Publications by authors named "Carmen van Dooijeweert"

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.

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Article Synopsis
  • - Breast cancer is the most common type of cancer that can happen during or right after pregnancy, which is called Pregnancy-Associated Breast Cancer (PABC).
  • - PABC often has more serious features and a worse outlook than breast cancer in women who aren’t pregnant.
  • - It’s really important for any pregnant or new moms to get any changes in their breasts checked out carefully, to make sure it’s not cancer.
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Introduction: Artificial intelligence (AI) has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI have yet to be performed, to the best of our knowledge. In this trial, we will explore the benefits of an AI-assisted pathology workflow, while maintaining diagnostic safety standards.

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Programmed death ligand-1 (PD-L1) immunostaining, which aids clinicians in decision-making on immunotherapy for non-small cell lung cancer (NSCLC) patients, is sometimes performed on cytological specimens. In this study, differences in cytology fixation and cell block (CB) processing between pathology laboratories were assessed, and the influence of these differences on interlaboratory variation in PD-L1 positivity was investigated. Questionnaires on cytology processing were sent to all Dutch laboratories.

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Aim: Substantial variation in Gleason grading (GG) of prostate cancer (PCa) exists between Dutch pathology laboratories. This study investigates its impact on treatment strategies.

Methods: Pathology reports of prostate needle biopsies and clinical data of patients with PCa diagnosed between 2017 and 2019 were retrieved from the Dutch nationwide network and registry of histopathology and cytopathology and The Netherlands Cancer Registry.

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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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Whether pregnancy-associated breast cancer (PABC) arise before or during pregnancy and whether this histopathology is affected by gestational age are currently unclear. The present study assesses the influence of gestational age and lactation on the histopathologic profile of PABC. We identified 744 patients with PABC (defined as breast cancer during pregnancy or 6 months following delivery).

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Purpose: Our aim was to analyze grading variation between pathology laboratories and between pathologists within individual laboratories using nationwide real-life data.

Methods: We retrieved synoptic ( = 13,397) and narrative ( = 29,377) needle biopsy reports from the Dutch Pathology Registry and prostate-specific antigen values from The Netherlands Cancer Registration for prostate cancer patients diagnosed between January 2017 and December 2019. We determined laboratory-specific proportions per histologic grade and unadjusted odds ratios (ORs) for International Society of Urological Pathologists Grades 1 vs.

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The definition of PABC is inconsistently given as either breast cancer diagnosed exclusively during pregnancy, or combined with breast cancer diagnosed within six months to five years after delivery, and sometimes even longer. The longer away from the delivery date breast cancer is diagnosed, the less clear this association with pregnancy may become. Therefore, breast cancer diagnosed during pregnancy (BCdP) may not necessarily be the same disease entity as PABC.

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Objectives: Immunohistochemical expression of programmed death-ligand 1 (PD-L1) is used as a predictive biomarker for prescription of immunotherapy to non-small cell lung cancer (NSCLC) patients. Accurate assessment of PD-L1 expression is therefore crucial. In this study, the extent of interlaboratory variation in PD-L1 positivity in the Netherlands was assessed, using real-world clinical pathology data.

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Histologic grade is a biomarker that is widely used to guide treatment of invasive breast cancer (IBC) and ductal carcinoma in situ of the breast (DCIS). Yet, currently, substantial grading variation between laboratories and pathologists exists in daily pathology practice. This study was conducted to evaluate whether an e-learning may be a feasible tool to decrease grading variation of (pre)malignant breast lesions.

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Background: Histologic grade of ductal carcinoma in situ of the breast (DCIS) may become the single biomarker that decides whether patients will be treated. Yet, evidence shows that grading variation in daily practice is substantial. To facilitate quality improvement, feedback reports, in which laboratory-specific case-mix adjusted proportions per grade were benchmarked against other laboratories, were sent to the individual laboratories by March 1, 2018.

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Aims: Histological grade is widely used to guide the management of invasive breast cancer (IBC). Yet, substantial interlaboratory and intralaboratory grading variations exist in daily pathology practice. To create awareness and to facilitate quality improvement, feedback reports, containing case-mix-adjusted laboratory-specific grades benchmarked against other laboratories, were sent to the individual laboratories by 1 March 2018.

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Accurate, consistent and reproducible grading by pathologists is of key-importance for identification of individual patients with invasive breast cancer (IBC) that will or will not benefit from adjuvant systemic treatment. We studied the laboratory-specific grading variation using nationwide real-life data to create insight and awareness in grading variation. Synoptic pathology reports of all IBC resection-specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch Pathology Registry (PALGA).

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Purpose: Patient management of invasive breast cancer (IBC) is to a large extent based on hormone- and HER2-receptor assessment. High-quality, reliable receptor assessment is of key importance as false results may lead to under- or overtreatment of patients. Surveillance of case-mix adjusted positivity rates has been suggested as a tool to identify laboratories with insufficient testing assays, as this covers the whole process of receptor assessment and enables laboratories to benchmark their positivity rates against other laboratories.

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Purpose: A considerable part of ductal carcinoma in situ (DCIS) lesions may never progress into invasive breast cancer. However, standard treatment consists of surgical excision. Trials aim to identify a subgroup of low-risk DCIS patients that can safely forgo surgical treatment based on histologic grade, which highlights the importance of accurate grading.

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