The application of digital pathology and artificial intelligence in anatomical pathology represents a revolutionary step towards the modernization of diagnostic processes. Digitalization, primarily based on creation and subsequent use of whole slide imaging, enables generating of full digital images of histological slides, offering potential benefits in diagnostic accuracy and accessibility. Unlike traditional microscopy, digital pathology also facilitates telemedicine and remote consultation, opening new possibilities for collaboration and sharing of expertise at both national and international levels. However, implementing a digital workflow requires substantial investments in scanners, software platforms, high-capacity storage, and IT infrastructure. Despite considerable costs of implementation, it brings numerous advantages, including time savings, opportunities for centralized diagnostics, and a reduction in sample transport costs. This paper focuses on the practical aspects of implementing digital pathology in pathology laboratories, emphasizing the benefits, risks, and technological requirements associated with digitalized workflows. It also discusses crucial roles of validation and verification, which are essential for ensuring a diagnostic accuracy of digital images compared to conventional microscopy. The article presents digital pathology as a dynamically evolving field with high potential for personalized medicine, improved diagnostic accuracy, and support for remote collaboration, addressing the growing demands of modern medicine.
- Keywords
- Digital Pathology, artificial intelligence, machine learning, whole slide image,
- MeSH
- Pathology, Clinical * methods MeSH
- Humans MeSH
- Microscopy MeSH
- Image Processing, Computer-Assisted * MeSH
- Workflow * MeSH
- Telepathology MeSH
- Artificial Intelligence MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
AI development in biotechnology relies on high-quality data to train and validate algorithms. The FAIR principles (Findable, Accessible, Interoperable, and Reusable) and regulatory frameworks such as the In Vitro Diagnostic Regulation (IVDR) and the Medical Device Regulation (MDR) specify requirements on specimen and data provenance to ensure the quality and traceability of data used in AI development. In this paper, a framework is presented for recording and publishing provenance information to meet these requirements. The framework is based on the use of standardized models and protocols, such as the W3C PROV model and the ISO 23494 series, to capture and record provenance information at various stages of the data generation and analysis process. The framework and use case illustrate the role of provenance information in supporting the development of high-quality AI algorithms in biotechnology. Finally, the principles of the framework are illustrated in a simple computational pathology use case, showing how specimen and data provenance can be used in the development and documentation of an AI algorithm. The use case demonstrates the importance of managing and integrating distributed provenance information and highlights the complex task of considering factors such as semantic interoperability, confidentiality, and the verification of authenticity and integrity.
- Keywords
- Artificial intelligence, Biological material, Provenance, Traceability,
- MeSH
- Algorithms * MeSH
- Biotechnology * MeSH
- Artificial Intelligence MeSH
- Publication type
- Journal Article MeSH
In the field of heart transplantation, the ability to accurately and promptly diagnose cardiac allograft rejection is crucial. This comprehensive review explores the transformative role of digital pathology and computational pathology, especially through machine learning, in this critical domain. These methodologies harness large datasets to extract subtle patterns and valuable information that extend beyond human perceptual capabilities, potentially enhancing diagnostic outcomes. Current research indicates that these computer-based systems could offer accuracy and performance matching, or even exceeding, that of expert pathologists, thereby introducing more objectivity and reducing observer variability. Despite promising results, several challenges such as limited sample sizes, diverse data sources, and the absence of standardized protocols pose significant barriers to the widespread adoption of these techniques. The future of digital pathology in heart transplantation diagnostics depends on utilizing larger, more diverse patient cohorts, standardizing data collection, processing, and evaluation protocols, and fostering collaborative research efforts. The integration of various data types, including clinical, demographic, and imaging information, could further refine diagnostic precision. As researchers address these challenges and promote collaborative efforts, digital pathology has the potential to become an integral part of clinical practice, ultimately improving patient care in heart transplantation.
