Ultrasound combined with Ki-67 to construct the prognostic model for radioactive iodine therapy outcomes in Graves' disease patients.

The aim of this study was to develop a prognostic model for radioactive iodine (RAI) therapy outcome in patients with Graves' disease. We enrolled 127 patients. Information on RAI therapy, ultrasound indexes of thyroid, and other lifestyle factors was collected. The competing risk model was used to estimate the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for nonhealing or recurrence of hyperthyroidism (NHRH). The performance of the model was assessed by receiver operator characteristic analysis and the Brier score and internally validated by bootstrap resampling. Then, a nomogram was developed. Forty-one cases (32.2%) of NHRH were documented. Positive Ki-67 expression, a higher dose of per-unit thyroid volume, and females showed lower risks of NHRH (all P < 0.05). The HR values (95% CI) were 0.42 (0.23, 0.79), 0.01 (0.00, 0.02), and 0.47 (0.25, 0.89), respectively. The bootstrap validation showed that the model had the highest accuracy and good calibration for predicting cumulative risk of NHRH at 180 days after RAI therapy (AUC = 0.772; 95% CI: 0.640-0.889, Brier score = 0.153). By decision curve analysis, the nomogram was shown to have a satisfactory net benefit between thresholds of 0.20 and 0.40. Ki-67, ultrasound volumetry, and scintigraphy techniques can play important roles in evaluating RAI therapy outcome in Graves' disease patients. The prediction nomogram shows reasonable accuracy in predicting NHRH.

Construction and Validation of a Predictive Nomogram Based on Ultrasound for Lymph Node Metastasis of Papillary Thyroid Carcinoma in the Cervical Central Region.

ABSTRACT: To establish and validate a nomogram for predicting lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) in the cervical central region. This retrospective study included 287 PTC patients with 309 nodules treated from December 2018 to May 2020 at our hospital. The cohort was divided randomly into a training set and a testing set according to a 7:3 ratio. The training set contained 216 nodules, and the testing set contained 93 nodules. The nomogram was developed using the training set, and the data of the testing set were used to validate the performance of nomogram. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. The study showed multifocality, thyroid lesion size, and American College of Radiology Thyroid Imaging, Reporting and Data System (TI-RADS) score were significantly independently associated with LNM in the cervical central region. In the testing set, the calibration curve showed that the nomogram had good discrimination with a C-index of 0.775 (95% confidence interval, 0.680-0.869) and adequate calibration ( P = 0.808). By decision curve analysis and clinical impact curve analysis, the nomogram was shown to have a satisfactory net benefit between thresholds of 0.40 and 0.75. The nomogram can be used for predicting LNM of PTC in the cervical central region and may provide valuable guidance for planning the surgical treatment of PTC patients.

Ultrasound Guided Intra-Articular Injection of Triptolide-loaded Solid Lipid Nanoparticle for Treatment of Antigen-Induced Arthritis in Rabbits.

