Value of Artificial Intelligence in Evaluating Lymph Node Metastases

Nicolò Caldonazzi; Paola Chiara Rizzo; Albino Eccher; Ilaria Girolami; Giuseppe Nicolò Fanelli; Antonio Giuseppe Naccarato; Giuseppina Bonizzi; Nicola Fusco; Giulia d’Amati; Aldo Scarpa; Liron Pantanowitz; Stefano Marletta

doi:10.3390/cancers15092491

Cancers (Apr 2023)

Value of Artificial Intelligence in Evaluating Lymph Node Metastases

Nicolò Caldonazzi,
Paola Chiara Rizzo,
Albino Eccher,
Ilaria Girolami,
Giuseppe Nicolò Fanelli,
Antonio Giuseppe Naccarato,
Giuseppina Bonizzi,
Nicola Fusco,
Giulia d’Amati,
Aldo Scarpa,
Liron Pantanowitz,
Stefano Marletta

Affiliations

Nicolò Caldonazzi: Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy
Paola Chiara Rizzo: Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy
Albino Eccher: Department of Pathology and Diagnostics, University and Hospital Trust of Verona, 37126 Verona, Italy
Ilaria Girolami: Department of Pathology, Lehrkrankenhaus der Paracelsus Medizinischen Privatuniversität, Provincial Hospital of Bolzano (SABES-ASDAA), 39100 Bolzano-Bozen, Italy
Giuseppe Nicolò Fanelli: Division of Pathology, Department of Translational Research, New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
Antonio Giuseppe Naccarato: Division of Pathology, Department of Translational Research, New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
Giuseppina Bonizzi: Division of Pathology, IEO, Europefan Institute of Oncology IRCCS, University of Milan, 20122 Milan, Italy
Nicola Fusco: Division of Pathology, IEO, Europefan Institute of Oncology IRCCS, University of Milan, 20122 Milan, Italy
Giulia d’Amati: Department of Radiology, Oncology and Pathology, Sapienza, University of Rome, 00185 Rome, Italy
Aldo Scarpa: Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy
Liron Pantanowitz: Department of Pathology, University of Michigan, Ann Arbor, MI 48104, USA
Stefano Marletta: Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37134 Verona, Italy

DOI: https://doi.org/10.3390/cancers15092491
Journal volume & issue: Vol. 15, no. 9
p. 2491

Abstract

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One of the most relevant prognostic factors in cancer staging is the presence of lymph node (LN) metastasis. Evaluating lymph nodes for the presence of metastatic cancerous cells can be a lengthy, monotonous, and error-prone process. Owing to digital pathology, artificial intelligence (AI) applied to whole slide images (WSIs) of lymph nodes can be exploited for the automatic detection of metastatic tissue. The aim of this study was to review the literature regarding the implementation of AI as a tool for the detection of metastases in LNs in WSIs. A systematic literature search was conducted in PubMed and Embase databases. Studies involving the application of AI techniques to automatically analyze LN status were included. Of 4584 retrieved articles, 23 were included. Relevant articles were labeled into three categories based upon the accuracy of AI in evaluating LNs. Published data overall indicate that the application of AI in detecting LN metastases is promising and can be proficiently employed in daily pathology practice.

Published in Cancers

ISSN: 2072-6694 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://www.mdpi.com/journal/cancers/

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