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Critical Reviews in Oncology/hematology Oct 2022Anatomic pathology has changed dramatically in recent years. Although the microscopic assessment of tissues and cells is and will remain the mainstay of cancer diagnosis... (Review)
Review
Anatomic pathology has changed dramatically in recent years. Although the microscopic assessment of tissues and cells is and will remain the mainstay of cancer diagnosis molecular profiling has become equally relevant. Thus, to stay abreast of the evolving landscape of today's anatomic pathology, modern pathologists must be able to master the intricate world of predictive molecular pathology. To this aim, pathologists have had to acquire additional knowledge to bridge the gap between clinicians and molecular biologists. This new role is particularly important, as cases are now collegially discussed in molecular tumor boards (MTBs). Moreover, as opposed to traditional pathologists, modern pathologists have also adamantly embraced innovation while keeping a constant eye on tradition. In this article, we depict the highlights and shadows of the upcoming "Anatomic Pathology 2.0" by placing particular emphasis on the pathologist's growing role in the management of cancer patients.
Topics: Humans; Neoplasms; Pathologists
PubMed: 35934262
DOI: 10.1016/j.critrevonc.2022.103776 -
Endocrine Pathology Mar 2023The effects of many pharmacological agents on thyroid function are well known. Direct influences on measurements of thyroid function tests are also described. However,... (Review)
Review
The effects of many pharmacological agents on thyroid function are well known. Direct influences on measurements of thyroid function tests are also described. However, certain classes of drugs produce morphological changes in the gland. This review focuses on the significance of the following drug classes for the thyroid pathologist: iodine, antithyroid drugs, psychotropic drugs, antibiotics, cardiotropic drugs, antidiabetic drugs, and immunomodulatory agents. Radioactive iodine initially induces mild histologic changes; however, the long-term effects include marked follicular atrophy, fibrosis, and nuclear atypia-changes that vary depending on the pre-therapy condition of the gland. Some psychotropic drugs have been associated with a spectrum of inflammatory changes throughout the gland. The tetracycline class of antibiotics, namely minocycline, can lead to a grossly black thyroid gland with pigment seen in both colloid and follicular epithelial cells while variably present within thyroid nodules. The surgical pathologist most commonly sees an amiodarone-affected gland removed for hyperthyroidism, and the histologic findings again depend on the pre-therapy condition of the gland. While GLP-1 receptor agonists carry an FDA black box warning for patients with a personal or family history of multiple endocrine neoplasia or medullary thyroid carcinoma, the C cell hyperplasia originally noted in rats has not borne out in human studies. Finally, thyroiditis and hypothyroidism are well known complications of checkpoint inhibitor therapy, and rare cases of severe thyroiditis requiring urgent thyroidectomy have been reported with unique histologic findings. In this review, we describe the histologic findings for these drugs and more, in many cases including their functional consequences.
Topics: Humans; Animals; Rats; Iodine Radioisotopes; Pathologists; Thyroid Neoplasms; Thyroiditis; Anti-Bacterial Agents; Iodine
PubMed: 36723855
DOI: 10.1007/s12022-023-09749-1 -
Science (New York, N.Y.) May 2022Itiel Dror is determined to reveal the role of bias in forensics, even if it sparks outrage.
Itiel Dror is determined to reveal the role of bias in forensics, even if it sparks outrage.
