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Pathology, Research and Practice Sep 2020Information, archives, and intelligent artificial systems are part of everyday life in modern medicine. They already support medical staff by mapping their workflows... (Review)
Review
Information, archives, and intelligent artificial systems are part of everyday life in modern medicine. They already support medical staff by mapping their workflows with shared availability of cases' referral information, as needed for example, by the pathologist, and this support will be increased in the future even more. In radiology, established standards define information models, data transmission mechanisms, and workflows. Other disciplines, such as pathology, cardiology, and radiation therapy, now define further demands in addition to these established standards. Pathology may have the highest technical demands on the systems, with very complex workflows, and the digitization of slides generating enormous amounts of data up to Gigabytes per biopsy. This requires enormous amounts of data to be generated per biopsy, up to the gigabyte range. Digital pathology allows a change from classical histopathological diagnosis with microscopes and glass slides to virtual microscopy on the computer, with multiple tools using artificial intelligence and machine learning to support pathologists in their future work.
Topics: Artificial Intelligence; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Pathologists; Pathology; Workflow
PubMed: 32825928
DOI: 10.1016/j.prp.2020.153040 -
Modern Pathology : An Official Journal... Feb 2022The field of anatomic pathology has been evolving in the last few decades and the advancements have been largely fostered by innovative technology. Immunohistochemistry... (Review)
Review
The field of anatomic pathology has been evolving in the last few decades and the advancements have been largely fostered by innovative technology. Immunohistochemistry enabled a paradigm shift in discovery and diagnostic evaluation, followed by booming genomic advancements which allowed for submicroscopic pathologic characterization, and now the field of digital pathology coupled with machine learning and big data acquisition is paving the way to revolutionize the pathology medical domain. Whole slide imaging (WSI) is a disruptive technology where glass slides are digitized to produce on-screen whole slide images. Specifically, in the past decade, there have been significant advances in digital pathology systems that have allowed this technology to promote integration into clinical practice. Whole slide images (WSI), or digital slides, can be viewed and navigated comparable to glass slides on a microscope, as digital files. Whole slide imaging has increased in adoption among pathologists, pathology departments, and scientists for clinical, educational, and research initiatives. Integration of digital pathology systems requires a coordinated effort with numerous stakeholders, not only within the pathology department, but across the entire enterprise. Each pathology department has distinct needs, use cases and blueprints, however the framework components and variables for successful clinical integration can be generalized across any organization seeking to undergo a digital transformation at any scale. This article will review those components and considerations for integrating digital pathology systems into clinical practice.
Topics: Humans; Microscopy; Pathologists; Pathology, Clinical
PubMed: 34599281
DOI: 10.1038/s41379-021-00929-0 -
The Journal of Pathology Jul 2022Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of digital pathology (DP) and an increase in computational power have led to... (Review)
Review
Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of digital pathology (DP) and an increase in computational power have led to the development of artificial intelligence (AI)-based tools that can assist pathologists and pulmonologists in improving clinical workflow and patient management. While previous works have explored the advances in computational approaches for breast, prostate, and head and neck cancers, there has been a growing interest in applying these technologies to lung diseases as well. The application of AI tools on radiology images for better characterization of indeterminate lung nodules, fibrotic lung disease, and lung cancer risk stratification has been well documented. In this article, we discuss methodologies used to build AI tools in lung DP, describing the various hand-crafted and deep learning-based unsupervised