Application of image recognition technology in pathological diagnosis of blood smears.

Traditional manual blood smear diagnosis methods are time-consuming and prone to errors, often relying heavily on the experience of clinical laboratory analysts for accuracy. As breakthroughs in key technologies such as neural networks and deep learning continue to drive digital transformation in the medical field, image recognition technology is increasingly being leveraged to enhance existing medical processes. In recent years, advancements in computer technology have led to improved efficiency in the identification of blood cells in blood smears through the use of image recognition technology. This paper provides a comprehensive summary of the methods and steps involved in utilizing image recognition algorithms for diagnosing diseases in blood smears, with a focus on malaria and leukemia. Furthermore, it offers a forward-looking research direction for the development of a comprehensive blood cell pathological detection system.

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.

OBJECTIVE: Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. MATERIALS AND METHODS: We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. RESULTS: The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. CONCLUSIONS: We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.

Medical Education in Pathology: General Concepts and Strategies for Implementation.

CONTEXT.­: Pathology education must evolve as medical knowledge expands and disruptive technologies emerge. The evolution in pathology teaching practices accelerated as traditional teaching modalities were suspended in March 2020 during the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVES.­: To provide pathologists an overview of established teaching paradigms and practical examples of how these paradigms may be applied to pathology education, emphasizing differences in graduate and undergraduate medical education as well as the challenges and promises of remote learning, as revealed by the COVID-19 pandemic. DATA SOURCES.­: Selected peer-reviewed publications representing the field of educational social science. CONCLUSIONS.­: Evidence-based methods described in education and social sciences can be effectively deployed in pathology education and especially remote learning, as necessitated by the current COVID-19 pandemic. Understanding established principles, such as cognitive load, competency-based learning, peer-assisted learning, and flipped classrooms may prove useful in developing effective, learner-centric content for pathology education.

Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing number of complex biomarkers contributes to costly and delayed decision-making in routine oncology care and treatment. As cancer is expected to rank as the leading cause of death and the single most important barrier to increasing life expectancy in the 21st century, there is a major emphasis on precision medicine, particularly individualisation of treatment through better prediction of patient outcome. Over the past few years, both surgical and pathology specialties have suffered cutbacks and a low uptake of pathology specialists means a solution is required to enable high-throughput screening and personalised treatment in this area to alleviate bottlenecks. Digital imaging in pathology has undergone an exponential period of growth. Deep-learning (DL) platforms for hematoxylin and eosin (H&E) image analysis, with preliminary artificial intelligence (AI)-based grading capabilities of specimens, can evaluate image characteristics which may not be visually apparent to a pathologist and offer new possibilities for better modelling of disease appearance and possibly improve the prediction of disease stage and patient outcome. Although digital pathology and AI are still emerging areas, they are the critical components for advancing personalised medicine. Integration of transcriptomic analysis, clinical information and AI-based image analysis is yet an uncultivated field by which healthcare professionals can make improved treatment decisions in cancer. This short review describes the potential application of integrative AI in offering better detection, quantification, classification, prognosis and prediction of breast and prostate cancer and also highlights the utilisation of machine learning systems in biomarker evaluation.

Clinical and molecular practice of European thoracic pathology laboratories during the COVID-19 pandemic. The past and the near future.

BACKGROUND: This study evaluated the consequences in Europe of the COVID-19 outbreak on pathology laboratories orientated toward the diagnosis of thoracic diseases. MATERIALS AND METHODS: A survey was sent to 71 pathology laboratories from 21 European countries. The questionnaire requested information concerning the organization of biosafety, the clinical and molecular pathology, the biobanking, the workload, the associated research into COVID-19, and the organization of education and training during the COVID-19 crisis, from 15 March to 31 May 2020, compared with the same period in 2019. RESULTS: Questionnaires were returned from 53/71 (75%) laboratories from 18 European countries. The biosafety procedures were heterogeneous. The workload in clinical and molecular pathology decreased dramatically by 31% (range, 3%-55%) and 26% (range, 7%-62%), respectively. According to the professional category, between 28% and 41% of the staff members were not present in the laboratories but did teleworking. A total of 70% of the laboratories developed virtual meetings for the training of residents and junior pathologists. During the period of study, none of the staff members with confirmed COVID-19 became infected as a result of handling samples. CONCLUSIONS: The COVID-19 pandemic has had a strong impact on most of the European pathology laboratories included in this study. Urgent implementation of several changes to the organization of most of these laboratories, notably to better harmonize biosafety procedures, was noted at the onset of the pandemic and maintained in the event of a new wave of infection occurring in Europe.

HER2 Testing in Endometrial Serous Carcinoma: Time for Standardized Pathology Practice to Meet the Clinical Demand.

CONTEXT.­: Endometrial serous carcinoma is an aggressive subtype of endometrial cancer with the highest rate of recurrence and mortality among all histotypes. A recent clinical trial showed prolonged progression-free survival in advanced-stage and recurrent human epidermal growth factor receptor 2 (HER2)-positive endometrial serous carcinoma when trastuzumab was added to the standard chemotherapy regimen. This targeted therapeutic approach was recently endorsed by the National Comprehensive Cancer Network clinical guidelines. There is a growing interest among clinicians to obtain HER2 testing in endometrial serous carcinoma, and pathologists need to be prepared to recognize the unique characteristics of HER2 protein expression and gene amplification in these tumors and apply specific HER2 scoring criteria. OBJECTIVE.­: To provide a historical overview of targeted HER2 therapy in endometrial serous carcinoma and to summarize key findings from recent studies on the specific features of HER2 protein expression and gene amplification relative to other tumor types. Endometrial carcinoma-specific HER2 testing criteria are proposed based on evidence in the existing literature. DATA SOURCES.­: Sources comprise review of the literature and personal experience of the author. CONCLUSIONS.­: HER2 protein overexpression and/or gene amplification is present in approximately 25% to 30% of endometrial serous carcinomas, providing an opportunity for targeted therapy. Pathologists play a key role in tumor HER2 testing and scoring to ensure appropriate patient selection and successful clinical outcome.

