Normal thyroid designated “normal” CT diagnosis in a 28-year-old woman (papillary thyroid carcinoma in the left thyroid). The thyroid gland shows iso- and homogeneous attenuation in nonenhanced CT image (a) and anteroposterior diameter of 1-2 cm, smooth margin, and homogeneous enhancement in contrast-enhanced CT image (b).

Normal thyroid designated “normal” CT diagnosis in a 28-year-old woman (papillary thyroid carcinoma in the left thyroid). The thyroid gland shows iso- and homogeneous attenuation in nonenhanced CT image (a) and anteroposterior diameter of 1-2 cm, smooth margin, and homogeneous enhancement in contrast-enhanced CT image (b).

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Objective. This study aimed to evaluate the CT features of incidentally detected DTD in the patients who underwent thyroidectomy and to assess the diagnostic accuracy of CT diagnosis. Methods. We enrolled 209 consecutive patients who received preoperative neck CT and subsequent thyroid surgery. Neck CT in each case was retrospectively investigated...

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... Cross-sectional studies have shown that thyroid CT densities in conditions such as chronic thyroiditis and hypothyroidism typically range from 36 to 81 Hounsfield units (HUs), which is are significantly lower than the normal range of 80-120 HU [7][8][9][10]. This decreased CT density can be attributed to the Life 2023, 13, 2303 2 of 11 replacement of thyroid follicular cells, infiltration of inflammatory cells, and subsequent fibrosis [7,8,[11][12][13]. ...
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This study aimed to explore the relationship between thyroid-stimulating hormone (TSH) elevation and the baseline computed tomography (CT) density and volume of the thyroid. We examined 86 cases with new-onset hypothyroidism (TSH > 4.5 IU/mL) and 1071 controls from a medical check-up database over 5 years. A deep learning-based thyroid segmentation method was used to assess CT density and volume. Statistical tests and logistic regression were employed to determine differences and odds ratios. Initially, the case group showed a higher CT density (89.8 vs. 81.7 Hounsfield units (HUs)) and smaller volume (13.0 vs. 15.3 mL) than those in the control group. For every +10 HU in CT density and −3 mL in volume, the odds of developing hypothyroidism increased by 1.40 and 1.35, respectively. Over the course of the study, the case group showed a notable CT density reduction (median: −8.9 HU), whereas the control group had a minor decrease (−2.9 HU). Thyroid volume remained relatively stable for both groups. Higher CT density and smaller thyroid volume at baseline are correlated with future TSH elevation. Over time, there was a substantial and minor decrease in CT density in the case and control groups, respectively. Thyroid volumes remained consistent in both cohorts.
... Besides that, Rho et al. has reported that some diffuse thyroid disease (e.g. Hashimoto's thyroiditis [HT]) could also result in inhomogeneous low attenuation of thyroid on CT images due to hypo-function [16]. However, to the best of our acknowledge, the study evaluating the influence of physiological factors (e.g. ...
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... Although clinical and laboratory findings have played a key role in the diagnosis and treatment of DTD, the use of thyroid US for detecting DTD is feasible (4)(5)(6)(7). Moreover, recent studies have demonstrated that computed tomography (CT) may be helpful to detect DTD (8)(9)(10). CT detection of DTD may be practical, as CT is widely used in the evaluation of neck lesions. ...
... In the literature, the known US features of normal thyroid parenchyma included a fine echotexture, iso-echogenicity, a smooth margin, a normal glandular size, and normal parenchymal vascularity (4-7). In contrast, the known CT features of normal thyroid parenchyma include iso-attenuation, homogeneous attenuation, an anteroposterior diameter of 1-2 cm, smooth margin, and homogeneous enhancement (8)(9)(10). In the present MRI study, the thyroid gland was compared with adjacent muscle. ...
... In the literature, the reported US features of DTD include increased or decreased parenchymal echogenicity, coarse echotexture or "micronodulation, " increased or decreased anteroposterior diameter of the thyroid gland, presence of marginal nodularity, and increased or decreased parenchymal vascularity (4)(5)(6)(7). In contrast, the CT features suggestive of DTD include low attenuation, inhomogeneous attenuation, increased glandular size, lobulated margin, and inhomogeneous enhancement (8)(9)(10). In the present MRI study, SI, glandular size or margin, and parenchymal enhancement may be different between normal thyroid parenchyma and DTD. ...
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... Therefore, regular monitoring of patients with DTD is performed at many institutions. Cases of symptomatic DTD are easily diagnosed by clinical and serological examinations, such as thyroid autoantibody or thyroid function tests; however, reliable diagnostic tools for detecting asymptomatic or subclinical DTD have not been established [5][6][7][8]. ...
... Thus, the establishment of specific CT features for detecting asymptomatic or subclinical DTD may be useful for managing patients with asymptomatic or subclinical DTD. Recently, some studies suggest that US and CT of the thyroid gland may be helpful for detecting and managing asymptomatic or subclinical DTD [5][6][7][8]. However, the role of imaging-based DTD diagnoses remains controversial despite technological advances and increasing use of ultrasonography and CT in daily clinical practice. ...
... The following CT features of the thyroid gland were retrospectively investigated: the degree (iso-[normal], decreased, or increased) and pattern (homogeneous or inhomogeneous) of parenchymal attenuation, glandular size (1-2 cm [normal], <1 cm, or >2 cm) and margin (smooth or lobulated), and degree (iso-[normal], decreased, or increased) and pattern (homogeneous or inhomogeneous) of parenchymal enhancement [6,7,9]. The Hounsfield unit (HU) values were measured separately in both thyroid lobes by using regions of interest that were placed on non-enhanced and contrast-enhanced CT images, respectively, and then averaged. ...
