We aimed to evaluate the value of sentinel lymph node contrast-enhanced ultrasound (SLN-CEUS) and surface tracing for the biopsy of intra-operative sentinel lymph nodes (SLNs). Between June 2015 and December 2017, a total of 453 patients with early invasive breast cancer were recruited. Patients received an intradermal injection of microbubble contrast agent around the areola on the day before surgery. The locations and sizes of lymphatic channels (LCs) and SLNs were marked on the body surface using gentian violet. Then, injection of double blue dye was performed half an hour before surgery. We compared the pathway of LCs and the location of SLNs obtained from SLN-CEUS and blue dye during surgery. Among the 453 patients, the mean numbers of LCs and SLNs detected by SLN-CEUS were 1.42 and 1.72, respectively, and the coincidence rate was 98.2% compared with blue dye during surgery. The median distance from the SLN to skin measured by preoperative CEUS and blue dye was 1.95 § 0.69 and 2.03 § 0.87 cm (p = 0.35). There were three SLN enhancement in our research, including homogeneous enhancement, inhomogeneous enhancement and no enhancement, with the sensitivity, specificity, positive predictive value and negative predictive value of SLN-CEUS for the diagnosis of SLNs being 96.82%, 91.91%, 87.54% and 98.01%, respectively. SLN-CEUS with skin marking can identify the pathway of LCs and the location of the SLN before surgery, measure the distance from the SLN to skin and determine if the SLN is metastatic. SLN-CEUS can be used as an effective complement to the blue dye method.

Adhesive capsulitis (AC) is a painful and disabling disorder, which caused restricted motion and chronic pain of shoulder. Intracavitary contrast-enhanced ultrasound has been recently applied to assess obstructive bile duct diseases, tubal patency, vesicoureteric reflux and so on. The aim of this study was to detect the value of US-arthrography by injecting the contrast agent SonoVue into glenohumeral joint compared with US in diagnosing AC. Utrasound (US) and US-arthrography images of 45 patients with AC were compared with that of 45 control subjects without AC with MRI as a gold standard. Patients with AC had a significantly thickened coracohumeral ligment (CHL, 3.1 mm) and inferior capsule (3.5 mm) on US, and a decreased volume of axillary recess (1.14 ml) on US-arthrography compared with the control subjects (1.59 ml). Filling defect (91.1%) and synovitis-like abnormality (75.6%) in the joint on US-arthrography were more sensitive than that of rotator interval abnormality (71.1%), thickened CHL more than 3 mm (64.4%), thickened inferior capsule more than 3.5 mm (66.7%) on US respectively for diagnosis of AC. Consequently, US-arthrography was more effective method than US for assessment of AC. Filling defects of joint cavity and synovitis-like abnormality in the joint are characteristic US-arthrography findings for diagnosing AC.

Reliable cell tracking is essential to understand the fate of stem cells following implantation, and thus promote the clinical application of stem cell therapy. Dual or multiple modal imaging modalities mediated by different types of multifunctional contrast agent are generally needed for efficient cell tracking. Here, we created a new contrast agent—PLGA/iron oxide microparticles (PLGA/IO MPs) and characterized the morphology, structure and function of enhancing both photoacoustic (PA) and magnetic resonance imaging (MRI). Both PA and MRI signal increased with increased Fe concentration of PLGA/IO MPs. Fluorescent staining, Prussian blue staining and transmission electron microscope (TEM) certified that PLGA/IO MPs were successfully encapsulated in the labeled TSCs. The established PLGA/IO MPs demonstrated superior ability of dual-modal PA/MRI tracking of TSCs without cytotoxicity at relatively lower Fe concentrations (50, 100 and 200 μg/mL). The optimal Fe concentration of PLGA/IO MPs was determined to be 100 μg/mL, thus laying a foundation for the further study of dual-modal PA/MRI tracking of TSCs in vivo and promoting the repair of injured tendon.

