The present, updated document describes the fourth iteration of recommendations for the hepatic use of contrast-enhanced ultrasound, first initiated in 2004 by the European Federation of Societies for Ultrasound in Medicine and Biology. The previous updated editions of the guidelines reflected changes in the available contrast agents and updated the guidelines not only for hepatic but also for non-hepatic applications. The 2012 guideline requires updating as, previously, the differences in the contrast agents were not precisely described and the differences in contrast phases as well as handling were not clearly indicated. In addition, more evidence has been published for all contrast agents. The update also reflects the most recent developments in contrast agents, including U.S. Food and Drug Administration approval and the extensive Asian experience, to produce a truly international perspective. These guidelines and recommendations provide general advice on the use of ultrasound contrast agents (UCAs) and are intended to create standard protocols for the use and administration of UCAs in liver applications on an international basis to improve the management of patients.

Guidelines and Good Clinical Practice Recommendations for Contrast-Enhanced Ultrasound (CEUS) in the Liver-Update 2020 WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS.

Clinical relevance of tumour-associated macrophages

Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses.

The present, updated document describes the fourth iteration of recommendations for the hepatic use of contrast enhanced ultrasound (CEUS), first initiated in 2004 by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB). The previous updated editions of the guidelines reflected changes in the available contrast agents and updated the guidelines not only for hepatic but also for non-hepatic applications. The 2012 guideline requires updating as previously the differences of the contrast agents were not precisely described and the differences in contrast phases as well as handling were not clearly indicated. In addition, more evidence has been published for all contrast agents. The update also reflects the most recent developments in contrast agents, including the United States Food and Drug Administration (FDA) approval as well as the extensive Asian experience, to produce a truly international perspective. These guidelines and recommendations provide general advice on the use of ultrasound contrast agents (UCA) and are intended to create standard protocols for the use and administration of UCA in liver applications on an international basis to improve the management of patients.

/pdf/guidelines-and-good-clinical-practice-recommendations-for-4d88ojd04v.pdf

Guidelines and Good Clinical Practice Recommendations for Contrast Enhanced Ultrasound (CEUS) in the Liver - Update 2020 - WFUMB in Cooperation with EFSUMB, AFSUMB, AIUM, and FLAUS

B cells and tertiary lymphoid structures as determinants of tumour immune contexture and clinical outcome

Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer.

Purpose Computer-aided diagnosis (CAD) systems assist in solving subjective diagnosis problems that typically rely on personal experience. A CAD system has been developed to differentiate malignant thyroid nodules from benign thyroid nodules in ultrasound images based on deep learning methods. The diagnostic performance was compared between the CAD system and the experienced attending radiologists. Methods The ultrasound image dataset for training the CAD system included 651 malignant nodules and 386 benign nodules while the database for testing included 422 malignant nodules and 128 benign nodules. All the nodules were confirmed by pathology results. In the proposed CAD system, a support vector machine (SVM) is used for classification and fused features which combined the deep features extracted by a convolutional neural network (CNN) with the hand-crafted features such as the histogram of oriented gradient (HOG), local binary patterns (LBP), and scale invariant feature transform (SIFT) were obtained. The optimal feature subset was formed by selecting these fused features based on the maximum class separation distance and used as the training sample for the SVM. Results The accuracy, sensitivity, and specificity of the CAD system were 92.5%, 96.4%, and 83.1%, respectively, which were higher than those of the experienced attending radiologists. The areas under the ROC curves of the CAD system and the attending radiologists were 0.881 and 0.819, respectively. Conclusions The CAD system for thyroid nodules exhibited a better diagnostic performance than experienced attending radiologists. The CAD system could be a reliable supplementary tool to diagnose thyroid nodules using ultrasonography. Macroscopic features in ultrasound images, such as the margins and shape of thyroid nodules, could influence the diagnostic efficiency of the CAD system.

Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images

To evaluate the utility of real-time contrast-enhanced ultrasound (CEUS)-guided coaxial needle biopsies for focal liver lesions (FLL) that were inconspicuous or could not be accurately identified the active site on B-mode ultrasound (US). This prospective study included 76 patients who had CEUS-guided coaxial needle biopsies for FLL between December 2015 and June 2017. We recorded characteristics of target lesions. We evaluated conspicuity of target lesions and accuracy of identifying the active site of target lesions on B-mode US and CEUS using a 5-point scale. Patients were divided into three groups, and analyzed according to body mass index (BMI). Based on the final diagnosis, the diagnostic performance was evaluated. The mean size and depth of target lesions were 41.5 ± 28.5 and 47.9 ± 18.9 mm on CEUS, respectively. In arterial phase, the enhanced pattern of target lesions varied. The conspicuity of target lesions and accuracy of identifying the active site of target lesions was significantly improved on CEUS compared to B-mode US (p < 0.05). The three BMI groups had significant differences in conspicuity of target lesions after using CEUS (p < 0.05). The high BMI group had a greater change in conspicuity of lesions compared to the normal BMI group or the low BMI group (p < 0.05). The sensitivity, specificity, and accuracy of this technique for the diagnosis of FLL were 92.8%, 100%, and 93.4%, respectively. Real-time CEUS-guided coaxial needle biopsy can be very useful for FLL that are inconspicuous or cannot be accurately identified the active site on B-mode US.

Usefulness of real-time contrast-enhanced ultrasound guided coaxial needle biopsy for focal liver lesions

OBJECTIVES To assess the value of ultrasonography (US) features for determining the malignant potential of complex cystic lesions. METHODS Seventy-nine complex cystic lesions were reviewed retrospectively. They were classified into four types according to US features in type I, the masses have a thick outer wall, thick internal septa, or both; in type II, the masses are an intracystic type with one or more discrete solid mural lesions within a cyst; in type III, the masses contain mixed cystic and solid components and are at least 50% cystic portion in a mass; in type IV, there are predominantly (at least 50%) solid masses with eccentric or central cystic foci. Positive predictive values were calculated for all types. RESULTS The frequency of malignancy was higher among type III and IV lesions than among the other two types. Lesions with a diameter greater than or equal to 20 mm, margins not circumscribed, resistance index greater than or equal to 0.7, and axillary abnormal nodes had a high probability of malignancy. CONCLUSIONS US is an important adjunct to evaluate the malignant potential of complex cystic lesions.

https://onlinelibrary.wiley.com/doi/pdf/10.7863/ultra.16.05012

Value of Ultrasonographic Features for Assessing Malignant Potential of Complex Cystic Breast Lesions.

Objective: To analyze the feature of breast complex cystic masses and to classify it at ultrasonography (US), which applied to the Breast Imaging Reporting and Data System (BI-RADS) categories 4a to 4c with pathological results as the golden standards. Methods: The ultrasonographic data and clinical features of 78 patients with complex cystic masses confirmed by pathology in Cancer Hospital from July 2014 to June 2017 were retrospectively reviewed. The complex cystic breast masses were divided into four classes on the basis of their US features: type 1 [thick wall and (or) thick septa (> 0.5 mm)], type 2 (one or more intra-cystic masses), type 3 (mixed cystic and solid components with cystic components more than 50%) and type 4 (mixed cystic and solid components with solid components more than 50%). Positive values (PPVs) were calculated for each type. Multiple linear regression analysis was used to analyze the ultrasonographic features of the masses (lesion size, margins, blood flow resistance index, calcification, and axillary lymph nodes, etc.) with malignant correlation. Results: There were 81 lesions in 78 patients. Among the 81 masses based on US appearance, 14 (17.3%) were classified as type Ⅰ, 18 (22.2%) as type Ⅱ, 18 (22.2%) as type Ⅲ, and 31 (38.3%) as type Ⅳ. The positive predictive values of the malignant lesions of type Ⅰ, type Ⅱ, Ⅲ and Ⅳ were 7.1%, 16.7%, 61.1% and 48.3%, respectively (P=0.040). In all the 81 masses, 14 were BI-RADS categories 4a, 18 were BI-RADS categories 4b and 49 were BI-RADS categories 4c. Masses with maximum diameter equal to or larger than 2.0 cm, unclear margins, RI≥0.7 and presence of abnormal axillary nodes assessment had a high probability of malignancy (P=0.030, 0.038, <0.001 and 0.025, respectively). Conclusion: Ultrasound typing is helpful for differentiating benign and malignant breast complex cysts and classifying BI-AIDS 4a to 4c, thus providing clearer treatment for clinical practice.

Qing Chang

Papers

Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer.

Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images

Usefulness of real-time contrast-enhanced ultrasound guided coaxial needle biopsy for focal liver lesions

Value of Ultrasonographic Features for Assessing Malignant Potential of Complex Cystic Breast Lesions.

[The value of ultrasound classification in BI-RADS category 4 of breast complex cystic masses].