• Journal of radiological science and technology
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• v.38 no.2
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• pp.145-153
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• 2015

Thyroid nodules are an endocrine disease often found in clinical practice, and patients with thyroid nodules found by chance have rapidly increased alongside development of thyroid ultrasound techniques for health examination purposes. This study analyzes the subjects' general characteristics, thyroid ultrasounds, and fine needle aspiration cytology in order to find out the relationship between male and female thyroid nodules and thyroid cancer frequency. An ultrasound examination of the thyroid was performed for 32,973 individuals who visited the K Hospital of Health Examination. Subjects have no history of thyroid disease and are 20 years old or over. Data of general characteristics, diabetes) was collected by a written survey completed by the subject, and the ultrasound of the thyroid(thyroid nodules existence, size, number) and FNAC was used to find out the malignancy rate. Frequency of patients with thyroid nodule was 4,611(26.1%) in men and 5,341(34.9%) in women between 32,973 individuals. Women's prevalence rate is significantly higher than men, and the prevalence rate significantly increased with age in men and women(p < 0.05). The prevalence of multiple nodules was significantly higher in women(43.5%) than in men(35.6%), and significantly increased with age in men and women(p < 0.05). The fine needle aspiration cytology was performed in 692(men 342, women 350) subjects who showed signs of malignancy through ultrasound. Prevalence of malignancy of the nodules was higher in men(33.3%) than in women(29.4%) although it is not statistically significant. It is known that thyroid nodule prevalence in women is much higher than in men. But this study shows the men's prevalence rate was not too low compared with women, and the men showed a rather higher malignancy rate in nodules than women. It is considered that the role of thyroid ultrasound is both important in men and women.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.473-479
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• 2021

The diagnostic criteria for diffuse thyroid disease are ambiguous and there are many errors due to the subjective diagnosis of experts. Also, studies on ultrasound imaging of thyroid nodules have been actively conducted, but studies on diffuse thyroid disease are insufficient. In this study, features were extracted by applying the GLCM algorithm to ultrasound images of normal and diffuse thyroid disease, and quantitative analysis was performed using the extracted feature values. Using the GLCM algorithm for thyroid ultrasound images of patients diagnosed at W hospital, 199 normal cases, 132 mild cases, and 99 moderate cases, a region of interest (50×50 pixel) was set for a total of 430 images, and Autocorrelation, Sum of squares, sum average, sum variance, cluster prominence, and energy were analyzed using six parameters. As a result, in autocorrelation, sum of squares, sum average, and sum variance four parameters, Normal, Mild, and Moderate were distinguished with a high recognition rate of over 90%. This study is valuable as a criterion for classifying the severity of diffuse thyroid disease in ultrasound images using the GLCM algorithm. By applying these parameters, it is expected that errors due to visual reading can be reduced in the diagnosis of thyroid disease and can be utilized as a secondary means of diagnosing diffuse thyroid disease.

• Journal of the Korean Society of Radiology
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• v.18 no.4
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• pp.317-325
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• 2024

This study aimed to classify normal and nodule images in thyroid ultrasound images using GLCM and machine learning. The research was conducted on 600 patients who visited S Hospital in Busan and were diagnosed with thyroid nodules using thyroid ultrasound. In the thyroid ultrasound images, the ROI was set to a size of 50x50 pixels, and 21 parameters and 4 angles were used with GLCM to analyze the normal thyroid patterns and thyroid nodule patterns. The analyzed data was used to distinguish between normal and nodule diagnostic results using the SVM model and KNN model in MATLAB. As a result, the accuracy of the thyroid nodule classification rate was 94% for SVM model and 91% for the KNN model. Both models showed an accuracy of over 90%, indicating that the classification rate is excellent when using machine learning for the classification of normal thyroid and thyroid nodules. In the ROC curve, the ROC curve for the SVM model was generally higher compared to the KNN model, indicating that the SVM model has higher within-sample performance than the KNN model. Based on these results, the SVM model showed high accuracy in diagnosing thyroid nodules. This result can be used as basic data for future research as an auxiliary tool for medical diagnosis and is expected to contribute to the qualitative improvement of medical services through machine learning technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.956-962
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• 2022

Diffuse thyroid disease has ambiguous diagnostic criteria and many errors occur according to the subjective diagnosis of skilled practitioners. If image processing technology is applied to ultrasound images, quantitative data is extracted, and applied to a computer auxiliary diagnostic system, more accurate and political diagnosis is possible. In this paper, 19 parameters were extracted by applying the Gray level co-occurrence matrix (GLCM) algorithm to ultrasound images classified as normal, mild, and moderate in patients with thyroid disease. Using these parameters, an artificial neural network (ANN) was applied to analyze diffuse thyroid ultrasound images. The final classification rate using ANN was 96.9%. Using the results of the study, it is expected that errors caused by visual reading in the diagnosis of thyroid diseases can be reduced and used as a secondary means of diagnosing diffuse thyroid diseases.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.201-207
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• 2019

