contrast enhanced ultrasound
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2022 ◽  
Vol 17 (3) ◽  
pp. 467-472
Author(s):  
Divina D'Auria ◽  
Dolores Ferrara ◽  
Gioconda Argenziano ◽  
Domenico Noviello ◽  
Anna Marcella Giugliano ◽  
...  

2022 ◽  
Vol 11 ◽  
Author(s):  
Lei Chen ◽  
Luzeng Chen ◽  
Zhenwei Liang ◽  
Yuhong Shao ◽  
Xiuming Sun ◽  
...  

ObjectiveTo evaluate the diagnostic performance of preoperative contrast-enhanced ultrasound (CEUS) in the detection of extracapsular extension (ECE) and cervical lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) and the added value of CEUS in the evaluation of PTC invasiveness to conventional ultrasound (US).Materials and MethodsA total of 62 patients were enrolled retrospectively, including 30 patients with invasive PTCs (Group A, ECE or LNM present) and 32 patients with non-invasive PTCs (Group B). All patients underwent US and CEUS examinations before surgery. US and CEUS features of PTCs and lymph nodes were compared between groups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of US, CEUS, and the combination of the two in the detection of ECE and LNM of PTCs were calculated. Logistic regression was used to analyze relationships between variables.ResultsThe PTC size was larger in group A on both US and CEUS (P = 0.001, P = 0.003). More PTCs showed hyper-enhancement in group A (P = 0.013) than in group B. More PTCs had >25% contact between PTC and the thyroid capsule and discontinued capsule on US and CEUS (all P < 0.05) in group A than in group B. More absent hilum and calcification of lymph nodes were observed in group A (both P < 0.05) than in group B on US. More centripetal perfusion and enlarged lymph nodes were observed in group A (both P < 0.05) than in group B on CEUS. CEUS alone and US combined with CEUS manifested higher diagnostic accuracy (79.0%) than US alone (72.6%) in the detection of ECE. The combination of US and CEUS manifested the highest diagnostic accuracy (95.2%) than CEUS alone (90.3%) and US alone (82.2%) in the detection of LNM. Diagnoses of ECE and LNM by the combination of US and CEUS were independent risk factors for PTC invasiveness [odds ratio (OR) = 29.49 and 97.20, respectively; both P = 0.001].ConclusionCEUS or US combined with CEUS is recommended for the detection of PTC ECE, while the combination of US and CEUS is most recommended for LNM detection. CEUS plays an essential role in the preoperative evaluation of PTC invasiveness.


2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Ying Wei ◽  
Yun Niu ◽  
Zhen-long Zhao ◽  
Xiao-jing Cao ◽  
Li-li Peng ◽  
...  

AbstractCervical lymph node metastasis (CLNM) is common in patients with papillary thyroid carcinoma (PTC), which is responsible for tumor staging and surgical strategy. The accurate preoperative identification of CLNM is essential. In this study, twenty consecutive patients with PTC received a parenchyma injection of Sonazoid followed by contrast enhanced ultrasound (CEUS) to identify CLNM. The specific lymphatic CEUS (LCEUS) signs for diagnosing CLNM were summarized, which were further compared with the resected specimens to get the pathological basis. After the injection of contrast agent, lymphatic vessel and lymph node (LN) could be exclusively displayed as hyperperfusion on LCEUS. The dynamic perfusion process of contrast agent in CLNM over time can be clearly visualized. Perfusion defect and interruption of bright ring were the two characteristic LCEUS signs in diagnosing CLNM. After comparing with pathology, perfusion defect was correlated to the metastatic foci in medulla and interruption of bright ring was correlated to the tumor seeding in marginal sinus (all p values < 0.001). The diagnostic efficacies of these two signs were high (perfusion defect vs. interruption of bright ring: AUC, 0.899, 95% CI 0.752–1.000 vs. 0.904, 0.803–1.000). LCEUS has advantages in identifying CLNM from PTC. The typical LCEUS signs of CLNM correlated with pathology.


