Search

Purpose This study aims to establish normative reference values for thoracic aortic diameter (AD) in participants in the National Lung Screening Trial. Methods Thoracic AD on 322 prevalence computed tomography was recorded at the sinotubular junction, mid-ascending, transverse arch, mid-descending, and diaphragmatic hiatus. Results Mean AD (cm) and upper limits of normal for men and women were recorded for at each location. Smoking did not correlate with AD. Age, gender, and body surface area (BSA) were the most significant factors. Conclusions Thoracic AD reference values are reported. They do not correlate with smoking, but they did for age, gender, and BSA. [ABSTRACT FROM AUTHOR]

• Multi-classifying thyroid disease leads to enhanced diagnostic decision-making. • Ultrasound image modalities outperform CT scans regarding CAD detection. • Xception generalizes well to different medical image modalities. • Adoptions of CAD in the clinic need to earn confidence among doctors and patients. [Display omitted] Background and Objective: As one of the largest endocrine organs in the human body, the thyroid gland regulates daily metabolism. Early detection of thyroid disease leads to reduced mortality rates. The diagnosis of thyroid disease is usually made by radiologists and pathologists, which heavily relies on their experience and expertise. To mitigate human false-positive diagnostic rates, this paper proves that deep learning-driven techniques yield promising performance for automatic detection of thyroid diseases which offers clinicians assistance regarding diagnostic decision-making. Method: This research study is the first of its kind, which adopts two pre-operative medical image modalities for multi-classifying thyroid disease types (i.e., normal, thyroiditis, cystic, multi-nodular goiter, adenoma, and cancer). Using the current state-of-the-art performing deep convolutional neural network (CNN) architecture, this study builds a thyroid disease diagnostic model for distinguishing among the disease types. Results: The model obtains unprecedented performance for both medical image sets, and it reaches an accuracy of 0.972 and 0.942 for ultrasound images and computed tomography (CT) scans correspondingly. Conclusion: The experimental results illustrate that the selected CNN can be adapted to both image modalities, indicating the feasibility of the deep learning model and emphasizing its further applications in clinics. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this study was to compare the diagnostic values of thyroid ultrasound (US) and neck computed tomography (CT) in incidentally detecting diffuse thyroid disease (DTD). A single radiologist made US and CT diagnoses of incidentally detected DTD in 130 consecutive patients before thyroidectomy for various malignancies. Histopathologic examinations confirmed normal thyroid (n = 80), Hashimoto thyroiditis (n = 20), non-Hashimoto lymphocytic thyroiditis (n = 28) and diffuse hyperplasia (n = 2). Receiver operating characteristic curves revealed that the best diagnostic indices of both imaging methods were achieved on the basis of two or more abnormal imaging findings. The sensitivity, specificity and accuracy of US and CT in incidentally detecting DTD by this classification were 72% and 72%, 87.5% and 91.3% and 81.5% and 83.8%, respectively. Thyroid US and neck CT have similar diagnostic values for differentiating incidental DTD from normal thyroid. [Copyright &y& Elsevier]

Abstract: Objective: The purpose of this study was to evaluate the preoperative computed tomography (CT) features of thyroglossal duct cysts (TDCs), with the main purpose of evaluating criteria helpful in differentiating TDCs from other lesions in children under 10-years-of-age. Methods: A retrospective chart review was performed at Chonnam National University Hospital for the period of March 2005 to June 2011. Pediatric patients under 10-years-of-age with suspected TDCs were divided into two groups depending on their histopathologic diagnosis. Results: Of the 29 pediatric patients with suspected TDCs, 16 patients (55%) had histopathologically confirmed TDCs. Thirteen patients (45%) had dermoid cysts (n =6), ranula (n =3), and inflammatory lesions (n =4). There were no statistically significant differences between the preoperative CT findings and the final histopathologic diagnosis of TDC. There were no major complications resulting from surgical interventions. Conclusion: CT is not helpful in differentiating TDC from other lesions in children under 10-years-of-age. Therefore, we suggest that preoperative CT of suspected TDCs in children should be performed more selectively. [Copyright &y& Elsevier]