Predicting the malignancy of extremity soft-tissue tumors by an ultrasound-based radiomics signature.

BACKGROUND: Accurate differentiation of extremity soft-tissue tumors (ESTTs) is important for treatment planning. PURPOSE: To develop and validate an ultrasound (US) image-based radiomics signature to predict ESTTs malignancy. MATERIAL AND METHODS: A dataset of US images from 108 ESTTs were retrospectively enrolled and divided into the training cohort (78 ESTTs) and validation cohort (30 ESTTs). A total of 1037 radiomics features were extracted from each US image. The most useful predictive radiomics features were selected by the maximum relevance and minimum redundancy method, least absolute shrinkage, and selection operator algorithm in the training cohort. A US-based radiomics signature was built based on these selected radiomics features. In addition, a conventional radiologic model based on the US features from the interpretation of two experienced radiologists was developed by a multivariate logistic regression algorithm. The diagnostic performances of the selected radiomics features, the US-based radiomics signature, and the conventional radiologic model for differentiating ESTTs were evaluated and compared in the validation cohort. RESULTS: In the validation cohort, the area under the curve (AUC), sensitivity, and specificity of the US-based radiomics signature for predicting ESTTs malignancy were 0.866, 84.2%, and 81.8%, respectively. The US-based radiomics signature had better diagnostic predictability for predicting ESTT malignancy than the best single radiomics feature and the conventional radiologic model (AUC = 0.866 vs. 0.719 vs. 0.681 for the validation cohort, all P <0.05). CONCLUSION: The US-based radiomics signature could provide a potential imaging biomarker to accurately predict ESTT malignancy.

Percutaneous nephrolithotomy guided by 5G-powered robot-assisted teleultrasound diagnosis system: first clinical experience with a novel tele-assistance approach (IDEAL stage 1).

BACKGROUND: To demonstrate the technical feasibility of percutaneous nephrolithotomy (PCNL) guided by 5G-powered robot-assisted teleultrasound diagnosis system (RTDS) in a complex kidney-stone (CKS) cohort and present our preliminary outcomes. PCNL is highly skill-required, which hinders it popularization in primary medical units of remote regions. We designed an innovative tele-assistance approach to make PCNL easy to be operated by inexperienced surgeons. METHODS: This was a prospective proof-of-concept study (IDEAL phase 1) on intraoperative tele-assistance provided by online urological experts via a 5G-powered RTDS. Total 15 CKS patients accepted this technology. Online experts manipulated a simulated probe to assist unskilled local operators by driving a patient-side robot-probe to guide and monitor the steps of access establishment and finding residual stones. RESULTS: Median total delay was 177ms despite one-way network-connecting distance > 5,800 km. No perceptible delay of audio-visual communication, driving robot-arm or dynamic ultrasound images was fed back. Successful tele-assistance was obtained in all cases. The first-puncture access-success rate was 78.6% with a one-session SF rate of 71.3% and without complications of grade III-V. CONCLUSIONS: The current technology based on 5G-powered RTDS can provide high-quality intraoperative tele-assistance, which has preliminarily shown satisfactory outcomes and reliable safety. It will break down a personal competence-based barrier to endow PCNL with more popular utilization. TRIAL REGISTRATION: The study was approved by ethics committee of the Xinjiang Kezhou People's Hospital and ethics committee of the First Affiliated Hospital of Nanjing Medical University and was registered on http://www.chictr.org.cn (ChiCTR2200065849, 16/11/2022).

A multiparametric clinic-ultrasomics nomogram for predicting extremity soft-tissue tumor malignancy: a combined retrospective and prospective bicentric study.

