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Digital pathology enabling lean management of HER2/neu testing in breast Cancer 数字病理学使乳腺癌HER2/neu检测精益管理
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-09-05 DOI: 10.1016/j.jpi.2025.100515
Aishwarya Sharma , Prarthna Shah , Manali Ranade , Trupti Pai , Ayushi Sahay , Asawari Patil , Tanuja Shet , Heena Gupta , Devika Chauhan , Puneet Somal , Sankalp Sancheti , Sangeeta Desai

Introduction

Invasive breast carcinomas with an equivocal result of HER2/neu on immunohistochemistry (IHC) are reflex tested by fluorescent in situ hybridisation (FISH). Molecular testing is often not available in rural laboratories, from where it is routinely outsourced to central laboratories. Histopathology review (HPR) and IHC analysis of the tissue sample is thus repeated at the central laboratory before molecular testing which increases the turnaround time (TAT) and cost incurred by both the patient and the hospital. We aimed to assess the reduction in TAT and the cost effectiveness after introducing Digital Pathology (DP).

Methods

The tumours with equivocal HER2/neu results were outsourced for FISH from HBCH, Sangrur (rural laboratory) to Molecular Pathology Laboratory, TMH, Mumbai (central laboratory). The Haematoxylin-Eosin (HE) and IHC slides of 47 cases were virtually shared after scanning by Philips SG 60 digital slide scanner. Paraffin blocks of these cases were sent for FISH testing only. TAT of these prospectively shared cases were compared with a retrospective cohort in which virtual slides were not available. The cost benefits were also assessed.

Results

With the availability of DP, we were able to obviate repeat IHC testing. We were able to achieve a 43.9 % reduction in the TAT (15.65 days to 8.775 days). We also achieved a 30 % reduction in cost.

