The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.

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COVID‐19 vaccine‐associated clinical lymphadenopathy (C19‐LAP) and subclinical lymphadenopathy (SLDI), which are mainly detected by 18F‐FDG PET‐CT, have been observed after the introduction of RNA‐based vaccines during the pandemic. Lymph node (LN) fine needle aspiration cytology (FNAC) has been used to diagnose single cases or small series of SLDI and C19‐LAP. In this review, clinical and LN‐FNAC features of SLDI and C19‐LAP are reported and compared to non‐Covid (NC)‐LAP. A search for studies on C19‐LAP and SLDI histopathology and cytopathology was performed on PubMed and Google Scholar, on 11 January 2023. Reports on LN‐FNAC of C19‐LAP were retrieved. A total of 14 reports, plus one unpublished case of C19‐LAP observed in our institution, diagnosed by LN‐FNAC were included in a pooled analysis and compared to the corresponding histopathological reports. In total, 26 cases were included in this review, with a mean age of 50.5 years. Twenty‐one lymphadenopathies assessed by LN‐FNAC were diagnosed as benign, and three cases as atypical lymphoid hyperplasia; the latter were subsequently confirmed as benign (one by repetition of LN‐FNAC, two by histological control). One case of mediastinal lymphadenopathy in a patient suffering from melanoma was reported as reactive granulomatous inflammation, while one unsuspected case was diagnosed as metastasis from melanoma. In all cases, the cytological diagnoses were confirmed by follow‐up or excisional biopsy. The high diagnostic value of LN‐FNAC in excluding malignant processes was extremely useful in this context and may be particularly valuable when CNB or histological excisions are difficult to perform, as was the case during Covid lockdowns.

Summary 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.

Background: Eosinophilic esophagitis (EoE) is increasingly diagnosed in patients with dysphagia and upper gastroenteric symptoms. Elimination diets and/or pharmacologic agents may accomplish temporary remission, but long-term control is challenging. Type-2 immunity to ingested antigens can induce EoE histopathology via non-IgE-dependent mechanisms, possibly involving IgG4 and IL-10 production. To elucidate the contribution of IgG4- and IL-10-producing cells to EoE pathogenesis, we examined their frequencies and association with clinical and histologic endpoints in adult EoE patients given a two-food elimination diet (TFED). Methods: Sixteen patients with EoE were prescribed a TFED. Biopsies collected at baseline and follow-up were used for immunofluorescent detection of IgG4- and IL-10-expressing cells and serum food-specific IgG4 were measured. All variables were correlated with established histologic measures of disease activity. Results: Patients exhibited significant clinical improvement and significant reduction in esophageal eosinophilia and overall histology. A significant decrease in the frequencies of IL-10-expressing cells was also observed, which correlated with histologic changes. In contrast, a concomitant decline in serum and esophageal IgG4, while substantial, did not correlate with IL-10 -cell frequencies or any histologic parameter of EoE activity. Conclusions: The close association of esophageal IL-10 expression with histologic features and their changes after a TFED suggests a critical role of this cytokine in EoE pathogenesis. Conversely, IgG4 serum and mucosal expression, while reflecting the level of exposure to relevant food antigens, is not obviously related to EoE histopathology or IL-10 expression. Studies are needed to characterize IL-10 cellular sources and their functions in EoE progression and treatment response.

Digital imaging, including the use of artificial intelligence, has been increasingly applied to investigate the placenta and its related pathology. However, there has been no comprehensive review of this body of work to date. The aim of this study was to therefore review the literature regarding digital pathology of the placenta. A systematic literature search was conducted in several electronic databases. Studies involving the application of digital imaging and artificial intelligence techniques to human placental samples were retrieved and analyzed. Relevant articles were categorized by digital image technique and their relevance to studying normal and diseased placenta. Of 2008 retrieved articles, 279 were included. Digital imaging research related to the placenta was often coupled with immunohistochemistry, confocal microscopy, 3D reconstruction, and/or deep learning algorithms. By significantly increasing pathologists’ ability to recognize potentially prognostic relevant features and by lessening inter-observer variability, published data overall indicate that the application of digital pathology to placental and perinatal diseases, along with clinical and radiology correlation, has great potential to improve fetal and maternal health care including the selection of targeted therapy in high-risk pregnancy.

We describe three cases of actinomycosis of the head and neck area, clinically suspected to be malignancies, diagnosed by fine-needle aspiration (FNAC). The patients presented with painless, slowly growing masses in the cervicofacial area. Ultrasonography identified the masses as enlarged lymph nodes which were subsequently biopsied by FNAC. Cytological features were similar in all cases, with a background of granulocytes and scattered lymphocytes and histiocytes. At high magnification colonies of branching, filamentous and beaded bacteria were detected. In the Diff-Quikstained smears, these filamentous colonies showed an evident yellowish color with the typical feature of the "sulfur granules" consistent with the Splendore-Hoep-SUMMARY pli phenomenon. A diagnosis of actinomycosis was made and confirmed in all cases by the subsequent microbiological tests. The patients were treated with high-dose penicillin, which caused the masses to progressively shrink. The lymph nodal localization of cervico-facial actinomycosis may be a diagnostic challenge, because in that area, lymphadenopathies may occur both in benign and malignant conditions. FNAC is a safe, fast, and reliable method to perform an accurate diagnosis of actinomycosis avoiding the surgical excision for histological evaluation.

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