Topics: Autopsy; Bias; Dermatoglyphics; Forensic Pathology; Humans; Pathologists
PubMed: 35549426
DOI: 10.1126/science.adc8720 -
American Journal of Clinical Pathology Mar 2020
Topics: Cell Biology; Humans; Pathologists; Workplace
PubMed: 31802132
DOI: 10.1093/ajcp/aqz190 -
Cardiovascular Pathology : the Official... 2021
Topics: Biomedical Research; Humans; Pathologists
PubMed: 34271195
DOI: 10.1016/j.carpath.2021.107369 -
Fetal and Pediatric Pathology 2024
Topics: Humans; Child; Pathologists; Disasters
PubMed: 38009306
DOI: 10.1080/15513815.2023.2285578 -
The Journal of Pathology Apr 2020Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leverage the enormous potential of personalised medicine and of... (Review)
Review
Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leverage the enormous potential of personalised medicine and of stratifying patients, enabling the administration of modern therapies. Therefore, the daily task for pathologists is changing drastically and will become increasingly demanding in order to take advantage of the development of modern computer technologies. The role of pathologist has rapidly evolved from exclusively describing the morphology and phenomenology of a disease, to becoming a gatekeeper for novel and most effective treatment options. This is possible based on the retrieval and management of a wide range of complex information from tissue or a group of cells and associated meta-data. Intelligent and self-learning software solutions can support and guide pathologists to score clinically relevant decisions based on the accurate and robust quantification of multiple target molecules or surrogate biomarker as companion or complimentary diagnostics along with relevant spatial relationships and contextual information from digital H&E and multiplexed images. With the availability of multiplex staining techniques on a single slide, high-resolution image analysis tools, and high-end computer hardware, machine and deep learning solutions now offer diagnostic rulesets and algorithms that still require clinical validation in well-designed studies. Before entering the clinical practice, the 'human factor' pathologist needs to develop trust in the output coming from the 'digital black box of computational pathology', including image analysis solutions and artificial intelligence algorithms to support critical clinical decisions which otherwise would not be available. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Topics: Algorithms; Artificial Intelligence; Humans; Image Interpretation, Computer-Assisted; Pathologists; Pathology; Software
PubMed: 31994192
DOI: 10.1002/path.5388 -
The Journal of Pathology. Clinical... Jul 2023The current move towards digital pathology enables pathologists to use artificial intelligence (AI)-based computer programmes for the advanced analysis of whole slide... (Review)
Review
The current move towards digital pathology enables pathologists to use artificial intelligence (AI)-based computer programmes for the advanced analysis of whole slide images. However, currently, the best-performing AI algorithms for image analysis are deemed black boxes since it remains - even to their developers - often unclear why the algorithm delivered a particular result. Especially in medicine, a better understanding of algorithmic decisions is essential to avoid mistakes and adverse effects on patients. This review article aims to provide medical experts with insights on the issue of explainability in digital pathology. A short introduction to the relevant underlying core concepts of machine learning shall nurture the reader's understanding of why explainability is a specific issue in this field. Addressing this issue of explainability, the rapidly evolving research field of explainable AI (XAI) has developed many techniques and methods to make black-box machine-learning systems more transparent. These XAI methods are a first step towards making black-box AI systems understandable by humans. However, we argue that an explanation interface must complement these explainable models to make their results useful to human stakeholders and achieve a high level of causability, i.e. a high level of causal understanding by the user. This is especially relevant in the medical field since explainability and causability play a crucial role also for compliance with regulatory requirements. We conclude by promoting the need for novel user interfaces for AI applications in pathology, which enable contextual understanding and allow the medical expert to ask interactive 'what-if'-questions. In pathology, such user interfaces will not only be important to achieve a high level of causability. They will also be crucial for keeping the human-in-the-loop and bringing medical experts' experience and conceptual knowledge to AI processes.
Topics: Humans; Artificial Intelligence; Pathologists; Algorithms; Image Processing, Computer-Assisted
PubMed: 37045794
DOI: 10.1002/cjp2.322 -
Archives of Pathology & Laboratory... Jul 2019
Topics: Humans; Medical Overuse; Pathologists; Radiologists; Thyroid Neoplasms
PubMed: 31225996
DOI: 10.5858/arpa.2019-0146-LE -
Archives of Pathology & Laboratory... Jul 2019
Topics: Humans; Medical Overuse; Pathologists; Radiologists; Thyroid Neoplasms
PubMed: 31225992
DOI: 10.5858/arpa.2019-0103-LE