Objective: To evaluate the efficacy of ultrasound-guided intra-articular injection of triptolide-loaded solid lipid nanoparticle (TP-SLN) for treatment of antigen-induced arthritis (AIA) in rabbits. Material and Methods: Knee joints of 33 New Zealand rabbits with AIA were injected intra-articularly with triptolide (TP: n = 7), TP-SLN (n = 7), betamethasone (BS: n = 7) and dimethyl sulfoxide (DMSO: n = 6). The remaining six rabbits were untreated as the control group. The injection therapy in intervention groups was initiated 1 week after the last immunization in order to avoid irreversible joint damage in the later induction. The ultrasonic scores of the joints were assessed based on synovitis, synovial blood flow and bone erosion. Meanwhile, the correlations of ultrasonic scores and pathological scores were determined. The efficacy and side effects of each group were determined by combining ultrasonic scores, pathological scores, behavior, appetite, weight, joint diameter, skin temperature and biochemical examination. Results: 1) Compared with the control group, the diameters of knee joints of the TP, TP-SLN and BS groups began to reduce 1 week after intra-articular injection (p < 0.01). 2) With the exception of the DMSO group, the interventions were effective in treating synovitis compared with the control group, with TP-SLN and BS being the best. The ultrasonic and pathological scores in synovitis of the TP group were lower than that of model group (Z = -2.726 and -2.530, p < 0.05). The ultrasonic scores differed significantly between BS group and TP-SLN group (Z = -2.17 and -2.360, respectively, p < 0.05) and pathological scores (Z = -2.687 and -2.082, respectively, p < 0.05). 3) Compared with the control group, the TP, BS and TP-SLN were all effective in treating synovial blood flow and bone erosion and there were no significant differences of ultrasonic and pathological scores among them (p > 0.05). The ultrasonic scores of synovial blood flow (Z = -3.033, -2.842, -3.277, p < 0.01) were lower than in the controls. The ultrasonic scores (Z = -2.948, -3.141, -3.210, p < 0.01) and pathological scores (Z = -2.216, -2.505, -2.505, p < 0.05) of bone erosion were also lower than in the model group.4) There were significant correlations between the ultrasonic and pathological scores of synovial inflammation and bone erosion (r = 0.832 and 0.859 respectively, p < 0.001). Conclusions: The therapeutic effect of TP-SLN on arthritis is better than that of TP, but there is no difference between BS and TP-SLN. Therefore, TP-SLN may be used as an alternative to BS in the treatment of rheumatoid arthritis in the future. The ultrasonic and pathological scores showed significant correlation in synovitis and bone erosion. Ultrasound can provide a useful assessment of synovitis in early arthritis.

Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula.

Background: Central venous stenosis (CVS) of radiocephalic arteriovenous fistula (RCAVF) affects RCAVF function and longevity. Ultrasound screening for CVS is limited by acoustic window. Herein, we analyzed the quantitative axillary venous (AxV) spectrum in hemodialysis patients via RCAVF, and constructed central venous stenosis index (CVSI) model based on the spectrum parameters to early detect resting asymptomatic CVS. Methods: From August 2017 to May 2021, stage 5 chronic kidney disease (CKD) patients dialysed via RCAVF at the First Affiliated Hospital of Fujian Medical University were included in this study. No CVS-related symptoms were found and the pulsation at the arteriovenous anastomosis was normal. However, the patients had the sensation of swelling in the ipsilateral upper limb during dialysis; the venous pressure advanced upon the completion of dialysis; or both (n=52). The inclusion criteria were as follows: (I) Ultrasound (US) showed that the temporal phases of the AxV spectrum were "normal"; and (II) CVS was confirmed by digital subtraction angiography (DSA). The exclusion criteria were as follows: (I) stent placement; (II) multiple stenosis; and (III) placement of central venous catheter. A total of 37 patients participated in the analysis. Eighteen patients were included in the CVS group, and 19 cases without CVS were included in the control group. Independent sample t-test was used to screen each parameter of the AxV spectrum, and a CVSI model was constructed by principal component analysis (PCA). The receiver operating characteristic curve (ROC) was applied to analyze the diagnostic value of CVSI. Results: According to the independent sample t-test, 9 parameters were found to have statistical significance (all P<0.05); they were analyzed by PCA, and the CVSI model was constructed. The ROC showed that CVSI had diagnostic value for CVS. When the cut-off value of CVSI was 7.13, the maximum value of the Youden index was 0.842, with a sensitivity of 100% and a specificity of 84.2%. Conclusions: The CVSI helps to early detect resting asymptomatic CVS and dramatically increases the detection rate of CVS.

Evaluation of ultrasonography in fetal intestinal malrotation with midgut volvulus.

