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Quantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms

DC FieldValueLanguage
dc.contributor.author곽진영-
dc.contributor.author김은경-
dc.contributor.author남세진-
dc.contributor.author문희정-
dc.contributor.author유재흥-
dc.contributor.author윤정현-
dc.contributor.author이혜선-
dc.date.accessioned2017-02-24T11:23:36Z-
dc.date.available2017-02-24T11:23:36Z-
dc.date.issued2016-
dc.identifier.issn0278-4297-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/146755-
dc.description.abstractOBJECTIVES: To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules. METHODS: From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated. RESULTS: A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P < .001), kurtosis (3.898 ± 2.652 versus 6.251 ± 9.102; P < .001), entropy (0.16 ± 0.135 versus 0.239 ± 0.185; P < .001), and principal component analysis index (-0.386±0.774 versus 0.134 ± 0.889; P < .001) were significantly different between the malignant and benign nodules. With the calculated cutoff values, the areas under the curve were 0.681 (95% confidence interval, 0.643-0.721) for standard deviation, 0.661 (0.620-0.703) for principal component analysis index, 0.651 (0.607-0.691) for kurtosis, 0.638 (0.596-0.681) for entropy, and 0.606 (0.563-0.647) for skewness. The subjective analysis of grayscale sonograms by radiologists alone showed an area under the curve of 0.861 (0.833-0.888). CONCLUSIONS: Grayscale histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms.-
dc.description.statementOfResponsibilityrestriction-
dc.format.extent775~782-
dc.languageEnglish-
dc.publisherAmerican Institute of Ultrasound in Medicine-
dc.relation.isPartOfJOURNAL OF ULTRASOUND IN MEDICINE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHAlgorithms*-
dc.subject.MESHData Interpretation, Statistical-
dc.subject.MESHDiagnosis, Differential-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHImage Enhancement/methods*-
dc.subject.MESHImage Interpretation, Computer-Assisted/methods*-
dc.subject.MESHMale-
dc.subject.MESHNumerical Analysis, Computer-Assisted-
dc.subject.MESHReproducibility of Results-
dc.subject.MESHSensitivity and Specificity-
dc.subject.MESHThyroid Nodule/diagnostic imaging*-
dc.subject.MESHUltrasonography/methods*-
dc.titleQuantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms-
dc.typeArticle-
dc.publisher.locationUnited States-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Radiology-
dc.contributor.googleauthorSe Jin Nam-
dc.contributor.googleauthorJaeheung Yoo-
dc.contributor.googleauthorHye Sun Lee-
dc.contributor.googleauthorEun-Kyung Kim-
dc.contributor.googleauthorHee Jung Moon-
dc.contributor.googleauthorJung Hyun Yoon-
dc.contributor.googleauthorJin Young Kwak-
dc.identifier.doi10.7863/ultra.15.05055-
dc.contributor.localIdA00182-
dc.contributor.localIdA00801-
dc.contributor.localIdA01255-
dc.contributor.localIdA01397-
dc.contributor.localIdA04609-
dc.contributor.localIdA02595-
dc.contributor.localIdA03312-
dc.relation.journalcodeJ01920-
dc.identifier.eissn1550-9613-
dc.identifier.pmid26969596-
dc.identifier.urlhttp://www.jultrasoundmed.org/content/35/4/775.long-
dc.subject.keywordhead and neck ultrasound-
dc.subject.keywordhistogram analysis-
dc.subject.keywordsonography-
dc.subject.keywordthyroid cancer-
dc.subject.keywordthyroid gland-
dc.contributor.alternativeNameKwak, Jin Young-
dc.contributor.alternativeNameKim, Eun Kyung-
dc.contributor.alternativeNameNam, Se Jin-
dc.contributor.alternativeNameMoon, Heui Jeong-
dc.contributor.alternativeNameYoo, Jae Heung-
dc.contributor.alternativeNameYoon, Jung Hyun-
dc.contributor.alternativeNameLee, Hye Sun-
dc.contributor.affiliatedAuthorKwak, Jin Young-
dc.contributor.affiliatedAuthorKim, Eun-Kyung-
dc.contributor.affiliatedAuthorNam, Se Jin-
dc.contributor.affiliatedAuthorMoon, Heui Jeong-
dc.contributor.affiliatedAuthorYoo, Jae Heung-
dc.contributor.affiliatedAuthorYoon, Jung Hyun-
dc.contributor.affiliatedAuthorLee, Hye Sun-
dc.citation.volume35-
dc.citation.number4-
dc.citation.startPage775-
dc.citation.endPage782-
dc.identifier.bibliographicCitationJOURNAL OF ULTRASOUND IN MEDICINE, Vol.35(4) : 775-782, 2016-
dc.date.modified2017-02-24-
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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