Conclusion

This is a prototype study highlighting the utility of DP in the lean management of HER2/neu testing. The integration of DP in the referral process reduces the TAT and expenditure optimizing resource utilisation.
浸润性乳腺癌的免疫组化(IHC)结果HER2/neu模棱两可,采用荧光原位杂交(FISH)反射检测。农村实验室通常不提供分子检测,通常将其外包给中央实验室。因此,在分子检测之前,组织样本的组织病理学检查(HPR)和免疫组化分析在中心实验室重复进行,这增加了周转时间(TAT)和患者和医院的费用。我们的目的是评估引入数字病理学(DP)后TAT的降低和成本效益。方法将HER2/neu结果不明确的肿瘤从桑格尔HBCH(农村实验室)外包给孟买TMH分子病理学实验室(中心实验室)进行FISH检测。47例患者经Philips SG 60型数字切片机扫描后,HE和IHC切片虚拟共享。这些箱子的石蜡块仅用于FISH检测。这些前瞻性共享病例的TAT与没有虚拟载玻片的回顾性队列进行比较。成本效益也进行了评估。结果由于DP的可用性,我们能够避免重复IHC检测。我们能够实现43.9 %的TAT减少(15.65 天到8.775 天)。我们还实现了30% %的成本降低。结论这是一项原型研究,突出了DP在HER2/neu检测精益管理中的应用。DP在转诊过程中的整合降低了TAT和支出,优化了资源利用。
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引用次数: 0
Streamlining HLA quality control applications: simplified development and role-based authorization with Next.js and NextUI 简化HLA质量控制应用:使用Next.js和NextUI简化开发和基于角色的授权
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100467
Jacob Kinskey , Scott Long , Paul Christensen , Todd Eagar
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引用次数: 0
AI-driven platform for streamlined breast biopsy interpretation: enhancing turnaround time and clinical workflow in digital pathology 简化乳腺活检解释的人工智能驱动平台:提高数字病理学的周转时间和临床工作流程
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100489
Ashbaker Kathleen , Soraki Rustin , Krishnan Tara , T. Nelson Maria , Rizkalla Carol , Kilgore Mark , C. Henriksen Jonathan , Hosny Kareem
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引用次数: 0
Unlocking big data: practical solutions to common challenges 解锁大数据:应对共同挑战的实用解决方案
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100483
Yonah C. Ziemba , Suhyeon Yoon , Harvey W. Kaufman , William A. Meyer III , Laura Gillim , Nkemakonam Okoye , Vincent Streva , Syed Qasid , Cheryl B. Schleicher , Ligia A. Pinto , Lynne Penberthy , James M. Crawford
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引用次数: 0
Development and implementation of a self-hosted web application for automated Ki67 index calculation 开发和实现用于自动Ki67索引计算的自托管web应用程序
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100493
Jitin Makker , Alireza Samiei
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引用次数: 0
Quantification of pathology associated collagen in murine models of pulmonary tuberculosis with whole-slide pixel classification of stained images and localized label- free second harmonic generation imaging 用染色图像的全切片像素分类和局部无标记的二次谐波成像定量小鼠肺结核模型的病理相关胶原
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100502
Shatavisha Dasgupta , Yuming Liu , Melisa Gillis , Kevin W. Elicieri , Amy K. Barczak , Beth A. Cimini
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引用次数: 0
Identification of inappropriate 1,25-dihydroxy Vitamin D ordering within a large, tertiary healthcare system 鉴定不适当的1,25-二羟基维生素D订购在一个大型,三级医疗保健系统
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-12-13 DOI: 10.1016/j.jpi.2025.100498
Christopher M. Zarbock , Ronald Jackups
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引用次数: 0
Deep learning for digital pathology: A critical overview of methodological framework 数字病理学的深度学习:方法框架的关键概述
Q2 Medicine Pub Date : 2025-11-01 Epub Date: 2025-09-08 DOI: 10.1016/j.jpi.2025.100514
Meghdad Sabouri Rad , Junze (Vincent) Huang , Mohammad Mehdi Hosseini , Rakesh Choudhary , Harmen Siezen , Ratilal Akabari , Tamara Jamaspishvili , Ola El-Zammar , Palak G Patel , Saverio J. Carello , Michel R. Nasr , Bardia Rodd
Deep learning frameworks have transformed the field of digital pathology by automating complex tasks and revealing intricate patterns within histopathological data. These advanced methodologies provide exceptional accuracy and scalability, facilitating the analysis of high-dimensional whole-slide images with unparalleled precision. In this article, we present a comprehensive deep learning framework highlighting recent advancements in computational pathology. We critically examine mathematical innovations and offer a comparative analysis of various models demonstrating the significant and ongoing improvements in the field.
深度学习框架通过自动化复杂任务和揭示组织病理学数据中的复杂模式,改变了数字病理学领域。这些先进的方法提供了卓越的准确性和可扩展性,以无与伦比的精度促进高维全幻灯片图像的分析。在这篇文章中,我们提出了一个全面的深度学习框架,突出了计算病理学的最新进展。我们批判性地审视数学创新,并提供各种模型的比较分析,展示了该领域的重大和持续改进。
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引用次数: 0
Proceedings of the Association for Pathology Informatics Bootcamp 2023: Ethics, equity, and regulations 病理学信息学训练营协会会议记录2023:伦理,公平和法规
Q2 Medicine Pub Date : 2025-08-01 Epub Date: 2025-05-15 DOI: 10.1016/j.jpi.2025.100452
Michelle R. Stoffel , Amrom E. Obstfeld , Brian R. Jackson , Vahid Azimi , Samuel I. McCash , Simone Arvisais-Anhalt , Lisa-Jean Clifford , Ronald Jackups
The Pathology Informatics Bootcamp is held annually at the Pathology Informatics Summit and provides pathology trainees with knowledge about both core and emerging topics in the rapidly evolving field of Pathology Informatics. In 2023, the Bootcamp focused on the applications of ethics, equity, and regulations pertinent to pathology informatics, with emphasis on the importance of these topics in the rapidly evolving landscape of artificial intelligence in pathology and lab medicine practice. Session topics are mapped to Pathology Informatics Essentials for Residents outlines to highlight the significance of these topics in pathology practice overall, and more so within informatics practice. The curriculum included lectures on data use in the clinical lab and in digital pathology, equitable use of lab data in daily practice and downstream use, and practical application of regulations for data with clinical decision-support, accreditation, and management of patient results.
病理信息学训练营每年在病理信息学峰会上举行,为病理学员提供有关快速发展的病理信息学领域的核心和新兴主题的知识。2023年,该训练营专注于病理学信息学相关的伦理、公平和法规的应用,强调这些主题在病理学和实验室医学实践中快速发展的人工智能领域的重要性。会议主题被映射到住院医师病理学信息学要点大纲,以突出这些主题在病理学实践中的总体意义,在信息学实践中更是如此。课程包括在临床实验室和数字病理学中使用数据的讲座,在日常实践和下游使用中公平使用实验室数据,以及在临床决策支持、认证和患者结果管理中数据法规的实际应用。
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引用次数: 0
Corrigendum to “Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review”. Journal of Pathology Informatics 15(2024) 100367 “淋巴结转移检测的计算方法和无转移淋巴结微结构的表征:系统叙述混合回顾”的勘误。病理信息学杂志15(2024)100367
Q2 Medicine Pub Date : 2025-08-01 Epub Date: 2025-07-07 DOI: 10.1016/j.jpi.2025.100457
Elzbieta Budginaite , Derek R. Magee , Maximilian Kloft , Henry C. Woodruff , Heike I. Grabsch
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引用次数: 0
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Journal of Pathology Informatics
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