OBJECTIVES: To investigate the clinical significance of prenatal diagnosis and prognostic evaluation of fetal intestinal malrotation with midgut volvulus via ultrasonography. MATERIAL AND METHODS: Ultrasonographic findings and clinical outcomes of fetal intestinal malrotation with midgut volvulus prenatally diagnosed via ultrasound at the Zhangzhou Hospital Affiliated of Fujian Medical University from January 2013 to May 2020 were summarised and analyzed. RESULTS: Eleven cases of fetal intestinal malrotation with midgut volvulus were accurately prenatally diagnosed according to the specific ultrasound signs, such as 'whirlpool sign' and 'twining sign'. Indirect and nonspecific ultrasonographic signs included ascites in four cases and echogenic bowel in nine, all of which were accompanied by intestinal dilatation at various degrees. Among all cases, two were complicated with other system abnormalities, and one had a chromosome abnormality. Three pregnant women chose termination of pregnancy, and eight neonates were transferred to the pediatric department for surgery after obtaining written informed consent. An accurate prenatal diagnosis was confirmed postoperatively, and the fetus recovered well postoperatively. CONCLUSION: S: : Fetal intestinal malrotation with midgut volvulus has typical sonographic features, and ultrasonography is the method of choice for prenatal diagnosis of this disease. Fetal intestinal malrotation with midgut volvulus is a non-fatal congenital malformation that can be treated. Prenatal diagnosis is essential for early postnatal treatment, and early surgery can often obtain good efficacy and prognosis.

[Establishment of a predictive model for central cervical lymph node metastasis of papillary thyroid carcinoma based on ACR TI-RADS score and evaluation of its diagnostic efficacy].

Objective:To establish a predictive model for central lymph node metastasis（CLNM） of papillary thyroid carcinoma（PTC） based on ACR TI-RADS grades（ATR model） and evaluate its diagnostic efficacy. Methods:A total of 319 patients with PTC diagnosed from January 2019 to May 2020 were included, including 366 nodules were used as the modeling cohort to construct the risk prediction model. A total of 105 PTC patients with 121 nodules from June to August 2020 were included as the external validation cohort. The C-index of the model was calculated and the Hosmer-Lemeshow goodness-of-fit test was performed to compare the diagnostic efficiency of ACR model and those conventional imaging models. Results:The ATR model, Y=-3.719+0.765×gender+1.094×multifocality+0.08×maximum diameter+0.266×ACR TI-RADS score. In the training set, validation set and external validation cohort, the model C-index was 0.758（95%CI: 0.699-0.817）, 0.717（95%CI: 0.619-0.815） and 0.756（95%CI: 0.671-0.840）, respectively. The Hosmer-Lemeshow goodness of fit test showed that the prediction rate of the model was consistent with the actual incidence rate（P=0.918; P=0.581; P=0.366）. With ≥0.434 as the diagnostic threshold, the model had the highest diagnostic efficacy （sensitivity: 86.0%, specificity: 56.3%, Youden index: 0.423）. In the external validation cohort, there was no significant difference between C-US and CT（P>0.05）. Compared with C-US and CT, the sensitivity（66.1% vs 16.1%, P<0.001; 66.1% vs 9.7%, P<0.001） and accuracy（68.6% vs 55.4%, P=0.041; 68.6% vs 52.9%, P=0.012） of ATR model were higher, and the negative predictive value was higher than that of CT（66.7% vs 50.9%, P=0.042）, but there was no difference between ATR model and C-US（66.7% vs 52.3%, P=0.066）; There was no significant difference among the three positive predictive values（70.7% vs 83.3%, P=0.211; 70.7% vs 85.7%, P=0.319）, but the specificity of the model was low （71.2% vs 96.6%, P=0.001; 71.2% vs 98.3%, P<0.001）. Conclusion:The predictive model based on ACR TI-RADS grades can predict CLNM of PTC more accurately and sensitively than traditional imaging examination.

Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Ultrasound is one of the critical methods for diagnosis and treatment in thyroid examination. In clinical application, many reasons, such as large outpatient traffic, time-consuming training of sonographers, and uneven professional level of physicians, often cause irregularities during the ultrasonic examination, leading to misdiagnosis or missed diagnosis. In order to standardize the thyroid ultrasound examination process, this paper proposes using a deep learning method based on residual network to recognize the Thyroid Ultrasound Standard Plane (TUSP). At first, referring to multiple relevant guidelines, eight TUSP were determined with the advice of clinical ultrasound experts. A total of 5,500 TUSP images of 8 categories were collected with the approval and review of the Ethics Committee and the patient's informed consent. Then, after desensitizing and filling the images, the 18-layer residual network model (ResNet-18) was trained for TUSP image recognition, and five-fold cross-validation was performed. Finally, through indicators like accuracy rate, we compared the recognition effect of other mainstream deep convolutional neural network models. Experimental results showed that ResNet-18 has the best recognition effect on TUSP images with an average accuracy rate of 91.07%. The average macro precision, average macro recall, and average macro F1-score are 91.39%, 91.34%, and 91.30%, respectively. It proves that the deep learning method based on residual network can effectively recognize TUSP images, which is expected to standardize clinical thyroid ultrasound examination and reduce misdiagnosis and missed diagnosis.

Recognition of Fetal Facial Ultrasound Standard Plane Based on Texture Feature Fusion.

In the process of prenatal ultrasound diagnosis, accurate identification of fetal facial ultrasound standard plane (FFUSP) is essential for accurate facial deformity detection and disease screening, such as cleft lip and palate detection and Down syndrome screening check. However, the traditional method of obtaining standard planes is manual screening by doctors. Due to different levels of doctors, this method often leads to large errors in the results. Therefore, in this study, we propose a texture feature fusion method (LH-SVM) for automatic recognition and classification of FFUSP. First, extract image's texture features, including Local Binary Pattern (LBP) and Histogram of Oriented Gradient (HOG), then perform feature fusion, and finally adopt Support Vector Machine (SVM) for predictive classification. In our study, we used fetal facial ultrasound images from 20 to 24 weeks of gestation as experimental data for a total of 943 standard plane images (221 ocular axial planes, 298 median sagittal planes, 424 nasolabial coronal planes, and 350 nonstandard planes, OAP, MSP, NCP, N-SP). Based on this data set, we performed five-fold cross-validation. The final test results show that the accuracy rate of the proposed method for FFUSP classification is 94.67%, the average precision rate is 94.27%, the average recall rate is 93.88%, and the average F1 score is 94.08%. The experimental results indicate that the texture feature fusion method can effectively predict and classify FFUSP, which provides an essential basis for clinical research on the automatic detection method of FFUSP.

Combination of high-frequency ultrasound and virtual touch tissue imaging and quantification improve the diagnostic efficiency for mild carpal tunnel syndrome.

BACKGROUND: Carpal tunnel syndrome (CTS) is the most common entrapment symptom in the peripheral nerves. High-frequency ultrasound (HFUS) is widely used in the diagnosis of CTS. Virtual Touch Tissue Imaging and Quantification (VTIQ), which provides more information about the hardness of organization, is used to diagnose CTS. However, the data of diagnostic value of them in various degrees of CTS are limited. Whether the combination of HFUS and VTIQ can improve the diagnostic efficiency also remains unknown. The study aimed to explore the diagnostic value of HFUS and VTIQ in various degrees of CTS and whether combination of HFUS and VTIQ could improve the diagnostic efficiency of CTS. METHODS: A collection and analysis of 133 CTS patients and 35 volunteers from January 2016 to January 2019 were performed. We compared the clinical characteristics, cross-sectional area (CSA) value and shear wave velocity SWVmean value of CTS group with volunteer group. RESULTS: The CSA value and SWVmean value of CTS cohort were significantly higher than volunteer group (10.79 ± 2.88 vs. 8.06 ± 1.39, p < 0.001, 4.36 ± 0.95 vs. 3.38 ± 1.09, p < 0.001, respectively). The area under the curve (AUC) of receiver operating characteristic (ROC) curve of CSA value and SWVmean value were 0.794 and 0.757, respectively. Hierarchical analysis of CSA value and SWVmean value showed that the AUC in the moderate and severe CTS group were higher than in mild CTS group. Furthermore, the CSA value combined with SWVmean value used to diagnose mild CTS was 0.758, which was higher than that of single CSA value or single SWVmean value. CONCLUSIONS: Both HFUS and VTIQ technology were feasible to evaluate CTS. HFUS was suitable for use in diagnosis of moderate and severe CTS. For mild CTS, combination of HFUS and VTIQ was relevant to improve the diagnostic efficiency of CTS.

