Value of routine cytokeratin immunohistochemistry in detecting low volume disease in cervical cancer

Baeten, Ilse; Hoogendam, Jacob P.; Jonges, G. N.; Jürgenliemk-Schulz, Ì.M.; Braat, Arthur J. A. T.; Diest, Paul J. van; Gerestein, C.G.; Zweemer, Ronald P.

doi:10.1016/j.ygyno.2022.02.011

Cited by 3 publications

(2 citation statements)

References 25 publications

(48 reference statements)

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“…To achieve this, 3791 slides were stained with IHC at an estimated additional cost of €94,775. In 1.4% (95% CI 0.3-4.3%) of patients, routine use of IHC adjusted the adjuvant treatment [18].…”

Section: Developing Ai-implementation Studiesmentioning

confidence: 99%

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

et al. 2022

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Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology infrastructure at the University Medical Center Utrecht and our roadmap for implementing AI algorithms in the next few years.

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Section: Developing Ai-implementation Studiesmentioning

confidence: 99%

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

et al. 2022

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“…If algorithms can reliably identify cancer cells on HE‐stained sections, this may save the high costs of immunohistochemistry, such as keratin stains on sentinel lymph nodes for breast of cervix carcinoma, 41 prostate biopsies, 41 or in identifying intrahepatic cholangiocarcinoma from colorectal liver metastases 42 . For example, in the UMC Utrecht, where HE slides of sentinel lymph nodes are assessed first, and stains are requested when these slides are morphologically negative, we spent over €30,000 on keratin stains for sentinel lymph node assessment in approximately 180 breast cancer patients.…”

Section: Pros Of Introducing Ai In Diagnostic Pathologymentioning

confidence: 99%

Pros and cons of artificial intelligence implementation in diagnostic pathology

van Diest,

Flach,

van Dooijeweert

et al. 2024

Histopathology

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The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

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Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study

Baeten

Hoogendam

Braat

et al. 2023

Expert Review of Medical Devices

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Value of routine cytokeratin immunohistochemistry in detecting low volume disease in cervical cancer

Cited by 3 publications

References 25 publications

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

Pros and cons of artificial intelligence implementation in diagnostic pathology

Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study

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