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Objectives: We aimed to evaluate the safety of the ultrasound contrast agent sulfur hexafluoride microbubbles in a large group of patients referred for routine contrast-enhanced ultrasound (CEUS). Methods: A retrospective assessment was made of all patients that received sulfur hexafluoride microbubbles intravenously for CEUS at 24 centers between January 2006 and April 2019. Patient demographic details, examination type, and the dose of sulfur hexafluoride microbubbles administered were recorded with specific adverse events (AEs) documentation tools at each center. All AEs were recorded as serious or non-serious. Non-serious AEs were classified by intensity as mild, moderate, or severe according to ACR criteria. The frequencies of AEs across patient subgroups were compared using the chi-square test. Results: A total of 463,434 examinations were evaluated. Overall, 157 AEs (153 [0.033%] non-serious; 4 [0.001%] serious) were reported after sulfur hexafluoride microbubbles administration, giving an AE frequency of 0.034% (157/463,434). Among the non-serious AEs, 66 (0.014%) were mild, 70 (0.015%) moderate, and 17 (0.004%) severe in intensity. The liver was the most common examination site, presenting an AE frequency of 0.026%. The highest AE frequency (0.092%) was for patients undergoing CEUS for vascular disease. There were no significant gender differences in either the total number or the severity of non-serious AEs (chi-square = 2.497, p = 0.287). The onset of AEs occurred within 30 min of sulfur hexafluoride microbubbles administration in 91% of cases. Conclusion: The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare, confirming that sulfur hexafluoride microbubbles are appropriate for routine CEUS applications. Key Point: • The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare. [ABSTRACT FROM AUTHOR]

Objective. Accurate T staging of rectal cancer based on ultrasound images is convenient for doctors to determine the appropriate treatment. To effectively solve the problems of low efficiency and accuracy of traditional methods for T staging diagnosis of rectal cancer, a deep-learning-based Xception-MS diagnostic model is proposed in this paper. Approach. The proposed diagnostic model consists of three steps. First, the model preprocesses rectal cancer images to solve the problem of data imbalance and deficiency of sample size, and reduces the risk of model overfitting. Second, a new Xception-MS network with stronger feature extraction capability, which is a combination of the Xception network and MS module, is proposed. The MS module is a new function module that can more effectively extract multi-scale information from rectal cancer images. In addition, to solve the deficiency of the small sample size of rectal cancer, the proposed network is combined with transfer learning technology. At last, the output layer of the network is modified, in which the global average pooling and a fully connected softmax layer are employed to replace the original ones, and then the rectal cancer 4 classification (T1, T2, T3, T4 staging) is output. Main results. Experiments of rectal cancer T staging are conducted on a dataset of 1078 rectal cancer images in 4 categories collected from the Department of Colorectal Surgery of the Third Affiliated Hospital of Kunming Medical University. The experimental results show that the accuracy, precision, recall and F 1 values obtained by the model are 94.66%, 94.70%, 94.65%, and 94.67%, respectively. Significance. The experimental results show that our model is superior to the existing classification models, can effectively and automatically classify ultrasound images of rectal cancer, and can better assist doctors in the diagnosis of rectal cancer. [ABSTRACT FROM AUTHOR]

Objective: Cervical lymph node metastasis (LNM) was found to be clinically significant prognostic factors of patients with papillary thyroid carcinomas (PTC). Ultrasound (US) characteristics of thyroid nodules and thyroid parenchyma may be used to predict LNM. To investigate the value of nodular US features as well as thyroid parenchymal microcalcifications on US in predicting LNM in patients with PTC. Methods: This prospective study was approved by the Institutional Review Board. From January 2018 to June 2019, 971 consecutive patients with solitary PTC who underwent preoperative neck US evaluation were included from six hospitals in China. The US features of thyroid nodules as well as thyroid parenchyma microcalcifications were carefully evaluated based on the static images and dynamic clips. Univariate and multivariate analyses were performed to determine independent predictors of LNM. Results: Of the 971 patients, 760 were female, 211 were male. According to the pathological examination, 241(24.82%) patients were found with cervical LNM (LNM positive group), while 730 (75.18%) patients were not (LNM negative group). Multiple logistic regression analysis showed that young age (<55 years old) (OR = 1.522, P = 0.047), large size (>10 mm) (OR = 1.814, P < 0.001), intratumoral microcalcifications (OR = 1.782, P = 0.002) and thyroid parenchyma microcalcifications (OR = 1.635, P = 0.046) were independent risk factors for LNM of PTC. Conclusions: Young age, large nodule size, intratumoral microcalcifications, as well as thyroid parenchyma microcalcifications on US are independent predictors of cervical LNM for patients with PTC. [ABSTRACT FROM AUTHOR]