ObjectiveTo systematically review the value of ultrasound contrast agents injected subcutaneously for diagnosing sentinel lymph nodes of breast cancer.
MethodsWe electronically searched databases including PubMed, EMbase, The Cochrane Library, CNKI, CBM, WanFang Data, and Medalink from their inception to July 2014, to collect diagnostic accuracy studies of ultrasound contrast agents injected subcutaneously for diagnosing sentinel lymph nodes of breast cancer. Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data and assessed the methodological quality of included studies. Then, meta-analysis was performed by using Meta-Disc 1.4 software.
ResultsEight studies involving 311 sentinel lymph nodes were included. The results of meta-analysis showed that, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the area under curve (AUC) of SROC were 0.89 (95%CI 0.84 to 0.93), 0.81 (95%CI 0.72 to 0.87), 4.14 (95%CI 2.20 to 7.79), 0.15 (95%CI 0.10 to 0.25), 33.23 (95%CI 11.17 to 98.83), and 0.96 respectively.
ConclusionContrast-enhanced ultrasound has a high value in diagnosis of sentinel lymph nodes of breast cancer. Due to limited quality and quantity of the included studies, more high quality and large-scale studies are needed to verify the above conclusion.
Objective To observe the protective effect of ultrasound microbubble contrast agentmediated transfection of brain-derived neurotrophic factor(BDNF) into the retina and visual cortex on retinal ganglion cells (RGC) after optic nerve injury. Methods A total of 88 male Sprague-Dawley (SD) rats were randomly divided into normal group (group A, eight rats), sham operation group (group B, 16 rats), control group (group C, 16 rats), eyes transfection group (group D, 16 rats), brain transfection group (group E, 16 rats), combined transfection group (group F, 16 rats). The optic nerve crush injury was induced, and then the groups B to F were divided into one-week and two-week after optic nerve injury subgroup with eight rats each, respectively. The rats in group B and C underwent intravitreal and visual cortex injection with phosphate buffered solution respectively. The rats in group D and E underwent intravitreal and visual cortex injection with the mixture solution of microbubbles and BDNF plasmids respectively. The rats in group F underwent both intravitreal and visual cortex injection with the mixture solution of microbubbles and BDNF plasmids at the same time. The ultrasound exposure was performed on the rats in group D to F after injection with the mixture solution of microbubbles and BDNF plasmids. One and two weeks after optic nerve injury, RGC were retrogradely labeled with Fluorogold; active caspase-3 protein was observed by immunohistochemistry and the N95 amplitude was detected by pattern electroretinogram (PERG). Results Golden fluorescence can be observed exactly in labeled RGC in all groups，the difference of the number of RGC between the six groups and ten subgroups were significant（F=256.30，65.18；P＜0.01）. Active caspase-3 in ganglion cell layer was detected in group C to F, but not in group A and B. The difference of the N95 amplitude between the six groups and ten subgroups were significant（F=121.56，82.38；P＜0.01）.Conclusion Ultrasound microbubble contrast agent-mediated BDNF transfection to the rat retina and visual cortex can inhibit the RGC apoptosis after optic nerve injury and protect the visual function.
ObjectiveTo evaluate the diagnostic value of contrast enhanced ultrasound (CEUS) to the sentinel lymph node (SLN) of breast cancer.
MethodsSeventy-two operable breast cancer patients with clinically negative axillary lymph node were enrolled.Sulphur hexafluoride microbubbles for injection (SonoVue) was used alone as the tracer agent for the sentinel lymph node biopsy (SLNB), and axillary dissection was performed after the methylene blue location.All SLNs were examined pathologically with HE staining.The SLN diagnosis result of contrast enhanced ultrasound and postoperative pathological examination result were comparative analyzed.