Cancer diagnostic rates during the 2020 'lockdown', due to COVID-19 pandemic, compared with the 2018-2019: an audit study from cellular pathology.

AIMS: We performed an audit to evaluate the impact of the COVID-19 pandemic-related delay in the diagnosis of major cancers at a Pathology Unit of a Secondary Care Hospital Network in Italy. METHODS: A comparison was made among the number of first cellular pathological diagnoses of malignancy made from the 11th to the 20th week of the years 2018-2020. RESULTS: Cancer diagnoses fell in 2020 by 39% compared with the average number recorded in 2018 and 2019. Prostate cancer (75%) bladder cancer (66%) and colorectal cancer (CRC; 62%) had the greatest decrease. CRC was identified as carrying a potentially important diagnostic delay. CONCLUSIONS: For CRC corrective procedures (continuing mass screening tests; patient triage by family physicians; diagnostic procedures alternative to colonoscopy; predictive evaluation on biopsy samples) were advised. Our simple audit model is widely applicable to avoid pandemic-related delay in clinical diagnosis of cancer.

Rocky road to digital diagnostics: implementation issues and exhilarating experiences.

Since 2007, we have gradually been building up infrastructure for digital pathology, starting with a whole slide scanner park to build up a digital archive to streamline doing multidisciplinary meetings, student teaching and research, culminating in a full digital diagnostic workflow where we are currently integrating artificial intelligence algorithms. In this paper, we highlight the different steps in this process towards digital diagnostics, which was at times a rocky road with definitely issues in implementation, but eventually an exciting new way to practice pathology in a more modern and efficient way where patient safety has clearly gone up.

Operational Impacts of the Coronavirus Disease 2019 (COVID-19) Pandemic and Early Recovery Trends: University of Washington Anatomic Pathology Experience.

CONTEXT.­: The coronavirus disease 2019 pandemic, caused by the novel coronavirus severe acute respiratory syndrome coronavirus 2, has resulted in worldwide disruption to the delivery of patient care. The Seattle, Washington metropolitan area was one of the first in the United States affected by the pandemic. As a result, the anatomic pathology services at the University of Washington experienced significant changes in operational volumes early in the pandemic. OBJECTIVE.­: To assess the impact of coronavirus disease 2019 and both state and institutional policies implemented to mitigate viral transmission (including institutional policies on nonurgent procedures) on anatomic pathology volumes. DESIGN.­: Accessioned specimens from January to June 2020 were evaluated as coronavirus disease 2019 and institutional policies changed. The data were considered in these contexts: subspecialty, billable Current Procedural Terminology codes, and intraoperative consultation. Comparable data were retrieved from 2019 as a historical control. RESULTS.­: There was a significant reduction in overall accessioned volume (up to 79%) from prepandemic levels during bans on nonurgent procedures when compared with 2020 pre-coronavirus disease 2019 volumes and historical controls. The gastrointestinal and dermatopathology services were most impacted, and breast and combined head and neck/pulmonary services were least impacted. Current Procedural Terminology code 88305, for smaller/biopsy specimens, had a 63% reduction during nonurgent procedure bans. After all bans on procedures were lifted, the overall volume plateaued at 89% of prepandemic levels. CONCLUSIONS.­: A significant decrease in specimen volume was most strongly associated with bans on nonurgent procedures. Although all departmental areas had a decrease in volume, the extent of change varied across subspecialty and specimen types. Even with removal of all bans, service volume did not reach prepandemic levels.

Global impact of the COVID-19 pandemic on cytopathology practice: Results from an international survey of laboratories in 23 countries.

BACKGROUND: To the authors' knowledge, the impact of the coronavirus disease 2019 (COVID-19) pandemic on cytopathology practices worldwide has not been investigated formally. In the current study, data from 41 respondents from 23 countries were reported. METHODS: Data regarding the activity of each cytopathology laboratory during 4 weeks of COVID-19 lockdown were collected and compared with those obtained during the corresponding period in 2019. The overall number and percentage of exfoliative and fine-needle aspiration cytology samples from each anatomic site were recorded. Differences in the malignancy and suspicious rates between the 2 periods were analyzed using a meta-analytical approach. RESULTS: Overall, the sample volume was lower compared with 2019 (104,319 samples vs 190,225 samples), with an average volume reduction of 45.3% (range, 0.1%-98.0%). The percentage of samples from the cervicovaginal tract, thyroid, and anorectal region was significantly reduced (P < .05). Conversely, the percentage of samples from the urinary tract, serous cavities, breast, lymph nodes, respiratory tract, salivary glands, central nervous system, gastrointestinal tract, pancreas, liver, and biliary tract increased (P < .05). An overall increase of 5.56% (95% CI, 3.77%-7.35%) in the malignancy rate in nongynecological samples during the COVID-19 pandemic was observed. When the suspicious category was included, the overall increase was 6.95% (95% CI, 4.63%-9.27%). CONCLUSIONS: The COVID-19 pandemic resulted in a drastic reduction in the total number of cytology specimens regardless of anatomic site or specimen type. The rate of malignancy increased, reflecting the prioritization of patients with cancer who were considered to be at high risk. Prospective monitoring of the effect of delays in access to health services during the lockdown period is warranted.