- Keywords
- Cardiac allograft rejection, Computational pathology, Digital image analysis, Digital pathology, Endomyocardial biopsy, Machine learning,
- MeSH
- Algorithms * MeSH
- Biopsy MeSH
- Humans MeSH
- Pathologists MeSH
- Heart Transplantation * adverse effects MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with 'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://onlinelibrary.wiley.com/journal/10969896). © 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
- Keywords
- 3D reconstruction, DNA sequencing, PAR1, PAR2, QuPath, adult stem cells, artificial intelligence, asthma, biomarkers, breast cancer, cancer, cancer-adjacent tissues, cancer-associated fibroblasts, chromothripsis, chronic obstructive pulmonary disease, clonal dynamics, clonality analysis, colon, computational pathology, convolutional neural networks, copy number aberrations, copy number signatures, cystic fibrosis, data repository, desquamation, digital pathology, epidermal inflammation, epidermis, epithelial transition states, extrachromosomal DNA, field cancerisation, filaggrin, functional pathology, genomics, haemopoietic stem cells, host, idiopathic pulmonary fibrosis, image analysis, image processing, immune checkpoint inhibitors, immune system, immunotherapy, in situ hybridisation, in vivo models, intestinal stem cells, intra-tumour heterogeneity, kallikrein-related peptidases, lineage tracing, lung atlas, lung diseases, lung progenitors, lung stem cells, machine learning, metabolome, microbiome, mutational signatures, open science, patient stratification, prediction, prognosis, protease inhibitors, proteolytic cascades, quantitative methods, single cell DNA sequencing, single cell RNA sequencing, single cell transcriptomics, skin diseases, skin physiology, software, structural variants, subclone, tumour evolution, tumour phylogeny, virtual slide, whole genome sequencing, whole-slide imaging, whole-slide scanning,
- MeSH
- Humans MeSH
- Mutation MeSH
- Tumor Microenvironment genetics MeSH
- Neoplasms * genetics pathology MeSH
- Software MeSH
- Check Tag
- Humans MeSH
- Publication type
- Introductory Journal Article MeSH
- Editorial MeSH
- Geographicals
- United Kingdom MeSH
With the advancing digitalization of pathology, the application of machine learning and artificial intelligence methods is becoming increasingly important. Research and development in this field are progressing rapidly, but the clinical implementation of learning systems still lags behind. The aim of this text is to provide an overview of the process of developing and deploying learning systems in digital pathology. We begin by describing the fundamental characteristics of data produced in digital pathology. Specifically, we discuss scanners and sample scanning, data storage and transmission, quality control, and preparation for processing by learning systems, with a particular focus on annotations. Our goal is to present current approaches to addressing technical challenges while also highlighting potential pitfalls in processing digital pathology data. In the first part of the text, we also outline existing software solutions for viewing scanned samples and implementing diagnostic procedures that incorporate learning systems. In the second part of the text, we describe common tasks in digital pathology and outline typical approaches to solving them. Here, we explain the necessary modifications to standard machine learning methods for processing large scans and discuss specific diagnostic applications. Finally, we provide a brief overview of the potential future development of learning systems in digital pathology. We illustrate the transition to large foundational models and introduce the topic of virtual staining of samples. We hope that this text will contribute to a better understanding of the rapidly evolving field of machine learning in digital pathology and, in turn, facilitate the faster adoption of learning-based methods in this domain.
- Keywords
- Digital Pathology, Image processing, Whole-slide images, artificial intelligence, machine learning,
- MeSH
- Humans MeSH
- Image Processing, Computer-Assisted * methods MeSH
- Machine Learning * MeSH
- Artificial Intelligence MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Three-dimensional surface technologies particularly close range photogrammetry and optical surface scanning have recently advanced into affordable, flexible and accurate techniques. Forensic postmortem investigation as performed on a daily basis, however, has not yet fully benefited from their potentials. In the present paper, we tested two approaches to 3D external body documentation - digital camera-based photogrammetry combined with commercial Agisoft PhotoScan(®) software and stereophotogrammetry-based Vectra H1(®), a portable handheld surface scanner. In order to conduct the study three human subjects were selected, a living person, a 25-year-old female, and two forensic cases admitted for postmortem examination at the Department of Forensic Medicine, Hradec Králové, Czech Republic (both 63-year-old males), one dead to traumatic, self-inflicted, injuries (suicide by hanging), the other diagnosed with the heart failure. All three cases were photographed in 360° manner with a Nikon 7000 digital camera and simultaneously documented with the handheld scanner. In addition to having recorded the pre-autopsy phase of the forensic cases, both techniques were employed in various stages of autopsy. The sets of collected digital images (approximately 100 per case) were further processed to generate point clouds and 3D meshes. Final 3D models (a pair per individual) were counted for numbers of points and polygons, then assessed visually and compared quantitatively using ICP alignment algorithm and a cloud point comparison technique based on closest point to point distances. Both techniques were proven to be easy to handle and equally laborious. While collecting the images at autopsy took around 20min, the post-processing was much more time-demanding and required up to 10h of computation time. Moreover, for the full-body scanning the post-processing of the handheld scanner required rather time-consuming manual image alignment. In all instances the applied approaches produced high-resolution photorealistic, real sized or easy to calibrate 3D surface models. Both methods equally failed when the scanned body surface was covered with body hair or reflective moist areas. Still, it can be concluded that single camera close range photogrammetry and optical surface scanning using Vectra H1 scanner represent relatively low-cost solutions which were shown to be beneficial for postmortem body documentation in forensic pathology.