feature approaches. Next, we review AI tools across a wide spectrum of lung diseases including cancer, tuberculosis, idiopathic pulmonary fibrosis, and COVID-19. We discuss the utility of novel imaging biomarkers for different types of clinical problems including quantification of biomarkers like PD-L1, lung disease diagnosis, risk stratification, and prediction of response to treatments such as immune checkpoint inhibitors. We also look briefly at some emerging applications of AI tools in lung DP such as multimodal data analysis, 3D pathology, and transplant rejection. Lastly, we discuss the future of DP-based AI tools, describing the challenges with regulatory approval, developing reimbursement models, planning clinical deployment, and addressing AI biases. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Topics: Artificial Intelligence; COVID-19; Humans; Lung; Lung Neoplasms; Pathologists
PubMed: 35579955
DOI: 10.1002/path.5966 -
Modern Pathology : An Official Journal... Mar 2023The repair of DNA double-stranded breaks relies on the homologous recombination repair pathway and is critical to cell function. However, this pathway can be lost in... (Review)
Review
The repair of DNA double-stranded breaks relies on the homologous recombination repair pathway and is critical to cell function. However, this pathway can be lost in some cancers such as breast, ovarian, endometrial, pancreatic, and prostate cancers. Cancer cells with homologous recombination deficiency (HRD) are sensitive to targeted inhibition of poly-ADP ribose polymerase (PARP), a key component of alternative backup DNA repair pathways. Identifying patients with cancer with HRD biomarkers allows the identification of patients likely to benefit from PARP inhibitor therapies. In this study, we describe the causes of HRD, the underlying molecular changes resulting from HRD that form the basis of different molecular HRD assays, and discuss the issues around their clinical use. This overview is directed toward practicing pathologists wishing to be informed of this new predictive biomarker, as PARP inhibitors are increasingly used in standard care settings.
Topics: Female; Humans; Recombinational DNA Repair; Ovarian Neoplasms; Homologous Recombination; Pathologists; DNA Repair
PubMed: 36788098
DOI: 10.1016/j.modpat.2022.100049 -
Folia Neuropathologica 2022The 5th edition of World Health Organization (WHO) Central Nervous System (CNS) tumours classification has transformed the pathological diagnosis of gliomas from purely... (Review)
Review
The 5th edition of World Health Organization (WHO) Central Nervous System (CNS) tumours classification has transformed the pathological diagnosis of gliomas from purely histological to the multilayered integrated one with molecular biomarkers necessary for proper classification, risk stratification, and prognostic-predictive clinical purposes. Because of deep and important changes in taxonomy and diagnostic approach to gliomas, this manuscript is a review of WHO CNS classification 5th edition with general testing guidance for pathologists and clinicians working in neuro-oncology.
Topics: Brain Neoplasms; Central Nervous System Neoplasms; Glioma; Humans; Pathologists; Prognosis; World Health Organization
PubMed: 35950467
DOI: 10.5114/fn.2022.118183 -
Archives of Pathology & Laboratory... Jan 2023
Topics: Humans; Pathologists
PubMed: 36577091
DOI: 10.5858/arpa.2022-0226-ED -
Archives of Pathology & Laboratory... Jul 2019Skin adnexal tumors, those neoplasms deriving from hair follicles and sweat glands, are often a source of confusion amongst even experienced pathologists. Many...
CONTEXT.—
Skin adnexal tumors, those neoplasms deriving from hair follicles and sweat glands, are often a source of confusion amongst even experienced pathologists. Many well-described entities have overlapping features, tumors are often only partially sampled, and many cases do not fit neatly into well-established classification schemes.
OBJECTIVES.—
To simplify categorization of adnexal tumors for the general surgical pathologist and to shed light on many of the diagnostic dilemmas commonly encountered in daily practice. The following review breaks adnexal neoplasms into 3 groups: sebaceous, sweat gland-derived, and follicular.
DATA SOURCES.—
Pathology reference texts and primary literature regarding adnexal tumors.
CONCLUSIONS.—
Review of the clinical and histopathologic features of primary cutaneous adnexal tumors, and the diagnostic dilemmas they create, will assist the general surgical pathologist in diagnosing these often challenging lesions.
