scholarly journals 2D Shear Wave Elastography in risk prediction of indeterminate thyroid nodules compared to histological findings

2019 ◽  
Vol 45 ◽  
pp. S4-S5
Author(s):  
Pedro P. Moraes ◽  
Marcelo M. Straus ◽  
Marcelo M. Schelini ◽  
Rosa R. Sigrist ◽  
Maria Cristina M.C. Chammas
2019 ◽  
Author(s):  
Mihaela Vlad ◽  
Ioana Golu ◽  
Maria Oprea ◽  
Daniela Amzar ◽  
Melania Balas ◽  
...  

2018 ◽  
Vol 68 (12) ◽  
pp. 2818-2822
Author(s):  
Maria Cristina Oprea ◽  
Mihaela Vlad ◽  
Ioana Golu ◽  
Ioan Sporea ◽  
Lazar Fulger

Thyroid nodules are a common pathology found in 50 to 60% of otherwise healthy people. Diagnostic imaging techniques are help discriminating between benign and malignant nodules, while fine needle aspiration is still a gold standard. Shear wave elastography, a recent imaging technique, holds the promise to become reliable diagnostic tools and is currently used in combination with ultrasound. We here report data obtained in a series of 52 thyroid nodules analysed by means of elastography, as well as conventional and Doppler ultrasound. We found no differences in age, nodule and thyroid volume, length, width, thickness and maximum diameter between benign and malignant lesions. Several sonographic patterns are considered to be predictive of malignancy, out of which we only found the intranodular blood flow to be statistically significant. By the means of shear wave elastography we have first assessed tissue elasticities, which are shown in a range of colours, depending on tissue elasticity/stiffness. Then, we have measured and recorded four parameters automatically displayed by the system, namely SWE-mean, SWE-max, SWE-SD and SWE-ratio. Data analysis showed all these quantitative parameters had good sensitivity, specificity, positive predictive value, negative predictive value and area under the curve, as calculated by the ROC curve. As with these parameters, the cut-off points were lower than in literature, still able to indicate reliable diagnoses, which were confirmed by histopathological exam. Our conclusion is that shear wave elastography has great potential for reliably and accurately diagnosing thyroid malignancies.


2015 ◽  
Vol 84 (3) ◽  
pp. 407-412 ◽  
Author(s):  
Ah Young Park ◽  
Eun Ju Son ◽  
Kyunghwa Han ◽  
Ji Hyun Youk ◽  
Jeong-Ah Kim ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mohammed Hazem ◽  
Ossama M. Zakaria ◽  
Mohamed Yasser Ibrahim Daoud ◽  
Ibrahim Khalid Al Jabr ◽  
Abdulwahab A. AlYahya ◽  
...  

Abstract Background Thyroid nodules are an important health problem in children and adolescents. They possess a higher risk of malignancy in comparison to adults. This fact forms a great dilemma for clinicians. The aim of this study was to evaluate the reliability of shear wave elastography (SWE) as a non-invasive technique in the characterization of thyroid nodules in children and adolescents. Methods This prospective study included 56 patients with thyroid nodules. All the patients underwent clinical assessment, laboratory investigations, ultrasound, and Doppler examination, followed by an SWE assessment. Statistical analysis was performed and the best cut-off value to differentiate benign from malignant nodules was determined using the ROC curve and AUC. Results Seventy-two nodules were detected in the examined patients (ages ranged from 11 to 19 years, with mean age of 14.89 ± 2.3 years). Fifty-eight nodules (80.6%) were benign, and fourteen nodules (19.4%) were malignant (histopathologically proved). Highly suspicious criteria for prediction of malignancy by ultrasound and Doppler were hypoechoic echopattern, internal or internal and peripheral vascularity, microcalcifications, taller-than-wide dimensions, irregular outlines, and absence of halo (p < 0.05). The diagnostic performance for their summation was 70.69% sensitivity, 82.8% specificity, 80.45% accuracy, a 63.79% positive predictive value (PPV), and 87.9% negative predictive values (NPV). Regarding SWE, our results showed that 42.2 kPa was the best cut-off value, with AUC = 0.921 to differentiate malignant from benign nodules; the diagnostic performance was 85.71% sensitivity, 94.83% specificity, 93.06% accuracy, 76.9% PPV, and 93.2% NPV. Conclusion Shear wave elastography is a non-invasive technique that can assist in the diagnosis of malignant thyroid nodules among children and adolescents.


2019 ◽  
Vol 40 (04) ◽  
pp. 495-503 ◽  
Author(s):  
Vito Cantisani ◽  
Emanuele David ◽  
Hektor Grazhdani ◽  
Antonello Rubini ◽  
Maija Radzina ◽  
...  

Abstract Purpose To evaluate the diagnostic performance of strain ratio elastography (SRE) and shear wave elastography (SWE) alone and in combination with Thyroid Imaging Reporting and Data System (TIRADS) classification parameters to improve differentiation between benign and malignant thyroid nodules. Materials and Methods In this prospective study benign (n = 191) and malignant (n = 52) thyroid nodules were examined with high-resolution ultrasound (US) features using the TIRADS lexicon and SRE semiquantitative and SWE quantitative findings using histology or cytology as the gold standard with a 12-month follow-up. Sensitivity (Se), specificity (Sp) and the area under the ROC curve (AUROC) were used to evaluate the diagnostic performance of each feature and combinations of the methods. Results TIRADS score showed a sensitivity of 59.6 %, a specificity of 83.8 % with an AUROC of 0.717, a PPV of 50.0 % and an NPV of 88.4 %. SRE yielded the highest performance with a sensitivity of 82.7 %, a specificity of 92.7 % with AUROC of 0.877, a PPV 75.4 % and an NPV of 95.2 %. SWE (kPa) had a sensitivity and specificity of 67.3 % and 82.7 %, respectively, with an AUROC of 0.750, a PPV of 51.5 % and an NPV of 90.3 %. Differences were significant for SRE only but not for SWE. Conclusion Ultrasound elastography may improve thyroid nodule discrimination. In particular, SRE has a better performance than TIRADS classification, while their combination improves sensitivity.


2017 ◽  
Vol 37 (3) ◽  
pp. 601-609 ◽  
Author(s):  
Fen Wang ◽  
Cai Chang ◽  
Min Chen ◽  
Yi Gao ◽  
Ya-Ling Chen ◽  
...  

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