the definition of monoclonal gammopathy of renal significance (MGRS), helping in identifying patients with sub-detectable neoplastic clones (MGUS) that would deserve aggressive chemotherapies. However, the rising complexity of this onco-nephrology field is significantly challenging the daily work of nephrologists and nephropathologists, leading to the formation of ultra-specialized international centers with dedicated personnel/instrumentation and stressing the need for a better understanding of the underlying molecular landscape of these entities. Summary: In this setting, the application of proteomic techniques, some with in situ capabilities (e.g., MALDI-MS imaging), for the investigation of the most challenging MGRS is progressively shedding light on the pathobiology of these diseases, providing new insights in the diagnosis and prognosis of these cases. This transformation is further enhanced by the application of next-generation digital pathology platforms, leading to a significant improvement of the cultural background for physicians thanks to second opinions, database and atlas creation, enhancement of diagnostic reports, with obvious repercussions for patients both in terms of turnaround time and appropriateness. Key Messages: The present review is aimed at bridging the gap between clinical questions (i.e., a better characterization of MGRS) and the molecular landscape of onco-nephrology entities

Real-world digital pathology: considerations and ruminations of four young pathologists

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Bowman's capsule rupture on renal biopsy improves the outcome prediction of ANCA-associated glomerulonephritis classifications

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Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP)

The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis led to increased interest in applying DP workflows. However, despite this revolutionary transition, real world data suggest that a fully digital approach to the histological workflow has been implemented in only a minority of pathology laboratories. The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation to identify: (a) the scope and the boundaries of the DP transformation; (b) how to introduce automation to reduce errors; (c) how to introduce appropriate quality control to guarantee the safety of the process and (d) the hardware and software needed to implement DP systems inside the pathology laboratory. The European Society of Digital and Integrative Pathology (ESDIP) provided consensus-based recommendations developed through discussion among members of the Scientific Committee. The recommendations are thus based on the expertise of the panel members and on the agreement obtained after virtual meetings. Prior to publication, the recommendations were reviewed by members of the ESDIP Board. The recommendations comprehensively cover every step of the implementation of the digital workflow in the anatomic pathology department, emphasizing the importance of interoperability, automation and tracking of the entire process before the introduction of a scanning facility. Compared to the available national and international guidelines, the present document represents a practical, handy reference for the correct implementation of the digital workflow in Europe

Natural Language Processing to extract SNOMED-CT codes from pathological reports

Objective: The use of standardized structured reports (SSR) and suitable terminologies like SNOMED-CT can enhance data retrieval and analysis, fostering large-scale studies and collaboration. However, the still large prevalence of narrative reports in our laboratories warrants alternative and automated labeling approaches. In this project, natural language processing (NLP) methods were used to associate SNOMED-CT codes to structured and unstructured reports from an Italian Digital Pathology Department. Methods: Two NLP-based automatic coding systems (support vector machine, SVM, and long-short term memory, LSTM) were trained and applied to a series of narrative reports. Results: The 1163 cases were tested with both algorithms, showing good performances in terms of accuracy, precision, recall, and F1 score, with SVM showing slightly better performances as compared to LSTM (0.84, 0.87, 0.83, 0.82 vs 0.83, 0.85, 0.83, 0.82, respectively). The integration of an explainability allowed identification of terms and groups of words of importance, enabling fine-tuning, balancing semantic meaning and model performance. Conclusions: AI tools allow the automatic SNOMED-CT labeling of the pathology archives, providing a retrospective fix to the large lack of organization of narrative reports