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Malignancy Risk Stratification of Thyroid Nodules: Comparison between the Thyroid Imaging Reporting and Data System and the

DC Field Value Language
dc.contributor.author곽진영-
dc.contributor.author김은경-
dc.contributor.author문희정-
dc.contributor.author윤정현-
dc.contributor.author이혜선-
dc.date.accessioned2017-02-24T03:37:28Z-
dc.date.available2017-02-24T03:37:28Z-
dc.date.issued2016-
dc.identifier.issn0033-8419-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/146396-
dc.description.abstractPURPOSE: To compare malignancy risk stratification of thyroid nodules with the 2014 American Thyroid Association (ATA) management guidelines and the Thyroid Imaging Reporting and Data System (TIRADS). MATERIALS AND METHODS: This retrospective study was approved by the institutional review board. The requirement to obtain informed consent was waived. From November 2013 to July 2014, 1293 thyroid nodules in 1241 patients (mean age, 50.8 years ± 13.5) were included in this study. All nodules measured at least 10 mm. Solidity, hypoechogenicity or marked hypoechogenicity, microlobulated to irregular margin, microcalcifications or mixed calcifications, and nonparallel shape were considered suspicious features at ultrasonography (US). A TIRADS category and the US pattern as determined with ATA guidelines were assigned to each nodule. The correlation between the TIRADS category or ATA pattern and the malignancy rate was evaluated with the Spearman rank test. RESULTS: Of the 1293 thyroid nodules, 1059 (81.9%) were benign and 234 (18.1%) were malignant. Forty-four of the 1293 nodules (3.4%) did not meet the criteria for the ATA patterns and were classified as "not specified." The malignancy rates of TIRADS category 3, 4a, 4b, 4c, and 5 nodules were 1.9% (six of 316 nodules), 4.2% (17 of 408 nodules), 12.9% (33 of 256 nodules), 49.8% (130 of 261 nodules), and 92.3% (48 of 52 nodules), respectively, with significant differences between categories (P < .001). Malignancy rates of nodules with very low, low, intermediate, and high suspicion for malignancy with the ATA guidelines and not specified patterns were 2.7% (11 of 407 nodules), 3.1% (10 of 323 nodules), 16.7% (39 of 233 nodules), 58.0% (166 of 286 nodules), and 18.2% (eight of 44 nodules), respectively, with significant differences between patterns (P < .001). There was high correlation between classification with TIRADS (r = 1.000, P < .001) and ATA guidelines (r = 0.900, P = 0.037), without statistically significant differences (P = .873). CONCLUSION: Both TIRADS and the ATA guidelines provide effective malignancy risk stratification for thyroid nodules. Nodules that do not meet the criteria for a specific pattern with the ATA guidelines have a relatively high risk of malignancy (18.2%).-
dc.description.statementOfResponsibilityrestriction-
dc.format.extent917~924-
dc.languageEnglish-
dc.publisherRadiological Society of North America-
dc.relation.isPartOfRADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHAdolescent-
dc.subject.MESHAdult-
dc.subject.MESHAged-
dc.subject.MESHAged, 80 and over-
dc.subject.MESHBiopsy, Fine-Needle-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPractice Guidelines as Topic-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHRisk Assessment-
dc.subject.MESHThyroid Nodule/diagnostic imaging-
dc.subject.MESHThyroid Nodule/epidemiology-
dc.subject.MESHThyroid Nodule/pathology*-
dc.subject.MESHUltrasonography-
dc.subject.MESHUnited States/epidemiology-
dc.titleMalignancy Risk Stratification of Thyroid Nodules: Comparison between the Thyroid Imaging Reporting and Data System and the-
dc.typeArticle-
dc.publisher.locationUnited States-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Radiology-
dc.contributor.googleauthorJung Hyun Yoon-
dc.contributor.googleauthorHye Sun Lee-
dc.contributor.googleauthorEun-Kyung Kim-
dc.contributor.googleauthorHee Jung Moon-
dc.contributor.googleauthorJin Young Kwak-
dc.identifier.doi10.1148/radiol.2015150056-
dc.contributor.localIdA00182-
dc.contributor.localIdA00801-
dc.contributor.localIdA01397-
dc.contributor.localIdA02595-
dc.contributor.localIdA03312-
dc.relation.journalcodeJ02596-
dc.identifier.eissn1527-1315-
dc.identifier.pmid26348102-
dc.identifier.urlhttp://pubs.rsna.org/doi/abs/10.1148/radiol.2015150056-
dc.contributor.alternativeNameKwak, Jin Young-
dc.contributor.alternativeNameKim, Eun Kyung-
dc.contributor.alternativeNameMoon, Heui Jeong-
dc.contributor.alternativeNameYoon, Jung Hyun-
dc.contributor.alternativeNameLee, Hye Sun-
dc.contributor.affiliatedAuthorKwak, Jin Young-
dc.contributor.affiliatedAuthorKim, Eun-Kyung-
dc.contributor.affiliatedAuthorMoon, Heui Jeong-
dc.contributor.affiliatedAuthorYoon, Jung Hyun-
dc.contributor.affiliatedAuthorLee, Hye Sun-
dc.citation.volume278-
dc.citation.number3-
dc.citation.startPage917-
dc.citation.endPage924-
dc.identifier.bibliographicCitationRADIOLOGY, Vol.278(3) : 917-924, 2016-
dc.date.modified2017-02-24-
dc.identifier.rimsid47904-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers

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