Value of Artificial Intelligence in Evaluating Lymph Node Metastases
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 t...
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| Veröffentlicht in: | Cancers 2023-04, Vol.15 (9), p.2491 |
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| creator | Caldonazzi, Nicolò Rizzo, Paola Chiara Eccher, Albino Girolami, Ilaria Fanelli, Giuseppe Nicolò Naccarato, Antonio Giuseppe Bonizzi, Giuseppina Fusco, Nicola d'Amati, Giulia Scarpa, Aldo Pantanowitz, Liron Marletta, Stefano |
| description | 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. |
| doi_str_mv | 10.3390/cancers15092491 |
| format | Article |
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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.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers15092491</identifier><identifier>PMID: 37173958</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Accuracy ; Algorithms ; Artificial intelligence ; Automation ; Breast cancer ; Cytokeratin ; Deep learning ; Lymph nodes ; Lymphatic system ; Metastases ; Metastasis ; Neural networks ; Pathology ; Prognosis ; Scanners ; Systematic Review ; Tumor staging ; Workloads</subject><ispartof>Cancers, 2023-04, Vol.15 (9), p.2491</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c489t-fecd6ad06a6e9208fbbb499045bbff1f5b81b1d0fad47fd59cffceaa46cc73483</citedby><cites>FETCH-LOGICAL-c489t-fecd6ad06a6e9208fbbb499045bbff1f5b81b1d0fad47fd59cffceaa46cc73483</cites><orcidid>0000-0003-1678-739X ; 0000-0002-6959-691X ; 0000-0001-7069-7980 ; 0000-0003-3537-4929 ; 0000-0002-9992-5550 ; 0000-0002-8195-9445 ; 0000-0001-7881-8767 ; 0000-0002-9101-9131</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10177013/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10177013/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37173958$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Caldonazzi, Nicolò</creatorcontrib><creatorcontrib>Rizzo, Paola Chiara</creatorcontrib><creatorcontrib>Eccher, Albino</creatorcontrib><creatorcontrib>Girolami, Ilaria</creatorcontrib><creatorcontrib>Fanelli, Giuseppe Nicolò</creatorcontrib><creatorcontrib>Naccarato, Antonio Giuseppe</creatorcontrib><creatorcontrib>Bonizzi, Giuseppina</creatorcontrib><creatorcontrib>Fusco, Nicola</creatorcontrib><creatorcontrib>d'Amati, Giulia</creatorcontrib><creatorcontrib>Scarpa, Aldo</creatorcontrib><creatorcontrib>Pantanowitz, Liron</creatorcontrib><creatorcontrib>Marletta, Stefano</creatorcontrib><title>Value of Artificial Intelligence in Evaluating Lymph Node Metastases</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>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.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Breast cancer</subject><subject>Cytokeratin</subject><subject>Deep learning</subject><subject>Lymph nodes</subject><subject>Lymphatic system</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Neural networks</subject><subject>Pathology</subject><subject>Prognosis</subject><subject>Scanners</subject><subject>Systematic Review</subject><subject>Tumor staging</subject><subject>Workloads</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkUtPJCEUhclkzGjU9exMJW5m08qroFiZjo8Zk1Y3OltCUZcWUwUtVJn476XHHqNGILkEvnPI4SL0k-AjxhQ-tiZYSJnUWFGuyDe0Q7GkMyEU__5uv432c37AZTBGpJA_0DaTRDJVNzvo7K_pJ6iiq-Zp9M5bb_rqMozQ934Jxb_yoTp_KpAZfVhWi-dhdV9dxw6qKxhNLgvyHtpyps-wv6m76O7i_Pb0z2xx8_vydL6YWd6ocebAdsJ0WBgBiuLGtW3LlcK8blvniKvbhrSkw850XLquVtY5C8ZwYa1kvGG76OTVdzW1A3QWwphMr1fJDyY962i8_ngT_L1exidNMJESE1Ycfm0cUnycII968NmWsCZAnLKmDWG1wJTzgh5-Qh_ilELJt6Yoa6j8Z7ihlqYH7YOL5WG7NtVzyRVWQnJaqKMvqDI7GLyNAZwv5x8Ex68Cm2LOCdxbSIL1uvn6U_OL4uD937zx_1vNXgDGUqun</recordid><startdate>20230426</startdate><enddate>20230426</enddate><creator>Caldonazzi, Nicolò</creator><creator>Rizzo, Paola Chiara</creator><creator>Eccher, Albino</creator><creator>Girolami, Ilaria</creator><creator>Fanelli, Giuseppe Nicolò</creator><creator>Naccarato, Antonio Giuseppe</creator><creator>Bonizzi, Giuseppina</creator><creator>Fusco, Nicola</creator><creator>d'Amati, Giulia</creator><creator>Scarpa, Aldo</creator><creator>Pantanowitz, Liron</creator><creator>Marletta, Stefano</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1678-739X</orcidid><orcidid>https://orcid.org/0000-0002-6959-691X</orcidid><orcidid>https://orcid.org/0000-0001-7069-7980</orcidid><orcidid>https://orcid.org/0000-0003-3537-4929</orcidid><orcidid>https://orcid.org/0000-0002-9992-5550</orcidid><orcidid>https://orcid.org/0000-0002-8195-9445</orcidid><orcidid>https://orcid.org/0000-0001-7881-8767</orcidid><orcidid>https://orcid.org/0000-0002-9101-9131</orcidid></search><sort><creationdate>20230426</creationdate><title>Value of Artificial Intelligence in Evaluating Lymph Node Metastases</title><author>Caldonazzi, Nicolò ; 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| subjects | Accuracy Algorithms Artificial intelligence Automation Breast cancer Cytokeratin Deep learning Lymph nodes Lymphatic system Metastases Metastasis Neural networks Pathology Prognosis Scanners Systematic Review Tumor staging Workloads |
| title | Value of Artificial Intelligence in Evaluating Lymph Node Metastases |
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