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ObjectiveThe purpose of this retrospective study is to evaluate the diagnostic value of contrast enhanced sonography plus gastric distention sonography, the Double Contrast-enhanced Ultrasound (DCUS) in gastric lesions.Methods107 cases with pathology confirmed gastric lesions were retrospectively reviewed, DCUS and oral contrast agent ultrasound (US) were performed in all cases prior to operation. Perfusion parameters including arrival time (AT), peak intensity (PI), time to peak (TTP), and area under the curve (AUC) of the lesion and surrounding normal tissue were analyzed. A reader blinded to pathology results were asked to rate and compare each case with surgical or resection biopsy pathology results.ResultsFrom the 107 gastric lesions, 75 were malignant gastric lesions (33 gastric cancers,42 gastrointestinal stromal tumors (GISTs)) and 32 were benign gastric lesions (11 inflammatory masses and 21 polypoid adenomas). Compared with US, DCUS achieved higher value in sensitivity (90.6% vs. 70.6%), specificity (75% vs. 62.5%), positive predictive value (89.5% vs. 81.5%), negative predictive value (77.4% vs. 47.6%), and overall accuracy (85.9% vs. 68.2%). When US was tested against DCUS, the increase in correct diagnoses value was significant (P = .01). Furthermore, gastric cancer had faster AT, higher PI and AUC than normal tissue (P<0.05); GIST and Inflammatory mass had higher PI than normal tissue (P<0.05); gastric cancer and GIST had faster AT than polypoid adenoma (P<0.05), Inflammatory mass showed higher PI than other 3 lesions and gastric cancer had higher PI than polypoid adenoma and GIST (P<0.05); gastric cancer and inflammatory mass had larger AUC than polypoid adenoma and GIST (P<0.05). Conclusion DCUS improved diagnostic performance compared with US. The combination of different CEUS enhancement characteristics with quantitative perfusion parameters may provide a promising tool to help differentiate gastric cancer and GIST from benign lesions.

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Background The purpose of this paper was to explore the correlation between multiple tumor markers and newly diagnosed gastric cancer. Methods We selected 268 newly diagnosed patients with gastric cancer and 209 healthy subjects for correlation research. The detection of multiple tumor markers was based on protein chips and the results were statistically analyzed using SPSS. Results We concluded that gastric cancer was significantly related to gender, age, alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 199 (CA199), and carbohydrate antigen 242 (CA242) positive levels (P < 0.001). After CA199 and CA242 were stratified by gender, the male odds ratio (OR) was 30.400 and 31.242, respectively, while the female OR was 3.424. After CA125 was stratified by age in patients over 54 years old with gastric cancer, the risk of occurrence in the CA125-positive population was 16.673 times that of the CA125-negative patients. Among patients 54 years old and younger, being CA125-positive was not a risk factor for gastric cancer (P = 0.082). AFP, CEA, CA125, CA199, and CA242 positive levels during the M1 stage were statistically significant when compared with the M0 stage and control group (P < 0.001), but the AFP (P = 0.045) and CA125 (P = 0.752) positive levels were not statistically significant when compared with the M0 stage and control group. The combined detection sensitivity of multiple tumor markers was 44.78%. Conclusion Our research shows that gastric cancer is associated with age, gender, and the positive levels of AFP, CEA, CA125, CA199, and CA242. The positive levels of AFP and CA125 were related to the distant metastasis of gastric cancer. To a certain extent, the combined detection sensitivity can be used for the initial screening of gastric cancer.

Objectives This study aims to develop and validate a virtual biopsy model to predict microsatellite instability (MSI) status in preoperative gastric cancer (GC) patients based on clinical information and the radiomics of deep learning algorithms. Methods A total of 223 GC patients with MSI status detected by postoperative immunohistochemical staining (IHC) were retrospectively recruited and randomly assigned to the training (n = 167) and testing (n = 56) sets in a 3:1 ratio. In the training set, 982 high-throughput radiomic features were extracted from preoperative abdominal dynamic contrast-enhanced CT (CECT) and screened. According to the deep learning multilayer perceptron (MLP), 15 optimal features were optimized to establish the radiomic feature score (Rad-score), and LASSO regression was used to screen out clinically independent predictors. Based on logistic regression, the Rad-score and clinically independent predictors were integrated to build the clinical radiomics model and visualized as a nomogram and independently verified in the testing set. The performance and clinical applicability of hybrid model in identifying MSI status were evaluated by the area under the receiver operating characteristic (AUC) curve, calibration curve, and decision curve (DCA). Results The AUCs of the clinical image model in training set and testing set were 0.883 [95% CI: 0.822–0.945] and 0.802 [95% CI: 0.666–0.937], respectively. This hybrid model showed good consistency in the calibration curve and clinical applicability in the DCA curve, respectively. Conclusions Using preoperative imaging and clinical information, we developed a deep-learning-based radiomics model for the non-invasive evaluation of MSI in GC patients. This model maybe can potentially support clinical treatment decision making for GC patients. Graphical abstract