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

 Se Jin Nam  ;  Jaeheung Yoo  ;  Hye Sun Lee  ;  Eun-Kyung Kim  ;  Hee Jung Moon  ;  Jung Hyun Yoon  ;  Jin Young Kwak 
 JOURNAL OF ULTRASOUND IN MEDICINE, Vol.35(4) : 775-782, 2016 
Journal Title
Issue Date
Algorithms* ; Data Interpretation, Statistical ; Diagnosis, Differential ; Female ; Humans ; Image Enhancement/methods* ; Image Interpretation, Computer-Assisted/methods* ; Male ; Numerical Analysis, Computer-Assisted ; Reproducibility of Results ; Sensitivity and Specificity ; Thyroid Nodule/diagnostic imaging* ; Ultrasonography/methods*
head and neck ultrasound ; histogram analysis ; sonography ; thyroid cancer ; thyroid gland
OBJECTIVES: 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.
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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
Yonsei Authors
Kwak, Jin Young(곽진영) ORCID logo https://orcid.org/0000-0002-6212-1495
Kim, Eun-Kyung(김은경) ORCID logo https://orcid.org/0000-0002-3368-5013
Nam, Se Jin(남세진)
Moon, Hee Jung(문희정) ORCID logo https://orcid.org/0000-0002-5643-5885
Yoo, Jae Heung(유재흥)
Yoon, Jung Hyun(윤정현) ORCID logo https://orcid.org/0000-0002-2100-3513
Lee, Hye Sun(이혜선) ORCID logo https://orcid.org/0000-0001-6328-6948
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