- Keywords
- Optical surface scanning, Photogrammetry, Point cloud comparison, Postmortem documentation,
- MeSH
- Algorithms MeSH
- Adult MeSH
- Photogrammetry * MeSH
- Middle Aged MeSH
- Humans MeSH
- Computer Simulation * MeSH
- Software MeSH
- Forensic Pathology methods MeSH
- Imaging, Three-Dimensional methods MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The 2023 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 12 invited reviews on topics of current interest in pathology. This year, our subjects include immuno-oncology and computational pathology approaches for diagnostic and research applications in human disease. Reviews on the tissue microenvironment include the effects of apoptotic cell-derived exosomes, how understanding the tumour microenvironment predicts prognosis, and the growing appreciation of the diverse functions of fibroblast subtypes in health and disease. We also include up-to-date reviews of modern aspects of the molecular basis of malignancies, and our final review covers new knowledge of vascular and lymphatic regeneration in cardiac disease. All of the reviews contained in this issue are written by expert groups of authors selected to discuss the recent progress in their particular fields and all articles are freely available online (https://pathsocjournals.onlinelibrary.wiley.com/journal/10969896). © 2023 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
- Keywords
- DNA damage repair, VEGF, advanced analytics, apoptosis, artificial intelligence, biomarkers, breast cancer, cancer, cancer-associated fibroblasts, cardiac regeneration, cell cycle arrest, cell plasticity, cellular senescence, clinical trials, computational pathology, copy number alterations, deep learning, digital pathology, endothelial cells, evolution, exosomes, extracellular vesicles, fibroblast heterogeneity, fibrosis, genomic complexity, guidelines, heart failure, histopathology, image analysis, immune checkpoint inhibitors, immunotherapy, immunotherapy failure, keloid scar, lineage tracing, lymphangiogenesis, machine learning, microvesicles, mutations, myocardial infarction, neovascularisation, oncogenic drivers, pancreatic cancer, patient-derived models, pitfalls, prognostic biomarker, quiescence, sarcomagenesis, sarcomas, secondary genetic alterations, senescence escape, senolytics, single cell sequencing, skin, spatial profiling, structural variants, triple-negative breast cancer, tumour heterogeneity, tumour microenvironment, tumour-infiltrating lymphocytes, whole slide images, wound healing,
- MeSH
- Humans MeSH
- Tumor Microenvironment MeSH
- Neoplasms * pathology MeSH
- Review Literature as Topic MeSH
- Prognosis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Introductory Journal Article MeSH
- Editorial MeSH
- Geographicals
- United Kingdom MeSH
This study investigates the influence of varying degrees of stenosis on blood flow within elliptic arteries, emphasizing the critical role of artery shape in clinical evaluations as opposed to the commonly studied circular arteries. Unlike prior work, this research offers a precise definition of stenosis by incorporating the measured length, height, and position of the narrowing. Employing the non-Newtonian Williamson fluid model, we conducted comprehensive numerical simulations to examine blood flow through four distinct stenosis formations. The novelty of this work lies in its accurate modeling of stenosis and use of advanced mesh generation, combined with commercial software and the finite volume method, to capture detailed hemodynamic behavior. Visualized results, including pressure profiles, velocity line graphs, and streamlines, further underscore the distinctive flow dynamics shaped by the elliptic geometry. Key findings of the obtained results reveal that blood velocity peaks near the stenosis and drops significantly post-stenosis, with notable variations in flow patterns, energy loss, and pressure distribution across different stenosis types. Further, higher velocity of blood flow is observed in elliptic arteries in comparison with circular ones. In the area of the high corners of stenotic segments, the pressure profile reaches high values. As a result of the narrowing of the arterial cross-section, the varied time shows that the post-stenotic segment of the artery has a higher pressure than the pre-stenotic section. The varied time suggests that an axially symmetric profile will eventually be the norm for the flow within the arterial portion. These insights have profound implications for improving clinical diagnosis and treatment strategies for conditions related to stenosed elliptic arteries.
Authors' experience gained during a one year usage of the Internet is presented. By now we have found many useful information resources related to the field of pathology. The MEDLINE database is available free of charge at several web sites as well as teaching diagnostic seminars, electronic color atlases, medical publishers homepages, etc. There is also a possibility to enter various topic-related groups in the framework of Internet discussion groups. The limiting factors for reaching medical information from the Internet is hardware and software equipment, the cost of Internet connection, and the data transmission capacity of phone lines.
This article traces the development of pathology practice from its origins in autopsy pathology to its current practice in the United States. The American model of practice differs markedly from that in continental European countries because of the extensive incorporation of "Clinical Pathology" with the traditional disciplines of anatomic pathology under the auspices of the Pathology Department. "Clinical Pathology" as it is now defined includes the laboratory testing disciplines of Chemistry, Hematology, Immunology, Medical Microbiology, and Transfusion Medicine. The increasing importance of computers and information management, DNA diagnostic techniques, and the multiple roles of the pathologist as a researcher and consultant in pathology practice in the United States is discussed.
- MeSH
- History, 19th Century MeSH
- History, 20th Century MeSH
- Pathology, Clinical history trends MeSH
- Forecasting MeSH
- Check Tag
- History, 19th Century MeSH
- History, 20th Century MeSH
- Publication type
- Journal Article MeSH
- Historical Article MeSH
- Geographicals
- United States MeSH