This study has evaluated whether the method of using the combination of different risk group, according to K-TIRADS classification and K-TIRADS classification in thyroid ultrasonography is useful in a differential diagnosis of benign and malignant nodules. The subject was patients underwent thyroid ultrasonography and retrospective analysis were performed based on the results of fine needle aspiration cytology. A chi-square test was performed for the difference analysis of the score system in K-TIRADS and different risk group according to the benign and malignant of thyroid nodule. The optimized cut off value was determined by the K-TIRADS score and different risk group to predict malignant nodule through ROC curve analysis. In the differential verification result of K-TIRADS and different risk group, according to the classification of benign and malignant nodule group each showed significant difference statistically(p=.001). In the point classification according to K-TIRADS for the prediction of benign and malignant in ROC curve analysis showed AUC 0.786, Cut-off value>2(p=.001), and in the different risk group, it was decided as AUC 0.640, Cut-off value>2(p=.001). When discovering the nodule in thyroid ultrasound, it is considered that the K-TIRADAS which helps in identifying benign and malignant thyroid nodules, it is considered to be helpful in the differential diagnosis of thyroid nodules, than the classification system according to Different risk group, and when applying the classification system according to K-TIRADS, it is considered that it can reduce unnecessary fine needle aspiration cytology and could be helpful in finding the malignant nodules early.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.290-297
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• 2016

This study analyzed the features of the nodules requiring a fine needle aspiration, which were found in thyroid ultrasonography of the employee health check-up examinees. Based on the fine needle aspiration results, over 1 cm nodules or those implying malignancy on the ultrasonography were categorized into the 1st group. Whereas, regardless of the size the fine needle aspiration results implying malignancy on the ultrasonography were categorized into the 2nd group. In the 1st group, 15.8% were malignant, and in the 2nd group, 28% were malignant. The findings implying malignancy were statistically significant. However, even though the nodules were larger than 1 cm, when the nodules were not accompanied by a high risk factor and showed a spongiform structure in the ultrasonographic results, most of them were benign, and a fine needle aspiration was not required. The ultrasonographic findings are important rationales in making a decision on whether or not a fine needle aspiration is required for thyroid nodules. Currently, the fine needle aspiration for thyroid nodules is commonly performed when the size of the nodule is larger than 1 cm, even though it has a spongiform structure, to relieve the patient's anxiety. However, if ultrasonographic findings of thyroid are correctly understood in differentiating malignant from benign nodules, unnecessary fine needle aspiration can be avoided.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.237-243
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• 2017

This study evaluated the applicability of computer-aided diagnosis by retrospective analysis of GLCM algorithm based on cytopathological diagnosis of normal and malignant nodules in thyroid ultrasound images. In the experiment, the recognition rate and ROC curve of thyroid malignant nodule were analyzed using 6 parameters of GLCM algorithm. Experimental results showed 97% energy, 93% contrast, 92% correlation, 92% homogeneity, 100% entropy and 100% variance. Statistical analysis showed that the area under the curve of each parameter was more than 0.947 (p = 0.001) in the ROC curve, which was significant in the recognition of thyroid malignant nodules. In the GLCM, the cut-off value of each parameter can be used to predict the disease through analysis of quantitative computer-aided diagnosis.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.227-234
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• 2017

This study evaluated the usefulness of the elasticity score and strain ratio in the differential diagnosis of benign and malignant nodules in thyroid elastography. We performed a retrospective analysis based on the results of fine needle aspiration cytology. The Chi-square test and the Mann-Whitney U test were used to analyze the difference between the five degrees of elasticity score and strain ratio according to the benign and malignant thyroid nodules. ROC curve analysis was used to determine the elasticity score and the best cut-off value of the strain ratio for the prediction of malignant nodules. There was a statistically significant difference (p=0.000) between the homogeneity of the elasticity score and the difference of the strain ratio between the benign and malignant nodule groups. On the ROC curve analysis, the elasticity score and the srain ratio for predicting benign and malignant nodules were determined as AUC 0.842, 0.700, cut-off value 3, 2.49 (p=0.001). Therefore, the elasticity score and strain ratio may be useful in the differential diagnosis of thyroid nodules.

• Clinical and Experimental Pediatrics
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• v.49 no.9
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• pp.1005-1009
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• 2006

A rare case is described of an intrathyroidal branchial cleft-like cyst in neonate. The patient was a newborn girl with a mass in the left lateral neck. The ultrasonography and computed tomography revealed a cystic lesion in the left thyroid. The lesion was enucleated surgically from the thyroid. Histologically, the cyst was lined by squamous or columnar epithelium and contained inflammatory cell infiltraion, thyroid and parathyroid tissue. The patient has been doing well without any evidence of thyroid dysfunction for 15 months.

• Clinical and Experimental Pediatrics
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• v.53 no.2
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• pp.158-162
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• 2010

Purpose : Turner syndrome (TS) is a disorder in which various anomalies can be accompanied, especially cardiovascular, renal, thyroid and auditory problems. The aim of this study is to identify the incidence of these disorders in patients with TS according to karyotype. Methods : We reviewed medical records of 90 patients with TS diagnosed by chromosomal analysis in 4 hospitals from Jan 1998 to Dec 2007. We evaluated these cases by prepared protocol of 4 medical problems.Results : The distribution of karyotype was 45,X (47.8%), mosaic pattern (34.4%) and structural aberration group (17.8%). Renal anomalies, cardiovascular anomalies, thyroid disorders and auditory problems are accompanied in 4.4%, 10.0 %, 11.1% and 5.6%, respectively. 45,X group had renal anomalies (7.0%), cardiovascular anomalies (18.6%), thyroid disorders (9.3%) and auditory problems (11.6%). Mosaic group had renal anomalies (3.2%), thyroid disorders (12.9%), no cardiovascular anomalies and auditory problems. Structural aberration group had cardiovascular anomalies (6.3%), thyroid disorders (12.5%) and no other 2 problems. Patients with 45,X group had a significant higher incidence of cardiovascular anomalies (P =0.025). Conclusion : Our results indicate that there are differences clinically according to karyotype of TS, especially in incidence of cardiovascular anomalies.