Future practices of breast pathology using digital and computational pathology Review


Authors: Hanna, M. G.; Brogi, E.
Review Title: Future practices of breast pathology using digital and computational pathology
Abstract: Pathology clinical practice has evolved by adopting technological advancements initially regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and genomic sequencing. Breast pathology has a critical role as a medical domain, where the patient's pathology diagnosis has significant implications for prognostication and treatment of diseases. The advent of digital and computational pathology has brought about significant advancements in the field, offering new possibilities for enhancing diagnostic accuracy and improving patient care. Digital slide scanning enables to conversion of glass slides into high-fidelity digital images, supporting the review of cases in a digital workflow. Digitization offers the capability to render specimen diagnoses, digital archival of patient specimens, collaboration, and telepathology. Integration of image analysis and machine learning-based systems layered atop the high-resolution digital images offers novel workflows to assist breast pathologists in their clinical, educational, and research endeavors. Decision support tools may improve the detection and classification of breast lesions and the quantification of immunohistochemical studies. Computational biomarkers may help to contribute to patient management or outcomes. Furthermore, using digital and computational pathology may increase standardization and quality assurance, especially in areas with high interobserver variability. This review explores the current landscape and possible future applications of digital and computational techniques in the field of breast pathology.
Keywords: classification; image analysis; breast; histology; artificial intelligence; diagnosis; carcinoma; fish; primary; digital pathology; her2 status; machine learning; cancer; image-analysis; artificial neural-network; computational pathology; racial bias
Journal Title: Advances in Anatomic Pathology
Volume: 30
Issue: 6
ISSN: 1072-4109
Publisher: Lippincott Williams & Wilkins  
Date Published: 2023-11-01
Start Page: 421
End Page: 433
Language: English
ACCESSION: WOS:001083998300009
DOI: 10.1097/pap.0000000000000414
PROVIDER: wos
PUBMED: 37737690
Notes: Review -- Source: Wos
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  1. Edi Brogi
    516 Brogi
  2. Matthew George Hanna
    101 Hanna