Digital Pathology in Translational Medicine and Clinical Practice

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Mechanisms of Diseases".

Deadline for manuscript submissions: 25 January 2025 | Viewed by 1046

Special Issue Editors

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Guest Editor
Department of Pathology, University Hospital of Salerno, 84131 Salerno, SA, Italy
Interests: digital pathology; computer-aided diagnosis; integrative pathology; computer vision; digital cytopathology; medical image analysis

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Guest Editor
Department of Medicine and Surgery, Pathology, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, MB, Italy
Interests: computational pathology; nephropathology; spatial proteomics; proteomics; mass spectrometry; biomarker discovery; glomerulonephritis; renal disease
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Pathology, Gravina Hospital, 95041 Caltagirone, CT, Italy
Interests: digital pathology; workflow analysis; computational pathology; public health; computer-aided diagnosis; artificial intelligence

Special Issue Information

Dear Colleagues,

Digital pathology is revolutionizing pathology departments by ensuring efficiency, safety, and productivity in traditional laboratory practices. This transformation can optimize the space utilization, working hours, and costs, ensuring a paradigm shift in diagnostic pathology. Despite its gradual implementation, fully digitizing pathology laboratories is an achievable goal.

Pathologists benefit significantly from the integration of computational techniques, as these not only accelerate the diagnostic process, but also the augment accuracy, thereby enhancing patient care. The scope of digital pathology extends across diverse domains, including primary diagnosis, telepathology, educational initiatives, and the integration of artificial intelligence. Each of these applications represents a distinct facet of digital pathology, promising to reshape the landscape of modern pathology practice.

Join us in exploring this revolution, where the convergence of technology and medical science is reshaping diagnostic paradigms.

Dr. Alessandro Caputo
Dr. Vincenzo L'Imperio
Dr. Filippo Fraggetta
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • digital pathology
  • computational pathology
  • integrative pathology
  • computer-aided diagnosis
  • artificial intelligence
  • biomarker discovery

Published Papers (1 paper)

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16 pages, 8663 KiB  
Digital Validation in Breast Cancer Needle Biopsies: Comparison of Histological Grade and Biomarker Expression Assessment Using Conventional Light Microscopy, Whole Slide Imaging, and Digital Image Analysis
by Ji Eun Choi, Kyung-Hee Kim, Younju Lee and Dong-Wook Kang
J. Pers. Med. 2024, 14(3), 312; - 16 Mar 2024
Viewed by 850
Given the widespread use of whole slide imaging (WSI) for primary pathological diagnosis, we evaluated its utility in assessing histological grade and biomarker expression (ER, PR, HER2, and Ki67) compared to conventional light microscopy (CLM). In addition, we explored the utility of digital [...] Read more.
Given the widespread use of whole slide imaging (WSI) for primary pathological diagnosis, we evaluated its utility in assessing histological grade and biomarker expression (ER, PR, HER2, and Ki67) compared to conventional light microscopy (CLM). In addition, we explored the utility of digital image analysis (DIA) for assessing biomarker expression. Three breast pathologists assessed the Nottingham combined histological grade, its components, and biomarker expression through the immunohistochemistry of core needle biopsy samples obtained from 101 patients with breast cancer using CLM, WSI, and DIA. There was no significant difference in variance between the WSI and CLM agreement rates for the Nottingham grade and its components and biomarker expression. Nuclear pleomorphism emerged as the most variable histologic component in intra- and inter-observer agreement (kappa ≤ 0.577 and kappa ≤ 0.394, respectively). The assessment of biomarker expression using DIA achieved an enhanced kappa compared to the inter-observer agreement. Compared to each observer’s assessment, DIA exhibited an improved kappa coefficient for the expression of most biomarkers with CLM and WSI. Using WSI to assess prognostic and predictive factors, including histological grade and biomarker expression in breast cancer, is acceptable. Furthermore, incorporating DIA to assess biomarker expression shows promise for substantially enhancing scoring reproducibility. Full article
(This article belongs to the Special Issue Digital Pathology in Translational Medicine and Clinical Practice)
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