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* Context.--The purpose of this review was to compare 3 coronavirus diseases, including severe acute respiratory syndrome, Middle East respiratory syndrome, and COVID-19 caused by SARS-CoV, MERS-CoV, and SARS-CoV-2 viruses, respectively. Objective.--To cover the following topics: clinical considerations, viral characteristics, pathology, immune response, pathogenesis, and the prognosis associated with each coronavirus disease in humans. Data Sources.--Clinically, flu-like symptoms are usual at the time of presentation for all 3 diseases, but these vary from asymptomatic to severe multisystem involvement. The pathology associated with symptomatic severe acute respiratory syndrome and COVID-19 has been well described, the most prominent of which is diffuse alveolar damage. The immune response to each of these viruses is highly complex and includes both humoral and cellular components that can have a significant impact on prognosis. In severe cases of COVID-19, a dysregulated innate host immune system can initiate a hyperinflammatory syndrome dominated by endothelial dysfunction that can lead to a hypercoagulable state with microthrombi, resulting in a systemic microvascular and macrovascular disease. Conclusions.--The severe acute respiratory syndrome and Middle East respiratory syndrome epidemics have been limited, involving approximately 8000 and 2500 individuals, respectively. In contrast, COVID-19 has resulted in a worldwide pandemic with more than 177 million cases and 3.9 million deaths as of June 15, 2021, and fatality rates ranging from less than 0.1% to approximately 10% depending upon the country. Ending on a positive note, the development of a number of vaccines, at least 6 of which now are in clinical use, should mitigate and eventually control the devastating COVID-19 pandemic. doi: 10.5858/arpa.2020-0820-SA, The purpose of this review was to compare the following 3 coronavirus diseases: severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and Coronavirus Disease 2019 (COVID-19) with an [...]

Objective: The Visiopharm artificial intelligence (AI) algorithm for oestrogen receptor (ER) immunohistochemistry (IHC) in whole slide images (WSIs) has been successfully validated in surgical pathology. This study aimed to assess its efficacy in cytology specimens. Methods: The study cohort comprised 105 consecutive cytology specimens with metastatic breast carcinoma. ER IHC WSIs were seamlessly integrated into the Visiopharm platform from the Image Management System (IMS) during our routine digital workflow, and an AI algorithm was employed for analysis. ER AI scores were compared with pathologists' manual consensus scores. Optimization steps were implemented and evaluated to reduce discordance. Results: The overall concordance between pathologists' scores and AI scores was excellent (99/105, 94.3%). Six cases exhibited discordant results, including two false‐negative (FN) cases due to abundant histiocytes incorrectly counted as negatively stained tumour cells by AI, two FN cases owing to weak staining, and two false‐positive (FP) cases where pigmented macrophages were erroneously counted as positively stained tumour cells by AI. The Pearson correlation coefficient of ER‐positive percentages between pathologists' and AI scores was 0.8483. Optimization steps, such as lowering the cut‐off threshold and additional training using higher input magnification, significantly improved accuracy. Conclusions: The automated ER AI algorithm demonstrated excellent concordance with pathologists' assessments and accurately differentiated ER‐positive from ER‐negative metastatic breast carcinoma cytology cases. However, precision in identifying tumour cells in cytology specimens requires further enhancement. [ABSTRACT FROM AUTHOR]

Background. Spindle cell/sclerosing rhabdomyosarcoma is a rare neoplasm and has an aggressive clinical course. Because of its rarity, we performed a multi-institutional collaboration to comprehend the overarching clinical, histopathological, and immunohistochemical characteristics of a cohort of spindle cell/sclerosing rhabdomyosarcoma. Materials and Methods. Forty-five patients with spindle cell/sclerosing rhabdomyosarcoma were identified. Demographics, clinical, histopathological, and immunohistochemistry data were reviewed and recorded. Results. The patients' age ranged from 1 to 85 years with a male to female ratio of 1.2:1. There were 15 children/adolescents and 30 adults. Eighteen (40%) tumors were located in the head and neck region. Twenty-four (53%) tumors displayed a bimorphic cellular arrangement with hypercellular areas having short, long, and sweeping fascicular and herringbone pattern, and hypocellular areas with stromal sclerosis and associated hyalinized and/or chondromyxoid matrix. Histomorphological differentials considered were leiomyosarcoma, malignant peripheral nerve sheath tumor, fibrosarcoma, nodular fasciitis, liposarcoma, synovial sarcoma, sarcomatoid carcinoma, solitary fibrous tumor, dermatofibrosarcoma protuberans, and schwannoma. Six tumors exhibited marked stromal sclerosis. The myogenic nature was confirmed by immunohistochemistry. Positivity for at least one skeletal muscle-associated marker (MyoD1 and/or myogenin) was observed. Conclusion. Spindle cell/sclerosing rhabdomyosarcoma diagnosis can be challenging as a number of malignant spindle cell neoplasm mimic this entity. Thus a correct diagnosis requires immunohistochemical work up with a broad panel of antibodies. In view of rarity of this neoplasm, further studies on a large cohort of patients with clinical follow-up data are needed for a better understanding of this tumor. [ABSTRACT FROM AUTHOR]

Background. Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. It utilizes virtual microscopy wherein glass slides are converted into digital slides and are viewed by pathologists by automated image analysis. Its impact on pathology workflow, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and institutional collaboration exemplifies a significant innovative movement. The recent US Food and Drug Administration approval to WSI for its use in primary surgical pathology diagnosis has opened opportunities for wider application of this technology in routine practice. Main Text. The ongoing technological advances in digital scanners, image visualization methods, and the integration of artificial intelligence-derived algorithms with these systems provide avenues to exploit its applications. Its benefits are innumerable such as ease of access through the internet, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides to name a few. Although the benefits of WSI to pathology practices are many, the complexities of implementation remain an obstacle to widespread adoption. Some barriers including the high cost, technical glitches, and most importantly professional hesitation to adopt a new technology have hindered its use in routine pathology. Conclusions. In this review, we summarize the technical aspects of WSI, its applications in diagnostic pathology, training, and research along with future perspectives. It also highlights improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology. WSI provides a golden opportunity for pathologists to guide its evolution, standardization, and implementation to better acquaint them with the key aspects of this technology and its judicial use. Also, implementation of routine digital pathology is an extra step requiring resources which (currently) does not usually result increased efficiency or payment. [ABSTRACT FROM AUTHOR]