Image Analysis in Histopathology and Cytopathology: From Early Days to Current Perspectives

Journal of Imaging, Journal Year: 2024, Volume and Issue: 10(10), P. 252 - 252

Published: Oct. 14, 2024

Both pathology and cytopathology still rely on recognizing microscopical morphologic features, image analysis plays a crucial role, enabling the identification, categorization, characterization of different tissue types, cell populations, disease states within microscopic images. Historically, manual methods have been primary approach, relying expert knowledge experience pathologists to interpret samples. Early were often constrained by computational power complexity biological The advent computers digital imaging technologies challenged exclusivity human eye vision brain skills, transforming diagnostic process in these fields. increasing digitization pathological images has led application more objective efficient computer-aided techniques. Significant advancements brought about integration pathology, machine learning, advanced technologies. continuous progress learning availability data offer exciting opportunities for future. Furthermore, artificial intelligence revolutionized this field, predictive models that assist decision making. future is predicted be marked analysis. promising, will invariably lead enhanced accuracy improved prognostic predictions shape personalized treatment strategies, ultimately leading better patient outcomes.

Language: Английский

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Advancements in Digital Cytopathology Since COVID-19: Insights from a Narrative Review of Review Articles

Healthcare, Journal Year: 2025, Volume and Issue: 13(6), P. 657 - 657

Published: March 17, 2025

Background/Objectives: The integration of digitalization in cytopathology is an emerging field with transformative potential, aiming to enhance diagnostic precision and operational efficiency. This narrative review reviews (NRR) seeks identify prevailing themes, opportunities, challenges, recommendations related the process cytopathology. Methods: Utilizing a standardized checklist quality control procedures, this examines recent advancements future implications domain. Twenty-one studies were selected through systematic process. Results: results highlight key trends, digital First, study identifies pivotal themes that reflect ongoing technological transformation, guiding focus areas field. A major trend artificial intelligence (AI), which increasingly critical improving accuracy, streamlining workflows, assisting decision making. Notably, AI technologies like large language models (LLMs) chatbots are expected provide real-time support automate tasks, though concerns around ethics privacy must be addressed. also emphasize need for protocols, comprehensive training, rigorous validation ensure tools reliable effective across clinical settings. Lastly, holds significant potential improve healthcare accessibility, especially remote areas, by enabling faster, more efficient diagnoses fostering global collaboration telepathology. Conclusions: Overall, highlights impact cytopathology, efficiency, accessibility whole-slide imaging While plays role, broader on integrating solutions workflows collaboration. Addressing challenges such as standardization, ethical considerations crucial fully realize these advancements.

Language: Английский

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Computer-assisted diagnosis to improve diagnostic pathology: A review

Indian Journal of Pathology and Microbiology, Journal Year: 2025, Volume and Issue: 68(1), P. 3 - 10

Published: Jan. 1, 2025

ABSTRACT With an increasing demand for accuracy and efficiency in diagnostic pathology, computer-assisted diagnosis (CAD) emerges as a prominent transformative solution. This review aims to explore the practical applications, implications, strengths, weaknesses of CAD applied pathology. A comprehensive literature search was conducted include English-language studies focusing on tools, digital Artificial intelligence (AI) applications The underscores potential tools particularly streamlining processes, reducing turnaround times, augmenting accuracy. It emphasizes strides made integration AI, promising prospects prognostic biomarker discovery using computational methods. Additionally, ethical considerations regarding data privacy, equity, trust AI deployment are examined. has revolutionize insights gleaned from this offer panoramic view recent advancements. Ultimately, guide future research, influence clinical practice, inform policy-making by elucidating horizons pitfalls integrating

Language: Английский

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Digital transformation of pathology - the European Society of Pathology expert opinion paper

Virchows Archiv, Journal Year: 2025, Volume and Issue: unknown

Published: March 31, 2025

Language: Английский

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Surveying the Digital Cytology Workflow in Italy: An Initial Report on AI Integration Across Key Professional Roles

Healthcare, Journal Year: 2025, Volume and Issue: 13(8), P. 903 - 903

Published: April 14, 2025

Background: The integration of artificial intelligence (AI) in healthcare, particularly digital cytology, has the potential to enhance diagnostic accuracy and workflow efficiency. However, AI adoption remains limited due technological human-related barriers. Understanding perceptions experiences healthcare professionals is essential for overcoming these challenges facilitating effective implementation. Objectives: This study aimed assess cytology workflows by evaluating professionals’ perspectives on its benefits, challenges, requirements successful adoption. Methods: A survey was conducted among 150 working public private settings Italy, including laboratory technicians (35%), medical doctors (25%), biologists (20%), specialists technical sciences (20%). Data were collected through a structured Computer-Assisted Web Interview (CAWI) Virtual Focus Group (VFG) capture quantitative qualitative insights familiarity, perceived advantages, barriers Results: findings indicated varying levels familiarity professionals. While many recognized AI’s improve streamline workflows, concerns raised regarding resistance change, implementation costs, doubts about reliability. Participants emphasized need training continuous support facilitate cytology. Conclusions: Addressing such as resistance, cost, trust workflows. Tailored programs ongoing professional can adoption, ultimately optimizing processes improving clinical outcomes

Language: Английский

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Genotoxicity and Cytotoxicity Assessment of Volatile Organic Compounds in Pathology Professionals Through the Buccal Micronuclei Assay