OBJECTIVE: We aimed at building and testing a multiparametric clinic-ultrasomics nomogram for prediction of malignant extremity soft-tissue tumors (ESTTs). MATERIALS AND METHODS: This combined retrospective and prospective bicentric study assessed the performance of the multiparametric clinic-ultrasomics nomogram to predict the malignancy of ESTTs, when compared with a conventional clinic-radiologic nomogram. A dataset of grayscale ultrasound (US), color Doppler flow imaging (CDFI), and elastography images for 209 ESTTs were retrospectively enrolled from one hospital, and divided into the training and validation cohorts. A multiparametric ultrasomics signature was built based on multimodal ultrasomic features extracted from the grayscale US, CDFI, and elastography images of ESTTs in the training cohort. Another conventional radiologic score was built based on multimodal US features as interpreted by two experienced radiologists. Two nomograms that integrated clinical risk factors and the multiparameter ultrasomics signature or conventional radiologic score were respectively developed. Performance of the two nomograms was validated in the retrospective validation cohort, and tested in a prospective dataset of 51 ESTTs from the second hospital. RESULTS: The multiparametric ultrasomics signature was built based on seven grayscale ultrasomic features, three CDFI ultrasomic features, and one elastography ultrasomic feature. The conventional radiologic score was built based on five multimodal US characteristics. Predictive performance of the multiparametric clinic-ultrasomics nomogram was superior to that of the conventional clinic-radiologic nomogram in the training (area under the receiver operating characteristic curve [AUC] 0.970 vs. 0.890, p = 0.006), validation (AUC: 0.946 vs. 0.828, p = 0.047) and test (AUC: 0.934 vs. 0.842, p = 0.040) cohorts, respectively. Decision curve analysis of combined training, validation and test cohorts revealed that the multiparametric clinic-ultrasomics nomogram had a higher overall net benefit than the conventional clinic-radiologic model. CONCLUSION: The multiparametric clinic-ultrasomics nomogram can accurately predict the malignancy of ESTTs.

Association of body composition with bone mineral density and fractures in Chinese male type 2 diabetes mellitus.

The association between body composition and bone health in men over 50 years with type 2 diabetes mellitus remains unclear. We aimed to investigate how fat and lean mass affect bone health in male patients with diabetes over 50 years. A total of 233 hospitalized male type 2 diabetes mellitus patients with aged 50 to 78 years were enrolled. Lean mass, fat mass and bone mineral density (BMD) were estimated. The clinical fractures were also assessed. Glycosylated hemoglobin, bone turnover markers, and biochemical parameters were measured. The normal BMD group had a higher lean mass index (LMI) and fat mass index (FMI) and lower levels of bone turnover markers. glycosylated hemoglobin was negatively correlated with LMI (r = -0.224, P = .001) and FMI (r = -0.158, P = .02). In partial correlation adjusted for age and body weight, FMI was negatively correlated (r = -0.135, P = .045) with lumbar spine, while LMI was still positively correlated with lumbar spine (R = 0.133, P = .048) and total hip (R = 0.145, P = .031). In multiple regression analysis, LMI was consistently associated with BMD at the spine (ß = 0.290, P < .01), hip (ß = 0.293, P < .01), and femoral neck (ß = 0.210, P = .01), whereas FMI was only positively associated with BMD at the femoral neck (ß = 0.162, P = .037). A total of 28 patients diagnosed with diabetic osteoporotic fractures had lower LMI and FMI than their non-fractured counterparts. LMI was negatively associated with fracture, whereas FMI had such an effect only before adjusting for BMD. Lean mass is dominant in maintaining BMD and is a BMD-independent protective factor for diabetic osteoporotic fracture in male patients aged over 50 years. Fat mass in gravity is positively associated with BMD in the femoral neck, which may mediate fracture protection.

