{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T08:46:36Z","timestamp":1773391596040,"version":"3.50.1"},"reference-count":51,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T00:00:00Z","timestamp":1559260800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["acsjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Cytopathology"],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Thyroid fine\u2010needle aspiration (FNA) plays a key role in triaging thyroid nodules. Yet many cases are assigned to indeterminate categories. The new category \u201cnoninvasive follicular thyroid neoplasm with papillary\u2010like features\u201d (NIFTP) complicates thyroid cytology. Digital image\u2010derived nuclear measurements might objectively distinguish papillary thyroid carcinoma (PTC) from benign nodules and NIFTP.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>All thyroid FNAs from 2012 to 2016 of atypia of undetermined significance (A; n\u00a0=\u00a08) and suspicious for malignancy (S; n\u00a0=\u00a02) with sufficient cellularity and surgical follow\u2010up, all FNAs preceding NIFTP (n\u00a0=\u00a06), and a random sample of PTC (n\u00a0=\u00a09) and benign (n\u00a0=\u00a010) cytology were studied. A modified Giemsa\u2010stained slide from each case was scanned using the Aperio imaging system, and long (d<jats:sub>l<\/jats:sub>) and short (d<jats:sub>s<\/jats:sub>)\u2010axis diameters were measured for 125 nuclei per case. Nuclear area and elongation were calculated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Nuclear area was larger in PTC (mean, 77.2\u00a0\u03bcm<jats:sup>2<\/jats:sup> [range, 70.6\u201086.0\u00a0\u03bcm<jats:sup>2<\/jats:sup>]) than benign (mean, 43.3\u00a0\u03bcm<jats:sup>2<\/jats:sup> [range 38.2\u201052.2\u00a0\u03bcm<jats:sup>2<\/jats:sup>]) (<jats:italic>P<\/jats:italic>\u00a0&lt;\u00a0.001). Nuclear areas from indeterminate FNAs segregated according to final histology (A\/S PTC mean 72.7\u00a0\u03bcm<jats:sup>2<\/jats:sup>, A\/S benign mean 53.7\u00a0\u03bcm<jats:sup>2<\/jats:sup>; <jats:italic>P<\/jats:italic>\u00a0=\u00a00.004), and were not significantly different from definitive FNAs of the same diagnosis. NIFTP nuclear area was smaller than PTC (mean, 54.8\u00a0\u03bcm<jats:sup>2<\/jats:sup> [range, 46.7\u201066.1\u00a0\u03bcm<jats:sup>2<\/jats:sup>]; <jats:italic>P<\/jats:italic>\u00a0&lt;\u00a0.001). Nuclear elongation showed similar results, but with greater group overlap.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Nuclear area and elongation can be calculated using a commercial digital imager; both correlate with the final surgical pathology diagnosis of PTC versus benign, including NIFTP. Area provides greater resolution than elongation. This technique could be used to resolve indeterminate cytology in which PTC is considered.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cncy.22120","type":"journal-article","created":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T09:10:51Z","timestamp":1559293851000},"page":"501-513","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Digital image\u2010assisted quantitative nuclear analysis improves diagnostic accuracy of thyroid fine\u2010needle aspiration cytology"],"prefix":"10.1002","volume":"127","author":[{"given":"Krista","family":"Chain","sequence":"first","affiliation":[{"name":"University of Maryland School of Medicine Baltimore Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Teklu","family":"Legesse","sequence":"additional","affiliation":[{"name":"University of Maryland School of Medicine Baltimore Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathon E.","family":"Heath","sequence":"additional","affiliation":[{"name":"University of Maryland School of Medicine Baltimore Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6526-5750","authenticated-orcid":false,"given":"Paul N.","family":"Staats","sequence":"additional","affiliation":[{"name":"University of Maryland School of Medicine Baltimore Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2019,5,31]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"National Cancer Institute: Surveillance Epidemiology and End Results Program.Cancer stat facts: cancer of the thyroid.http:\/\/seer.cancer.gov\/statfacts\/html\/thyro.html. 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