Toxics, Journal Year: 2025, Volume and Issue: 13(5), P. 411 - 411

Published: May 19, 2025

In pathology laboratories, several volatile organic compounds (VOCs) are used, such as formaldehyde, ethanol, and xylene. These substances recognized genotoxic cytotoxic, which is why their handling poses risks to human health. The buccal micronucleus (MN) cytome assay a non-invasive, useful, simple method detect these effects in exposed individuals. aim of the study was evaluate risk genotoxicity cytotoxicity VOCs professionals S. Miguel Island, Azores, Portugal. comprised two groups: workers (n = 21) from three laboratories Miguel, reference group 50), randomly chosen other hospital services without known exposure VOCs. exfoliated cells were auto-sampled by all participants using cytobrush. samples processed ThinPrep®, stained with modified Feulgen Fast Green, visualized for MN nuclear anomalies (ONAs), karyorrhexis, pyknotic, karyolytic cells. Results showed that have predictive significance frequency, leading conclusion an increased factor health professionals, approximately four times greater than control group.

Language: Английский

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Implementing 100% quality control in a cervical cytology workflow using whole slide images and artificial intelligence provided by the Techcyte SureView™ System

Cancer Cytopathology, Journal Year: 2025, Volume and Issue: 133(6)

Published: May 19, 2025

Abstract Background Recent advancements in digital pathology have extended into cytopathology. Laboratories screening cervical cytology specimens now choose between limited imaging options and traditional manual microscopy. The Techcyte SureView™ Cervical Cytology System, designed for cytopathology, was validated at CorePlus, a laboratory Puerto Rico, adopted as 100% quality control (QC) tool. Methods validation study included 1442 whole slide images (WSIs) from 1273 ThinPrep® 169 SurePath™ slides, digitized with the 3DHISTECH Panoramic 1000 DX scanner using dry water immersion scanning profiles. These WSIs were processed by system, board‐certified cytopathologist reviewing artificial intelligence (AI)‐identified objects of interest comparing them to light microscopy results. Results profile outperformed both detecting squamous glandular abnormalities. It achieved 97% accuracy, 82% sensitivity, 99% specificity, 98% negative predictive value, 86% positive value. Additionally, review time rapid. system has been operational several months, enhancing accuracy workflow efficiency. Conclusions This demonstrates that particularly through can improve performance. Successful led CorePlus integrate AI algorithm their QC tool, resulting improved benefiting professionals patients.

Language: Английский

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Validation of AI-assisted ThinPrep® Pap test screening using the GeniusTM Digital Diagnostics System

Journal of Pathology Informatics, Journal Year: 2024, Volume and Issue: 15, P. 100391 - 100391

Published: July 3, 2024

Advances in whole-slide imaging and artificial intelligence present opportunities for improvement Pap test screening. To date, there have been limited studies published regarding how best to validate newer AI-based digital systems screening tests clinical practice. In this study, we validated the Genius™ Digital Diagnostics System (Hologic) by comparing performance traditional manual light microscopic diagnosis of ThinPrep

Language: Английский

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Revolutionizing Cytology and Cytopathology with Natural Language Processing and Chatbot Technologies: A Narrative Review on Current Trends and Future Directions

Bioengineering, Journal Year: 2024, Volume and Issue: 11(11), P. 1134 - 1134

Published: Nov. 11, 2024

The application of chatbots and Natural Language Processing (NLP) in cytology cytopathology is an emerging field, which currently characterized by a limited but growing body research. Here, narrative review has been proposed utilizing standardized checklist quality control procedure for including scientific papers. This explores the early developments potential future impact these technologies medical diagnostics. current literature, comprising 11 studies (after excluding comments, letters, editorials) suggests that NLP offer significant opportunities to enhance diagnostic accuracy, streamline clinical workflows, improve patient engagement. By automating extraction classification information, can reduce human error increase precision. They also promise make information more accessible facilitate complex decision-making processes, thereby fostering greater involvement healthcare. Despite promising prospects, several challenges need be addressed full realized. These include data standardization, mitigation biases Artificial Intelligence (AI) systems, comprehensive validation. Furthermore, ethical, privacy, legal considerations must navigated carefully ensure responsible AI deployment. Compared established fields histology, histopathology, especially radiology, integration digital tools still its infancy. Building on advancements related fields, radiology's experience with integration, where already solutions mentoring, second opinions, education, we leverage this knowledge further develop natural language processing cytopathology. Overall, underscores transformative while outlining critical areas research development.

Language: Английский

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AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(22), P. 6745 - 6745

Published: Nov. 9, 2024

The integration of artificial intelligence (AI) in cytopathology is an emerging field with transformative potential, aiming to enhance diagnostic precision and operational efficiency. This umbrella review seeks identify prevailing themes, opportunities, challenges, recommendations related AI cytopathology. Utilizing a standardized checklist quality control procedures, this examines recent advancements future implications technologies domain. Twenty-one studies were selected through systematic process. has demonstrated promise automating refining processes, potentially reducing errors improving patient outcomes. However, several critical challenges need be addressed realize the benefits fully. underscores necessity for rigorous validation, ongoing empirical data on accuracy, protocols, effective existing clinical workflows. Ethical issues, including privacy algorithmic bias, must managed ensure responsible applications. Additionally, high costs substantial training requirements present barriers widespread adoption. Future directions highlight importance applying successful strategies from histopathology radiology Continuous research needed improve model interpretability, standardization. Developing incorporating into practice establishing comprehensive ethical regulatory frameworks will crucial overcoming these challenges. In conclusion, while holds significant advancing cytopathology, its full potential can only achieved by addressing cost, ethics. provides overview current advancements, identifies offers roadmap informed insights fields.

Language: Английский

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