Applications of Mechanical Arm in the Virtual Touch Tissue Imaging Quantification and the Differential Diagnosis of Breast Tumors.

ABSTRACT: To assess the diagnostic performance of quantitative parameters for virtual touch tissue imaging quantification by the mechanical arm probe, 128 women with 152 breast lesions (90 benign and 62 malignant) were included and maximum elasticity (Vmax), median elasticity (Vmean), maximum elasticity minus minimum (Vmax-min), and minimum elasticity (Vmin) were measured. Intercorrelation coefficients and Bland-Altman plots were used to compare the repeatability and consistency of handheld probe and mechanical arm measurements. Receiver operating characteristic curve was used to evaluate the diagnostic efficiency. The results showed that intercorrelation coefficients were 0.694 to 0.951 by the mechanical arm and 95% limits of agreement were wider than handheld probe. Using 4.36 m/s as cutoff value for Vmax by the mechanical arm, we achieved sensitivity (88.7%) and specificity (90.0%). We concluded that the mechanical arm can reduce the influence of different scanning pressures on the elastic modulus of breast tissue.

Diagnostic Efficiency of Gynecologic Imaging Reporting and Data System Combined With 3-dimensional Contrast-enhanced Ultrasound Scoring System in Evaluating Ovarian Tumor.

To estimate the value of gynecologic imaging reporting and data system (GI-RADS) combined with 3-dimensional contrast-enhanced ultrasound (3D-CEUS) scoring system in the differential diagnosis of ovarian tumor. Both of 2-dimensional ultrasound (2D-US) and 3D-CEUS were performed on 114 patients with ovarian masses by Voluson E8 with SonoVue (Bracco, Italy). Besides, dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI) (Siemens Magneton Verio 3.0T, Germany) was performed on the patients. There were totally 62 benign and 52 malignant ovarian tumors in all patients. The ability of GI-RADS combined with 3D-CEUS scoring system to distinguish benign and malignant ovarian tumors was superior to conventional ultrasound GI-RADS classification. The sensitivity, specificity, and accuracy of GI-RADS combined with 3D-CEUS scoring system were 96.2% and 98.1%, 87.10%, whereas those of MRI were 87.10%, 91.23%, and 92.11% respectively, indicating that there was high concordance in ovarian tumors assessment between the 2 diagnostic methods. The new scoring system has a good correlation with microvessel density (P = 0.000, r = 0.73), estrogen receptor (P = 0.000, r = 0.59), progesterone receptor (P = 0.000, r = 0.56), and matrix metalloproteinase-9 (P = 0.000, r = 0.61). The GI-RADS combined with 3D-CEUS scoring system was valuable in clinical diagnosis and differential diagnosis of ovarian tumor and show good agreement with MRI.

A Benign and Malignant Breast Tumor Classification Method via Efficiently Combining Texture and Morphological Features on Ultrasound Images.

The classification of benign and malignant based on ultrasound images is of great value because breast cancer is an enormous threat to women's health worldwide. Although both texture and morphological features are crucial representations of ultrasound breast tumor images, their straightforward combination brings little effect for improving the classification of benign and malignant since high-dimensional texture features are too aggressive so that drown out the effect of low-dimensional morphological features. For that, an efficient texture and morphological feature combing method is proposed to improve the classification of benign and malignant. Firstly, both texture (i.e., local binary patterns (LBP), histogram of oriented gradients (HOG), and gray-level co-occurrence matrixes (GLCM)) and morphological (i.e., shape complexities) features of breast ultrasound images are extracted. Secondly, a support vector machine (SVM) classifier working on texture features is trained, and a naive Bayes (NB) classifier acting on morphological features is designed, in order to exert the discriminative power of texture features and morphological features, respectively. Thirdly, the classification scores of the two classifiers (i.e., SVM and NB) are weighted fused to obtain the final classification result. The low-dimensional nonparameterized NB classifier is effectively control the parameter complexity of the entire classification system combine with the high-dimensional parametric SVM classifier. Consequently, texture and morphological features are efficiently combined. Comprehensive experimental analyses are presented, and the proposed method obtains a 91.11% accuracy, a 94.34% sensitivity, and an 86.49% specificity, which outperforms many related benign and malignant breast tumor classification methods.