2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Heng Zhou ◽  
Bin Liu ◽  
Yang Liu ◽  
Qunan Huang ◽  
Wei Yan

Thyroid diseases are divided into papillary carcinoma and nodular diseases, which are very harmful to the human body. Ultrasound is a common diagnostic method for thyroid diseases. In the process of diagnosis, doctors need to observe the characteristics of ultrasound images, combined with professional knowledge and clinical experience, to give the disease situation of patients. However, different doctors have different clinical experience and professional backgrounds, and the diagnosis results lack objectivity and consistency, so an intelligent diagnosis technology for thyroid diseases based on the ultrasound image is needed in clinic, which can give objective and reliable diagnosis opinions on thyroid diseases by extracting the texture, shape, and other information of the image and assist doctors in clinical diagnosis. This paper mainly studies the intelligent ultrasonic diagnosis of papillary thyroid cancer based on machine learning, compares the ultrasonic characteristics of PTMC diagnosed by using the new ultrasound technology (CEUS and UE), and summarizes the differential diagnosis effect and clinical application value of the two technology methods for PTMC. In this paper, machine learning, diffuse thyroid image features, and RBM learning methods are used to study the ultrasonic intelligent diagnosis of papillary thyroid cancer based on machine learning. At the same time, the new contrast-enhanced ultrasound (CEUS) technology and ultrasound elastography (UE) technology are used to obtain the experimental phenomena in the experiment of ultrasonic intelligent diagnosis of papillary thyroid cancer. The results showed that 90% of the cases were diagnosed by contrast-enhanced ultrasound and confirmed by postoperative pathology. CEUS and UE have reliable practical value in the diagnosis of PTMC, and the combined application of CEUS and UE can improve the sensitivity and accuracy of PTMC diagnosis.


Author(s):  
Yi Dong ◽  
Dan Zuo ◽  
Yi-Jie Qiu ◽  
Jia-Ying Cao ◽  
Han-Zhang Wang ◽  
...  

OBJECTIVES: To establish and evaluate a machine learning radiomics model based on grayscale and Sonazoid contrast enhanced ultrasound images for the preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS: 100 cases of histopathological confirmed HCC lesions were prospectively included. Regions of interest were segmented on both grayscale and Kupffer phase of Sonazoid contrast enhanced (CEUS) images. Radiomic features were extracted from tumor region and region containing 5 mm of peritumoral liver tissues. Maximum relevance minimum redundancy (MRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) were used for feature selection and Support Vector Machine (SVM) classifier was trained for radiomic signature calculation. Radiomic signatures were incorporated with clinical variables using univariate-multivariate logistic regression for the final prediction of MVI. Receiver operating characteristic curves, calibration curves and decision curve analysis were used to evaluate model’s predictive performance of MVI. RESULTS: Age were the only clinical variable significantly associated with MVI. Radiomic signature derived from Kupffer phase images of peritumoral liver tissues (kupfferPT) displayed a significantly better performance with an area under the receiver operating characteristic curve (AUROC) of 0.800 (95% confidence interval: 0.667, 0.834), the final prediction model using Age and kupfferPT achieved an AUROC of 0.804 (95% CI: 0.723, 0.878), accuracy of 75.0%, sensitivity of 87.5% and specificity of 69.1%. CONCLUSIONS: Radiomic model based on Kupffer phase ultrasound images of tissue adjacent to HCC lesions showed an observable better predictive value compared to grayscale images and has potential value to facilitate preoperative identification of HCC patients at higher risk of MVI.


2022 ◽  
Vol 2022 ◽  
pp. 1-6
Author(s):  
Hong Cheng ◽  
Shuang-Shuang Zhuo ◽  
Xin Rong ◽  
Ting-Yue Qi ◽  
Hong-Guang Sun ◽  
...  