ResultsAfter the injection of SonoVue can obtain a clear image of the lymphatic vessels and SLN.The success rate of CEUS imaging was 84.72% (61/72) in this group of 72 patients, and the false negative rate was 12.12% (4/33).The sensitivity and specificity of diagnosis by CEUS was 92.50% (37/40) and 92.59% (50/54), respectively, the diagnostic odds ratio (DOR) was 154.17.By the pathology results as the gold standard, the internal consistency of these two methods was good (Kappa value=0.848, P < 0.01).
ConclusionCEUS may be a useful orientation and determination method for SLNs.
Due to its irregular shape and varying contour, pancreas segmentation is a recognized challenge in medical image segmentation. Convolutional neural network (CNN) and Transformer-based networks perform well but have limitations: CNN have constrained receptive fields, and Transformer underutilize image features. This work proposes an improved pancreas segmentation method by combining CNN and Transformer. Point-wise separable convolution was introduced in a stage-wise encoder to extract more features with fewer parameters. A densely connected ensemble decoder enabled multi-scale feature fusion, addressing the structural constraints of skip connections. Consistency terms and contrastive loss were integrated into deep supervision to ensure model accuracy. Extensive experiments on the Changhai and National Institute of Health (NIH) pancreas datasets achieved the highest Dice similarity coefficient (DSC) values of 76.32% and 86.78%, with superiority in other metrics. Ablation studies validated each component’s contributions to performance and parameter reduction. Results demonstrate that the proposed loss function smooths training and optimizes performance. Overall, the method outperforms other advanced methods, enhances pancreas segmentation performance, supports physician diagnosis, and provides a reliable reference for future research.
Objective To investigate the value of contrast-enhanced ultrasonography in detection and diagnosis of small primary liver cancer. Methods SonoVue-enhanced ultrasonography were performed on 353 patients with 378 primary liver cancer, less than 3 cm in diameter. Enhancement patterns and enhancement phases of hepatic lesions on contrast-enhanced ultrasonography were analyzed and compared with the results of histopathology. Results In all hepatic tumors, 96.6% （365/378） lesions enhanced in the arterial phase. Among them, 317 (83.9%) tumors enhanced earlier than liver parenchyma and 48 (12.7%) tumors enhanced synchronously with liver parenchyma, and 342 (90.5%) tumors showed early wash-out in the portal and late phases. With regard to the enhancement pattern, 329 (87.0%) tumors presented whole-lesion enhancement, 35 (9.3%) to be mosaic enhancement and 14 (3.7%) to be rim-like enhancement. If taking the whole-lesion enhancement and mosaic enhancement in arterial phase as diagnotic standard for primary liver cancer on contrast-enhanced ultrasonography, the sensitivity was 92.9%(351/378), and if the earlier or synchronous enhancement of the tumor compared with liver parenchyma in arterial phase and the wash-out in portal phase were regarded as the stardand, the sensitivity was 87.3%(330/378). Conclusion Contrast-enhanced ultrasonography could display real-time enhancement patterns as well as the wash-out processes both in hepatic tumors and the liver parenchyma. It might be of clinical value in diagnosis of primary liver cancer based on the hemodynamics of hepatic tumors on contrast-enhanced ultrasonography.
ObjectivesTo evaluate the association between high homocysteine (Hcy) levels and risk of contrast-induced nephropathy (CIN).MethodsCNKI, VIP, WanFang Data, PubMed, The Cochrane Library and Web of Science databases were electronically searched to collect the case-control studies on the association between Hcy and risk of CIN from inception to November 30th, 2017. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was performed by using Stata 12.0 software.ResultsTen case-control studies involving 6 124 subjects were included. Meta-analysis showed that the high Hcy level was associated with an increased risk of CIN (OR=1.59, 95%CI 1.33 to 1.89, P<0.001), and the homocysteine level in CIN group was higher than that in non-CIN group (WMD=8.74, 95%CI 6.18 to 11.31,P<0.001).ConclusionsAccording to the current evidence, the high Hcy level is a risk factor for CIN. Due to limited quality and quantity of the included studies, more high quality studies are required to verify the above conclusion.