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This study aimed to assess the diagnostic performance of computed tomography (CT) for differentiating diffuse thyroid disease (DTD) from normal thyroid parenchyma (NTP) using multicenter data. Between January 2016 and June 2016, 229 patients underwent preoperative neck CT and subsequent thyroid surgery at five participating institutions. The neck CT images of each patient were retrospectively reviewed and classified into the following four categories: no DTD, indeterminate, suspicious for DTD, and DTD. The results of the CT image evaluations were compared with the histopathological results to determine the diagnostic accuracy of CT at each institution. According to the histopathological results, there were NTP (n = 151), Hashimoto thyroiditis (n = 24), non-Hashimoto lymphocytic thyroiditis (n = 47), and diffuse hyperplasia (n = 7). The CT categories of the 229 patients were “no DTD” in 89 patients, “indeterminate” in 40 patients, “suspicious for DTD” in 42 patients, and “DTD” in 58 patients. The presence of two or more CT features of DTD, which was classified as “suspicious for DTD” by all radiologists, had the largest area under the receiver-operating characteristic curve (Az = 0.820; 95% confidence interval: 0.764, 0.868), with sensitivity of 85.9% and specificity of 78.2%. However, no statistical significance between readers’ experience and their diagnostic accuracy was found. In conclusion, evaluations of CT images are helpful for differentiating DTD from NTP.
... In comparison, 9 months before presentation, when he was feeling well, the HU of strap muscle was 49 and 56 without and with contrast, while that of thyroid was 105 and 140-160, respectively. The low thyroid HU without contrast after he developed cobalt toxicity symptoms implies that the thyroid had low iodine content, while the high thyroid HU with contrast indicates that the thyroid had high blood flow, both are features of destruction thyroiditis [11]. Thus biochemical and imaging findings both demonstrate that he had destruction thyroiditis and impaired thyroid hormone synthesis. ...
... For diffused thyroid disease in ITD, many cases may be diagnosed as simple goiter, Hashimoto thyroiditis, autoimmune thyroid disease, or Graves' disease. A recent series by Rho and Kim [6] showed that thyroid ultrasound and neck CT have similar diagnostic values for differentiating incidental diffuse thyroid disease presenting as ITD from normal thyroid. This will be more complicated when nodular thyroid disease is diagnosed by thyroid ultrasound. ...
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Background Nodular thyroid disease is by far the most common thyroid disease and is closely associated with the development of thyroid cancer. Coal miners with chronic coal dust exposure are at higher risk of developing nodular thyroid disease. There are few studies that use machine learning models to predict the occurrence of nodular thyroid disease in coal miners. The aim of this study was to predict the high risk of nodular thyroid disease in coal miners based on five different Machine learning (ML) models. Methods This is a retrospective clinical study in which 1,708 coal miners who were examined at the Huaihe Energy Occupational Disease Control Hospital in Anhui Province in April 2021 were selected and their clinical physical examination data, including general information, laboratory tests and imaging findings, were collected. A synthetic minority oversampling technique (SMOTE) was used for sample balancing, and the data set was randomly split into a training and Test dataset in a ratio of 8:2. Lasso regression and correlation heat map were used to screen the predictors of the models, and five ML models, including Extreme Gradient Augmentation (XGBoost), Logistic Classification (LR), Gaussian Parsimonious Bayesian Classification (GNB), Neural Network Classification (MLP), and Complementary Parsimonious Bayesian Classification (CNB) for their predictive efficacy, and the model with the highest AUC was selected as the optimal model for predicting the occurrence of nodular thyroid disease in coal miners. Result Lasso regression analysis showed Age, H-DLC, HCT, MCH, PLT, and GGT as predictor variables for the ML models; in addition, heat maps showed no significant correlation between the six variables. In the prediction of nodular thyroid disease, the AUC results of the five ML models, XGBoost (0.892), LR (0.577), GNB (0.603), MLP (0.601), and CNB (0.543), with the XGBoost model having the largest AUC, the model can be applied in clinical practice. Conclusion In this research, all five ML models were found to predict the risk of nodular thyroid disease in coal miners, with the XGBoost model having the best overall predictive performance. The model can assist clinicians in quickly and accurately predicting the occurrence of nodular thyroid disease in coal miners, and in adopting individualized clinical prevention and treatment strategies.
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PurposeTo compare the diagnostic performance of ultrasonography (US) and computed tomography (CT) for diagnosing incidentally detected diffuse thyroid disease (DTD) in patients who underwent thyroid surgery using multicenter data. Methods Between July and December 2016, a total of 177 patients who underwent preoperative thyroid US and neck CT, and subsequent thyroid surgery at 4 participating institutions, were reviewed. US and CT images in each case were retrospectively reviewed by a radiologist at each institution, and classified into one of the following four categories based on US and CT features: no DTD; indeterminate; suspicious for DTD; and DTD. The diagnostic accuracy of US and CT were calculated at each institution by comparison with histopathological results. ResultsRespective US and CT classifications in the 177 patients were no DTD in 75 and 71, indeterminate in 46 and 34, suspicious for DTD in 28 and 31, and DTD in 28 and 41. Among the histopathological results, 113 patients had normal thyroid parenchyma, 23 had Hashimoto thyroiditis, 36 had non-Hashimoto lymphocytic thyroiditis, and 5 had diffuse hyperplasia. The presence of ≥ 2 US and CT features of DTD, which was classified as suspicious for DTD or DTD, had the largest area under the receiver operating characteristic curve (0.866 and 0.893, respectively), with sensitivity and specificity of 71.9 and 91.2% in US, and 84.4 and 84.1% in CT, respectively. However, there was no statistically significant difference between readers’ experience and their diagnostic performance. ConclusionUS and CT imaging may be helpful for detecting incidental DTD.
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