Topics: Humans; Neoplasms, Adnexal and Skin Appendage; Pathologists; Pathology, Surgical; Skin Neoplasms
PubMed: 30638401
DOI: 10.5858/arpa.2018-0189-RA -
Archives of Pathology & Laboratory... Apr 2020
Topics: Career Choice; Career Mobility; Humans; Pathologists; Pathology, Clinical
PubMed: 31971465
DOI: 10.5858/arpa.2019-0680-ED -
JAMA Network Open Jan 2023A standardized pathology classification system for melanocytic lesions is needed to aid both pathologists and clinicians in cataloging currently existing diverse...
IMPORTANCE
A standardized pathology classification system for melanocytic lesions is needed to aid both pathologists and clinicians in cataloging currently existing diverse terminologies and in the diagnosis and treatment of patients. The Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) has been developed for this purpose.
OBJECTIVE
To revise the MPATH-Dx version 1.0 classification tool, using feedback from dermatopathologists participating in the National Institutes of Health-funded Reducing Errors in Melanocytic Interpretations (REMI) Study and from members of the International Melanoma Pathology Study Group (IMPSG).
EVIDENCE REVIEW
Practicing dermatopathologists recruited from 40 US states participated in the 2-year REMI study and provided feedback on the MPATH-Dx version 1.0 tool. Independently, member dermatopathologists participating in an IMPSG workshop dedicated to the MPATH-Dx schema provided additional input for refining the MPATH-Dx tool. A reference panel of 3 dermatopathologists, the original authors of the MPATH-Dx version 1.0 tool, integrated all feedback into an updated and refined MPATH-Dx version 2.0.
FINDINGS
The new MPATH-Dx version 2.0 schema simplifies the original 5-class hierarchy into 4 classes to improve diagnostic concordance and to provide more explicit guidance in the treatment of patients. This new version also has clearly defined histopathological criteria for classification of classes I and II lesions; has specific provisions for the most frequently encountered low-cumulative sun damage pathway of melanoma progression, as well as other, less common World Health Organization pathways to melanoma; provides guidance for classifying intermediate class II tumors vs melanoma; and recognizes a subset of pT1a melanomas with very low risk and possible eventual reclassification as neoplasms lacking criteria for melanoma.
CONCLUSIONS AND RELEVANCE
The implementation of the newly revised MPATH-Dx version 2.0 schema into clinical practice is anticipated to provide a robust tool and adjunct for standardized diagnostic reporting of melanocytic lesions and management of patients to the benefit of both health care practitioners and patients.
Topics: Humans; Skin Neoplasms; Melanoma; Pathologists; Consensus; Health Facilities
PubMed: 36630138
DOI: 10.1001/jamanetworkopen.2022.50613 -
Modern Pathology : An Official Journal... Mar 2022Since the discovery of an oncogenic tropomyosin-receptor kinase (TRK) fusion protein in the early 1980s, our understanding of neurotrophic tropomyosin-receptor kinase... (Review)
Review
Since the discovery of an oncogenic tropomyosin-receptor kinase (TRK) fusion protein in the early 1980s, our understanding of neurotrophic tropomyosin-receptor kinase (NTRK) fusions, their unique patterns of frequency in different tumor types, and methods to detect them have grown in scope and depth. Identification of these molecular alterations in the management of patients with cancer has become increasingly important with the emergence of histology-agnostic, US Food and Drug Administration-approved, effective TRK protein inhibitors. Herein, we review the biology of TRK in normal and malignant tissues, as well as the prevalence and enrichment patterns of these fusions across tumor types. Testing methods currently used to identify NTRK1-3 fusions will be reviewed in detail, with attention to newer assays including RNA-based next-generation sequencing. Recently proposed algorithms for NTRK fusion testing will be compared, and practical insights provided on how testing can best be implemented and communicated within the multidisciplinary healthcare team.
Topics: Gene Fusion; Humans; Neoplasms; Oncogene Proteins, Fusion; Pathologists; Protein Kinase Inhibitors; Receptor, trkA
PubMed: 34531526
DOI: 10.1038/s41379-021-00913-8