Development of an Ultrasound Prediction Model to Discriminate between Malignant and Benign Liver Lesions.

To discriminate between malignant and benign liver lesions, we evaluated the ultrasound features of the target lesions in 266 patients and established a prediction model using a logistic regression algorithm. The prediction model based on independent factors was expressed as predictive score = 1.129 × interaction of irregular shape and unclear boundary + 1.398 × occupying effect + 2.363 × hypo-echoic halo + 1.987 × marginal vascular sign + 3.627 × cirrhosis background + 2.976 × nodule in nodule sign + 3.690 × metastasis sign. Receiver operating characteristic curve analysis revealed that the optimal cutoff predictive score was 2.8 (area under the curve = 0.942). The specificity of the prediction model was not significantly different from that of computed tomography/magnetic resonance imaging (91.7% vs. 98.8%, p = 0.077), whereas the prediction model had a lower sensitivity (90.1% vs. 97.8%, p < 0.001) and accuracy (90.6% vs. 98.1%, p < 0.001) than computed tomography/magnetic resonance imaging. We conclude that the ultrasound prediction model exhibited good diagnostic performance in discriminating malignant from benign liver lesions.

Evaluation of Skeletal Muscle Microcirculation and Reserve Function of the Type 2 Diabetes with Contrast-Enhanced Ultrasonography.

OBJECTIVE: This study aimed to discuss clinical application value of contrast-enhanced ultrasonography on lesion skeletal muscle microcirculation and arterial perfusion reserve in type 2 diabetes mellitus and complicated microvessels. METHODS: Patients in the control group, type 2 diabetes mellitus (DM) group, diabetic microangiopathy (DM + MC) group underwent contrast-enhanced ultrasonography before and after temporary arterial occlusion to observe blood perfusion of gastrocnemius muscle; draw the time-intensity curve of arteriole, muscular tissue, and venule, and obtain perfusion parameters such as contrast agent arrival time and contrast agent transit time. Blood glucose, insulin, insulin resistance index, and relevant blood rheology parameters were measured. RESULTS: Contrast agent transit time of the DM + MC group before arterial occlusion was significantly longer than that of the DM group and control group (P < 0.05). Contrast agent transit time of the DM + MC group after temporary arterial occlusion was significantly longer than that of the DM group and control group (P < 0.05). Contrast agent transit time of △artery-muscle, △artery-vein, and △muscle-vein of the DM group and control group and △artery-muscle of the DM + MC group after arterial occlusion was significantly shortened, when compared with that before arterial occlusion (P < 0.05). For △muscle-vein and △artery-vein contrast agent transit time in the DM + MC group, the difference was not statistically significant. By comparing blood glucose, insulin, insulin resistance index, and relevant blood rheology parameters among the DM + MC group, DM group, and control group, the difference was statistically significant, and there was a good correlation. CONCLUSION: Contrast-enhanced ultrasonography can be used to evaluate skeletal muscle microcirculation disturbance and arterial reserve function of patients who had type 2 diabetic microangiopathy.

Point-of-Care Ultrasound-A New Option for Early Quantitative Assessment of Pulmonary Edema.

