Digital Technology in Diagnostic Breast Pathology and Immunohistochemistry

Digital technology has been used in the field of diagnostic breast pathology and immunohistochemistry (IHC) for decades. Examples include automated tissue processing and staining, digital data processing, storing and management, voice recognition systems, and digital technology-based production of antibodies and other IHC reagents. However, the recent application of whole slide imaging technology and artificial intelligence (AI)-based tools has attracted a lot of attention. The use of AI tools in breast pathology is discussed briefly as it is covered in other reviews. Here, we present the main application of digital technology in IHC. This includes automation of IHC staining, using image analysis systems and computer vision technology to interpret IHC staining, and the use of AI-based tools to predict marker expression from haematoxylin and eosin-stained digitalized images.

Risk factors for dyshormonal benign hyperplasia and breast cancer

Risk factors for the occurrence of benign diseases and breast cancer were studied in a comparative analysis of the survey data of 321 women who were operated on the mammary gland, had an established histological diagnosis and were registered in the oncology offices of the Kursk polyclinics (main group), and 150 women who did not have any clinical , no objective manifestations of breast pathology (comparison group). To study the frequency of dyshormonal hyperplasias of the mammary glands and risk factors in girls, an in-depth preventive examination of 390 schoolgirls aged 13-17 years was carried out.

Sistema Internacional Yokohama para el informe de la citología mamaria. Academia Internacional de Citología

Fine needle aspiration biopsy cytology is part of the diagnostic triad in the evaluation of breast pathology, along with clinical and mammography or ultrasound findings. The Yokohama international system of the International Agency for Cytology has been proposed to report fine needle puncture-aspiration biopsy breast cytology, through 5 diagnostic categories: Inadequate/insufficient, benign, atypical, suspicious for malignancy and malignant, including in each of these definitions, key cytological diagnostic criteria and suggestions for clinical management. The objective of this article was to know the guidelines of this new breast cytological classification system for its implementation in this region. Fine needle puncture-aspiration biopsy is a precise and effective method to diagnose different breast lesions, which requires an adequate cell sample and a precise cytomorphological interpretation. The application of standardized Yokohama system will allow to improve the evaluation, diagnosis and clinical management of the breast pathology. Keywords: Breast cytology. Fine-needle aspiration biopsy (FNAB). Reporting system Yokohama.

Assessment of mitotic activity in breast cancer: revisited in the digital pathology era

The assessment of cell proliferation is a key morphological feature for diagnosing various pathological lesions and predicting their clinical behaviour. Visual assessment of mitotic figures in routine histological sections remains the gold-standard method to evaluate the proliferative activity and grading of cancer. Despite the apparent simplicity of such a well-established method, visual assessment of mitotic figures in breast cancer (BC) remains a challenging task with low concordance among pathologists which can lead to under or overestimation of tumour grade and hence affects management. Guideline recommendations for counting mitoses in BC have been published to standardise methodology and improve concordance; however, the results remain less satisfactory. Alternative approaches such as the use of the proliferation marker Ki67 have been recommended but these did not show better performance in terms of concordance or prognostic stratification. The advent of whole slide image technology has brought the issue of mitotic counting in BC into the light again with more challenges to develop objective criteria for identifying and scoring mitotic figures in digitalised images. Using reliable and reproducible morphological criteria can provide the highest degree of concordance among pathologists and could even benefit the further application of artificial intelligence (AI) in breast pathology, and this relies mainly on the explicit description of these figures. In this review, we highlight the morphology of mitotic figures and their mimickers, address the current caveats in counting mitoses in breast pathology and describe how to strictly apply the morphological criteria for accurate and reliable histological grade and AI models.