{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T14:57:11Z","timestamp":1787497031593,"version":"build-2736575974"},"reference-count":47,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2022,10,28]],"date-time":"2022-10-28T00:00:00Z","timestamp":1666915200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Although cervical lymph node metastasis is an important prognostic factor for oral cancer, occult metastases remain undetected even by diagnostic imaging. We developed a learning model to predict lymph node metastasis in resected specimens of tongue cancer by classifying the level of immunohistochemical (IHC) staining for angiogenesis\u2010 and lymphangiogenesis\u2010related proteins using a multilayer perceptron neural network (MNN).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We obtained a dataset of 76 patients with squamous cell carcinoma of the tongue who had undergone primary tumor resection. All 76 specimens were IHC stained for the six types shown above (VEGF\u2010C, VEGF\u2010D, NRP1, NRP2, CCR7, and SEMA3E) and 456 slides were prepared. We scored the staining levels visually on all slides. We created virtual slides (4560 images) and the accuracy of the MNN model was verified by comparing it with a hue\u2013saturation (HS) histogram, which quantifies the manually determined visual information.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The accuracy of the training model with the MNN was 98.6%, and when the training image was converted to grayscale, the accuracy decreased to 52.9%. This indicates that our MNN adequately evaluates the level of staining rather than the morphological features of the IHC images. Multivariate analysis revealed that CCR7 staining level and T classification were independent factors associated with the presence of cervical lymph node metastasis in both HS histograms and MNN.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These results suggest that IHC assessment using MNN may be useful for identifying lymph node metastasis in patients with tongue cancer.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cam4.5343","type":"journal-article","created":{"date-parts":[[2022,10,29]],"date-time":"2022-10-29T00:15:01Z","timestamp":1667002501000},"page":"5312-5322","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Prediction of cervical lymph node metastasis from immunostained specimens of tongue cancer using a multilayer perceptron neural network"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2983-0943","authenticated-orcid":false,"given":"Kohei","family":"Kawamura","sequence":"first","affiliation":[{"name":"1st Department of Oral and Maxillofacial Surgery, Graduate School of Dentistry Osaka University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chonho","family":"Lee","sequence":"additional","affiliation":[{"name":"Cybermedia Center Osaka University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takashi","family":"Yoshikawa","sequence":"additional","affiliation":[{"name":"Cybermedia Center Osaka University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Al\u2010Shareef","family":"Hani","sequence":"additional","affiliation":[{"name":"Department of Oral &amp; Maxillofacial Surgery Osaka City University Graduate School of Medicine  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Usami","sequence":"additional","affiliation":[{"name":"Department of Oral Pathology Osaka University Graduate School of Dentistry  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoru","family":"Toyosawa","sequence":"additional","affiliation":[{"name":"Department of Oral Pathology Osaka University Graduate School of Dentistry  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susumu","family":"Tanaka","sequence":"additional","affiliation":[{"name":"1st Department of Oral and Maxillofacial Surgery, Graduate School of Dentistry Osaka University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0018-9523","authenticated-orcid":false,"given":"Shin\u2010Ichiro","family":"Hiraoka","sequence":"additional","affiliation":[{"name":"1st Department of Oral and Maxillofacial Surgery, Graduate School of Dentistry Osaka University  Osaka Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,10,28]]},"reference":[{"key":"e_1_2_14_2_1","first-page":"15","article-title":"Report of head and neck cancer registry of Japan clinical statistics of registered patients 2012","volume":"40","author":"Japan Society for Head and Neck Cancer Registry Committee","year":"2014","journal-title":"Jpn J Head Neck Cancer"},{"key":"e_1_2_14_3_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21654"},{"key":"e_1_2_14_4_1","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/5815493"},{"key":"e_1_2_14_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.anl.2017.02.004"},{"key":"e_1_2_14_6_1","unstructured":"National comprehensive cancer network clinical practice guidelines in oncology head and neck cancers version 3.2021.2021. 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