The aim of the work described here was to investigate the value of point-of-care ultrasound (POCUS) in the early assessment of the severity of pulmonary edema in rabbits. A rabbit oleic acid (OA)-induced pulmonary edema model was used. Thirty-two New Zealand rabbits were randomly divided into four groups: a control group and three pulmonary edema groups (mild, moderate and severe). Features of transthoracic B-line artifacts (BLA), blood pH, PaO2 and PaCO2, serum inflammatory factors, lung coefficient (LC), lung wet-to-dry weight ratio (W/D) and lung histopathology were assessed. BLA features and severity of pulmonary edema were semiquantitatively scored. Correlations between the number of BLA and PaO2, PaCO2, serum inflammatory factors, LC and W/D were analyzed. An additional 8 rabbits with severe pulmonary edema were used as the verified group, in which the lung was divided into ex vivo BLA (BLA-ev)-free (BLA-ev-free) and BLA-ev-clustered subregions depending on the features of BLA-ev recorded by ex vivo lung ultrasound. Lung specimens from each subregion were collected for histopathological examination. Relationships between features of BLA-ev and lung histopathological abnormalities were analyzed. With increasing doses of OA, number of BLA, W/D and levels of serum inflammatory factors decreased. Meanwhile, lung pathologic abnormalities were aggravated. In addition, time of appearance of BLA, blood pH and PaO2, and PaCO2 decreased dose dependently on OA (p < 0.05). Number of BLA was linear positively correlated with severity of pulmonary edema (r = 0.953, p < 0.05). Consistently, the features of BLA-ev reflected the severity of lung histopathological abnormalities (r = 0.936, p < 0.05). Thus, POCUS is useful in the early quantitative assessment of the severity of pulmonary edema.

Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses.

OBJECTIVE: The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses. METHODS: In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results. RESULTS: (1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience. CONCLUSIONS: The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses.

Combination of GI-RADS and 3D-CEUS for differential diagnosis of ovarian masses

SUMMARY OBJECTIVE The purpose of this study is to evaluate the efficacy of the combination of gynecologic imaging reporting and data system (GI-RADS) ultrasonographic stratification and three-dimensional contrast-enhanced ultrasonography (3D-CEUS) in order to distinguish malignant from benign ovarian masses. METHODS In this study, 102 patients with ovarian masses were examined by both two-dimensional ultrasound(2D-US) and 3D-CEUS. Sonographic features of ovarian masses obtained from 3D-CEUS were analyzed and compared with 2D-US. All patients with ovarian masses were confirmed by operational pathology or long-term follow-up results. RESULTS (1)The Chi-square test and multiple Logistic regression analysis confirmed that there were only eight independent predictors of malignant masses, including thick septa (≥3mm), thick papillary projections(≥7mm), solid areas, presence of ascites, central vascularization, contrast enhancement, distribution of contrast agent, and vascular characteristics of the solid part and their odds ratios which were 5.52, 5.39, 4.94, 4.34, 5.92, 7.44, 6.09, and 7.67, respectively (P<0.05). (2)These eight signs were used to combine the GI-RADS with 3D-CEUS scoring system in which the corresponding value of the area under the curve (AUC) was 0.969, which was superior to using GI-RADS lonely (Z-value=1.64, P<0.025). Using 4 points as the cut-off, the scoring system showed the performance was clearly better than using GI-RADS alone (P<0.05). (3) The Kappa value was 0.872 for two different clinicians with equal experience. CONCLUSIONS The combination of GI-RADS and 3D-CEUS scoring system would be a more effective method to distinguish malignant from benign ovarian masses.

