CT-detected solitary thyroid calcification: an important imaging feature for papillary carcinoma

Qiao

International Journal of Endocrinology

2020

The present work has investigated the value of computed tomography (CT) features in the diagnosis of papillary thyroid tumors in the incidental thyroid nodules (ITNs). In the 82 enrolled patients, 101 thyroid nodules were incidentally found by the neck CT scanning, among which 49 were histologically confirmed to be papillary thyroid carcinoma (PTC) while the other 52 were nodular goiter (NG). The tumor location, size, shape, tiny calcification, cystic change, and signs of an irregular ring, marginal defects, and enhanced blurring were all depicted by CT features. Both univariate and multivariate analyses were employed to identify independent predictors of PTC. The univariate analysis of PTC and NG showed that four CT features were statistically significant, including tiny calcification and signs of an irregular ring, marginal defects, and enhanced blurring. Furthermore, the multivariate logistic regression model indicated that signs of an irregular ring, marginal defects, and enhanced blurring were strongly correlated with PTC, of which the odds ratio (OR) was 27.374 (95% CI: 5.871∼127.636), 28.587 (95% CI: 4.139∼197.460), and 4.315 (95% CI: 0.858∼21.694), respectively. In the predictive model of PTC, the value of sensitivity, specificity, accuracy, and Youden index was 87.8%, 94.2%, 91.1%, and 0.82 with a likelihood ratio of 15.1. Therefore, the signs of an irregular ring, marginal defects, and enhanced blurring may be helpful in the diagnosis of PTC in incidentally found thyroid nodules.

Section: Introductionmentioning

confidence: 99%

Value of CT Features in the Diagnosis of Papillary Thyroid Tumors in Incidental Thyroid Nodules

Qiao

International Journal of Endocrinology

2020

Computational Intelligence and Neuroscience

“…Ultrasound technology is the most widely employed imaging method for the diagnosis and follow-up of thyroid disorders such as nodules, tumors, and cysts [3, 4]. However, with the further improvement of CT examination and the proposal of multirow spiral CT, contrast-enhanced CT scanning is gradually gaining importance in the diagnosis of thyroid nodules [5–7].…”

Section: Introductionmentioning

confidence: 99%

Cascade and Fusion of Multitask Convolutional Neural Networks for Detection of Thyroid Nodules in Contrast-Enhanced CT

Zhen

et al. 2019

With the development of computed tomography (CT), the contrast-enhanced CT scan is widely used in the diagnosis of thyroid nodules. However, due to the artifacts and high complexity of thyroid CT images, traditional machine learning has difficulty in detecting thyroid nodules in contrast-enhanced CT. A fully automated detection algorithm for thyroid nodules using contrast-enhanced CT images is developed. A modified U-Net architecture of fully convolutional networks is employed to segment the thyroid region of interest (ROI), and a fusion of convolutional neural networks (CNN-Fs) is proposed to detect benign and malignant thyroid nodules from the ROI images and original contrast-enhanced CT images. Experimental results demonstrate that the proposed cascade and fusion method of multitask convolutional neural networks (CNNs) is efficient in diagnosing thyroid diseases with contrast-enhanced CT images and has superior performance compared with other CNN methods.

“…At present, the use of CT for thyroid nodules with coarse calcifications have been rarely reported. Publications have mainly focused on unenhanced CT for analyzing the morphology and density of calcifications (19,20), while a limited number of studies have been published on the use of enhanced CT. Yang et al (21) analyzed 41 cases of solitary calcified nodules and 55 cases of coarse calcified nodules. They found that enlarged lesions observed using enhanced CT was an independent risk factor for cancer.…”

Section: Discussionmentioning

confidence: 99%

The Diagnostic Role of Computed Tomography for ACR TI-RADS 4–5 Thyroid Nodules With Coarse Calcifications

et al. 2020

Objectives: Coarse calcifications are prone to cause echo attenuation during ultrasonography (US) and hence affect the classification of benign and malignant nodules. This study aimed to investigate the diagnostic role of computed tomography (CT) for differentiating the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4-5 nodules with coarse calcifications. Methods: CT data of 216 ACR TI-RADS 4-5 nodules with coarse calcifications confirmed by surgery and pathology in 207 patients were analyzed retrospectively. Halo sign, artifacts, and CT values (i.e., Hounsfield unit) of the nodules were determined by two radiologists. Univariate analysis and binary logistic regression were used to determine the relationship of halo sign, artifact, and CT value with benign nodules. A predictive model for benign nodules with coarse calcifications was then constructed. The receiver operating characteristic (ROC) curve was used to analyze the predictive value of halo sign, artifact, CT value, and logistic regression model. Results: Of the 216 ACR TI-RADS 4-5 nodules with coarse calcifications, 170 were benign and 46 were malignant. There were 92 benign and 7 malignant nodules with halo sign (χ 2 = 22.067, P < 0.001), and 79 benign and 10 malignant nodules with artifacts (χ 2 = 9.140, P < 0.001). The CT values of benign and malignant nodules were 791 (543-1,025) Hu and 486 (406-670) Hu, respectively (Z = −5.394, P < 0.001). Binary logistic regression demonstrated that the halo sign, artifact, and CT value were independent predictors for benign nodules with coarse calcifications. The area under the ROC curve (AUC) of halo sign, artifact, CT value and regression model for predicting benign nodules with coarse calcifications were 0.776, 0.711, 0.784, and 0.850, respectively, and the optimal threshold of CT value was 627.5 Hu. Conclusion: Halo sign, artifact, and CT value > 627.5 Hu were helpful for identifying ACR TI-RADS 4-5 thyroid benign nodules with coarse calcifications. Wei et al. CT Diagnose Thyroid Calcified Nodules The diagnostic performance of the logistic regression model was higher than that of any single indicator. Accurate identification of these indicators could identify benign nodules and reduce unnecessary surgical trauma.