Objective To determine the correlation between central macular thickness (CMT) and the visual function in patients iwht macular edema (ME). Methods The clinical data of 42 eyes of 40 patients with ME which were examined by optical coherence tomography (OCT) and microperimetry (MP-1) were retrospectively analyzed. In 40 patients (42 eyes), diabetic ME (DME) was in 27 eyes，branch retinal vein occlusion was in 11eyes, and central retinal vein occlusion was in 4 eyes. All of the eyes had undergone OCT，MP-1 and best-corrected visual acuity (BCVA) test. Central macular thickness (CMT) was measured by fast macular scans using OCT. Retinal sensitivity (MS) and fixation patterns were evaluated by Mp-1. The position was chosen :2 disc diameters (DD) temporal to the disc and one third of a DD inferior to the centre of the disc. Results The correlation between CMT and BCVA is not significant (r＝－0.429，P=0.069) as well as the correlation between CMT and MS (r＝－0.433，P=0.058). The difference of CMT between the unstable and stable group was significant (F=3.262, P=0.039）. The difference of CMT between the central fixation group and preferred retinal locus (PRL) group was significant (F=3.173, P=0.044). Conclusions BCVA and MS have no significant correlation with CMT. When CMT increases, the fixation stability decreases, fixation location.changes, and PRL occurs.
Objective
To determine the value of contrast-enhanced ultrasound (CEUS) in the differentiation of primary liver cancer (PLC) and hepatic alveolar echinococcosis (HAE).
Methods
The data of 56 patients with PLC or HAE were collected between January 2010 and May 2015. Grayscale and CEUS features of the patients were analyzed retrospectively. The frequency of each imaging finding, including calcification, arterial enhancement, and internal enhancement were evaluated and compared.
Results
Statistically significant difference of the proportion of gender and age were detected between the two groups (P=0.013, 0.002). Thirty-eight PLC lesions were detected in 32 patients. The diameters of PLC lesions were 3-10 cm with an average of (5.6±2.1) cm. Thirty-two HAE lesions were found in 24 patients. The diameters of HAE lesions were 4-12 cm with an average of (9.1±4.4) cm. Statistically significant difference of lesion size and the incidence rate of calcification (5.3% vs. 75.0%) were seen between PLC and HAE (P<0.001). Peripheral enhancement were seen in 100.0% (38/38) PLC lesions, including 84.2% (32/38) hyperenhancement and 15.8% (6/38) dendritic hyperenhancement. All PLC lesions demonstrated hypoenhancement in late phase. Irregular peripherally hyperenhancement both in arterial and late phase were detected in 43.8% (14/32) HAE lesions. The other 56.2% (18/32) HAE lesions showed no peripheral enhancement both in arterial and late phase. No internal enhancement were seen in HAE lesions. The presence of arterial enhancement (100.0% vs. 43.8%) and absence of internal enhancement (0 vs. 100.0%) were significantly different between PLC and HAE (P<0.001).
Conclusions
PLC is predicted by arterial phase hyperenhancement and late phase hypoenhancement on CEUS. HAE is predicted with calcification on baseline sonography and internal non-enhancement on CEUS. Arterial phase enhancement is less common and less intensive in HAE than in PLC which also contributes to the differentiation of these lesions.
Sample size calculation is an important factor to evaluate the reliability of the diagnostic test. In this paper, a case study of the clinical diagnostic test of artificial intelligence for identification of liver contrast-enhanced ultrasound was performed to conduct two-category and multi-categories studies. Based on sensitivity and specificity, the sample size was then estimated in combination with the statistical characteristics of disease incidence, test level and one/two-sided test. Eventually, the sample size was corrected by integrating the factors of the proportion of training/test dataset and the dropout rate of cases in the medical image recognition system. Moreover, the application of Sample Size Calculator, MedCalc, PASS, and other software can accelerate sample size calculation and reduce the amount of labor.