RESUMO OBJETIVO O objetivo deste estudo é avaliar a eficácia da combinação da estratificação por ultrassonografia usando o Sistema de Relatórios e Dados de Imagem Ginecológica (GI-RADS) e ultrassonografia 3D com contraste (3D-CEUS) para diferenciar massas ovarianas benignas de malignas. METODOLOGIA Neste estudo, 102 pacientes com massas ovarianas foram examinadas usando ultrassonografia bidimensional (2D-US) e 3D-CEUS. As características ultrassonográficas das massas ovarianas obtidas com 3D-CEUS foram analisadas e comparadas com de 2D-US. Todos os pacientes com massas ovarianas tiveram o diagnóstico confirmado pelos resultados de patologia cirúrgica ou acompanhamento de longo prazo. RESULTADOS (1) O teste qui-quadrado e a regressão logística múltipla confirmaram a existência de apenas oito preditores independentes de massas malignas, incluindo septos espessos (≥3mm), projeções papilares espessas (≥7mm), áreas sólidas, presença de ascite, vascularização central, aumento de contraste, distribuição do agente de contraste e características vasculares da parte sólida e suas razões de possibilidades (OR), que foram 5,52, 5,39, 4,94, 4,34, 5,92, 7,44, 6,09 e 7.67, respectivamente (P< 0,05). (2) Esses oito preditores foram utilizados para combinar o GI-RADS com o sistema de escores da 3D-CEUS, para o qual o valor correspondente da área sob a curva (AUC) foi de 0,969, superior ao uso exclusivo do GI-RADS (valor de Z = 1,64, P < 0,025). Usando 4 pontos como corte, o sistema de escores mostrou que o desempenho foi muito melhor do que com o uso exclusivo do GI-RADS (P < 0,05). (3) O valor de Kappa foi 0,872, obtido por dois médicos diferentes com igual experiência. CONCLUSÃO A combinação do GI-RADS e do sistema de pontuação da 3D-CEUS é um método mais eficaz para distinguir massas ovarianas benignas de malignas.

The Clinical Value of New Scoring System of Cervical Lymph Node.

To distinguish malignant cervical lymphadenopathy, we established a new scoring system based on ultrasound features. Two hundred sixty-three patients with cervical lymphadenopathy received ultrasonic examination and underwent ultrasound-guided core needle biopsy or fine needle aspiration. The scoring system was proposed by multivariate logistic regression analysis and compared with Liao scoring system (0.06 × age + 4.76 × shortest-to-longest axis ratio + 2.15 × internal echo + 1.80 × vascular pattern). A new scoring system model, 1.346 × margin + 1.339 × hilum + 2.411 × calcification + 2.619 × vascular pattern + 0.837 × shortest-to-longest axis ratio, was generated. Lymph nodes were regarded as malignancy when the score was ≥2.4. Compared with the Liao scoring system, the new scoring system had larger area under the curve (0.86 versus 0.76, P = 0.036), specificity (86.7% versus 75.0%, P = 0.001), accuracy (87.1% versus 80.6%, P = 0.007), and positive predictive value (89.0% versus 80.0%, P = 0.043). Sensitivity (87.4% versus 85.3%, P = 0.647) and negative predictive value (85.0% versus 81.0%, P = 0.395) did not differ. We concluded that the new scoring system is more reliable and can play an important role in the differential diagnosis of cervical lymph nodes.

Prenatal Evaluation for Detection of Anorectal Atresia: Value of Ultrasound.

OBJECTIVES: To investigate the applicability and value of ultrasound (US) in the diagnosis of anorectal atresia. METHODS: Between January 2008 and January 2016, we prospectively evaluated 63,101 fetuses (gestational age, 20-38 weeks), including low- and high-risk populations using 2-dimensional US scans. An abnormal imaging finding was defined as an anal canal diameter of less than the 95% confidence interval (small anal canal) of the normal range or the absence of an anal canal and rectum. Imaging findings were considered normal on detection of an anal canal with a normal width and the absence of abnormalities. Prenatal imaging findings were confirmed by a postnatal or postmortem examination. RESULTS: Among the investigated fetuses, 28 showed evidence of anorectal atresia on US scans, and 22 of those with anorectal atresia had additional anomalies. Six cases of isolated anorectal atresia were successfully detected during the preclusive prenatal US scans. Four cases of a low imperforate anus (including 2 covered anuses) yielded false-negative results, indicating a diagnostic rate of 87.5% (28 of 32). The normal appearance of the fetal rectum and anal canal ruled out anorectal atresia in 30 fetuses with a dilated colon. Additionally, there were 3 false-positive cases, in which a narrow anal canal was observed. CONCLUSIONS: Identifying the abnormal appearance or absence of the fetal anal canal and rectum on preclusive US anomaly scans is useful for prenatal diagnosis or exclusion of anorectal atresia, which may help improve the detection of isolated anorectal atresia. Furthermore, a combined evaluation of the longitudinal and axial appearances of the fetal anal canal and rectum can improve diagnostic accuracy.