Computed tomography features of incidentally detected diffuse thyroid disease

Relationship between Thyroid CT Density, Volume, and Future TSH Elevation: A 5-Year Follow-Up Study

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.

Influence of sex, age and thyroid function indices on dual-energy computed tomography-derived quantitative parameters of thyroid in patients with or without Hashimoto's thyroiditis

PURPOSE

To study the influence of sex, age and thyroid function indices on dual-energy computed tomography (DECT)-derived quantitative parameters of thyroid in patients with or without Hashimoto's thyroiditis (HT).

MATERIAL AND METHODS

A total of 198 consecutive patients who underwent DECT scan of neck due to unilateral thyroid lesions were retrospectively enrolled. Iodine concentration (IC), total iodine content (TIC) and volume of normal thyroid lobe were calculated. Influences of sex, age and thyroid function indices on DECT-derived parameters in overall study population, subgroup patients with, and those without HT were assessed using Mann-Whitney U test, Student's T-test, and Spearman correlation analyses, respectively, as appropriate.

RESULTS

HT group showed significantly lower IC and TIC, while higher volume than No-HT group (all p < 0.001). The volume was larger in male than that in female in overall study population and No-HT group (p = 0.047 and 0.010, respectively). There was no significant difference in any DECT-derived parameters between low (≤ 35 years) and high (> 35 years) age group in all three groups (all p > 0.05). TPOAb and TgAb correlated positively with IC and TIC, and negatively with volume in overall study population (all p < 0.05). TPOAb and TgAb also correlated positively with IC in HT group (p = 0.002 and 0.007, respectively).

CONCLUSION

DECT-derived parameters of thyroid differed significantly between patients with and without HT. Sex and thyroid function indices could affect the DECT-derived parameters. Aforementioned physiological factors should be considered when analyzing the DECT-derived parameters of thyroid.

Predicting the risk of nodular thyroid disease in coal miners based on different machine learning models

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.

Diagnostic accuracy of computed tomography for differentiating diffuse thyroid disease from normal thyroid parenchyma: A multicenter study

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.

Comparison of ultrasonography and computed tomography for diagnosing diffuse thyroid disease: a multicenter study

PURPOSE

To 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.

RESULTS

Respective 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.

CONCLUSION

US and CT imaging may be helpful for detecting incidental DTD.

Magnetic Resonance Imaging Features of Normal Thyroid Parenchyma and Incidental Diffuse Thyroid Disease: A Single-Center Study

Background: No previous studies have investigated the feasibility of magnetic resonance imaging (MRI) diagnosis for detecting incidental diffuse thyroid disease (DTD). This study investigated MRI features of normal thyroid parenchyma and incidental DTD. Methods: From January 2008 to December 2017, 387 patients underwent neck MRI in our hospital due to tumor/nodal staging (n = 137), lymphadenopathy (n = 122), inflammatory neck lesion (n = 85), congenital neck lesion (n = 12), and patient request (n = 31). Among them, 375 patients were excluded because of a lack of appropriate histopathological data on the thyroid parenchyma. Results: Among the patients included, 10 had normal thyroid parenchyma, 1 had Hashimoto thyroiditis, and 1 had diffuse hyperplasia. The common MRI features of normal thyroid parenchyma include iso-/slightly high and homogeneous signal intensity on T1/T2-weighted images, normal anteroposterior diameter of the thyroid gland, smooth margin, and homogeneously increased enhancement as compared to adjacent muscle. Hashimoto thyroiditis exhibited high and inhomogeneous signal intensity on T2-weighted images, while diffuse hyperplasia revealed an increased anteroposterior diameter and lobulated margin of the thyroid gland, and inhomogeneous enhancement. Conclusions: MRI may be helpful for detection of incidental DTD.