Objectives. To explore the value of applying contrast-enhanced ultrasound (CEUS) in adjusting the classification of category 4 nodules in the Chinese-Thyroid Imaging Report and Data System (C-TIRADS). Methods. The data of preoperative conventional ultrasound and CEUS examinations of 125 C-TIRADS 4 nodules in 109 patients were retrospectively analyzed. We divided the thyroid nodules into two groups based on whether recommend by the guide fine-needle aspiration (FNA). Group I included C-TIRADS 4A nodules with a maximum diameter ≤15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter ≤10 mm, and Group II included C-TIRADS 4A nodules with a maximum diameter >15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter >10 mm. In CEUS, thyroid nodules showing suspicious malignant features such as hypoenhancement or early washout were adjusted to a level higher in the C-TIRADS classification; thyroid nodules showing possible benign features such as iso- or hyperenhancement were adjusted to a level lower; and thyroid nodules showing no enhancement were adjusted to C-TIRADS 3. Taking the pathological results as the gold standard, the receiver operating characteristic (ROC) curves of the C-TIRADS classification before and after the adjustment based on CEUS were plotted, and the diagnostic efficiency was compared. Results. The sensitivity, specificity, accuracy, and positive and negative predictive values of the C-TIRADS classification for the diagnosis of thyroid nodule malignancy before the adjustment based on the CEUS results were 83.6%, 63.8%, 74.4%, 72.7%, and 77.1%, respectively, and these values were 91.0%, 82.8%, 87.2%, 85.9%, and 88.9%, respectively, after the adjustment. The area under the ROC curve (AUC) was 0.737 and 0.869, respectively, showing a significant difference (Z = 3.288, P = 0.001 ). The diagnostic efficiency of C-TIRADS classification after the adjustment based on the CEUS results in both groups was improved compared with the result before the adjustment, and the difference in Group II was significant (Z = 2.931, P = 0.003 ). Conclusions. CEUS significantly improved the diagnostic performance in the adjustment of C-TIRADS 4 nodule classification, especially for the nodules which needs FNA recommended by the C-TIRADS.


Author(s):  
E.M. Jung ◽  
F. Jung ◽  
C. Stroszczynski ◽  
I. Wiesinger

AIM: To evaluate the additive clinical value of endoluminal contrast enhanced ultrasound (CEUS) after interventional placement of drainages in abdominal fluid collections. MATERIAL/METHOD: Examination of 30 patients using a 1–6 MHz convex probe (Resona 7, Mindray) to locate the fluid collection in B-Mode. Additionally, dynamic endoluminal CEUS with 1 ml sulphur-hexafluoride microbubbles was performed to measure the extent of the percutaneously drained abscesses. Independent assessment of dynamically stored images in PACS in DICOM format. Correlation to reference imaging using computed tomography (CT). RESULTS: A total of 30 patients were examined (17 m, 19–78 years, mean 56.1 years). Drainages were positioned in the liver in 15 cases, in the pelvis after kidney transplantation in 4 cases, close to the spleen in 1 case and in the abdomen in 10 cases. In all cases abscesses showed marginal hyperaemia with reactive septations in CEUS. The drainage position was assessed by means of B-mode in all cases first and then by CEUS. In 4 cases CEUS showed a fistula to the pleura, in 5 cases to the peritoneum, in 2 cases to the intestine, in 5 cases to the biliary tract, corresponding to the CT. In 2 cases there was a hint of an anastomotic leakage after intestinal anastomosis, which was reliably detected by CT. The drainage was removed in 11 cases within a period of 2 to 5 days after CEUS control, in 9 cases within a period of 5 to 10 days. Another operation was necessary in 3 cases. A new drainage was placed in 2 cases. The required amount of contrast medium is 1 ml endoluminally diluted to 9 ml sodium chloride. CONCLUSION: CEUS facilitates the exact localization and characterization of inflammatory abdominal fluid collections. Furthermore, possible fistulas can be detected that cannot be seen with conventional ultrasound.


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