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

OBJECTIVES: To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features and clinical characteristics for evaluating therapeutic response after neoadjuvant chemotherapy (NAC) in patients with breast cancer. METHODS: A total of 603 patients who underwent NAC were retrospectively included between January 2018 and June 2021 from three different institutions. Four different deep convolutional neural networks (DCNNs) were trained by pretreatment ultrasound images using annotated training dataset (n = 420) and validated in a testing cohort (n = 183). Comparing the predictive performance of these models, the best one was selected for image-only model structure. Furthermore, the integrated DLR model was constructed based on the image-only model combined with independent clinical-pathologic variables. Areas under the curve (AUCs) of these models and two radiologists were compared by using the DeLong method. RESULTS: As the optimal basic model, Resnet50 achieved an AUC and accuracy of 0.879 and 82.5% in the validation set. The integrated DLR model, yielding the highest classification performance in predicting response to NAC (AUC 0.962 and 0.939 in the training and validation cohort), outperformed the image-only model and the clinical model and also performed better than two radiologists' prediction (all p < 0.05). In addition, predictive efficacy of the radiologists was improved under the assistance of the DLR model significantly. CONCLUSION: The pretreatment US-based DLR model could hold promise as a clinical guidance for predicting NAC response of patients with breast cancer, thereby providing benefit of timely treatment strategy adjustment to potential poor NAC responders. KEY POINTS: • Multicenter retrospective study showed that deep learning radiomics (DLR) model based on pretreatment ultrasound image and clinical parameter achieved satisfactory prediction of tumor response to neoadjuvant chemotherapy (NAC) in breast cancer. • The integrated DLR model could become an effective tool to guide clinicians in identifying potential poor pathological responders before chemotherapy. • The predictive efficacy of the radiologists was improved under the assistance of the DLR model.

Combining primary tumor features derived from conventional and contrast-enhanced ultrasound facilitates the prediction of positive axillary lymph nodes in Breast Imaging Reporting and Data System category 4 malignant breast lesions.

PURPOSE: To determine whether the primary tumor features derived from conventional ultrasound (US) and contrast-enhanced US (CEUS) facilitate the prediction of positive axillary lymph nodes (ALNs) in breast cancer diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4. METHODS: A total of 240 women with breast cancer who underwent preoperative conventional US, strain elastography, and CEUS between September 2016 and December 2019 were included. The multiple parameters of the primary tumor were obtained, and univariate and multivariate analyses were performed to predict positive ALNs. Then three prediction models (conventional US features, CEUS features, and the combined features) were developed, and the diagnostic performance was evaluated with receiver operating characteristic curves. RESULTS: On conventional US, the traits of large size and the non-circumscribed margin of the primary tumor were marked as two independent predictors. On CEUS, the features of vessel perforation or distortion and the enhanced range of the primary tumor were marked as two independent predictors for positive ALNs. Three prediction models were then developed: model A (conventional US features), model B (CEUS features), and model C (model A plus B). Model C yielded the highest area under the curve (AUC) of 0.82 [95% confidence interval (CI), 0.75-0.88] compared with model A (AUC 0.74; 95% CI, 0.68-0.81; P = 0.008) and model B (AUC 0.72; 95% CI, 0.65-0.80; P < 0.001) as per the DeLong test. CONCLUSION: CEUS, as a non-invasive examination technique, can be used to predict ALN metastasis. Combining conventional US and CEUS may produce favorable predictive accuracy for positive ALNs in BI-RADS category 4 breast cancer.

Added value of contrast-enhanced ultrasound to conventional ultrasound for characterization of indeterminate soft-tissue tumors.

OBJECTIVE: To assess the added value of contrast-enhanced ultrasound (CEUS) to conventional ultrasound in differentiating benign soft-tissue tumors from malignant ones. METHODS: 197 soft-tissue tumors underwent ultrasound examination with confirmed histopathology were retrospectively evaluated. The radiologists classified all the tumors as benign, malignant, or indeterminate according to ultrasound features. The indeterminate tumors underwent CEUS were reviewed afterwards for malignancy identification by using individual and combined CEUS features. RESULTS: Ultrasound analysis classified 62 soft-tissue tumors as benign, 111 tumors as indeterminate and 24 tumors as malignant. There 104 indeterminate tumors were subject to CEUS. Three CEUS features including enlargement of enhancement area, infiltrative enhancement boundary, and intratumoral arrival time difference were significantly associated with the tumor nature in both univariable and multivariable analysis for the indeterminate tumors (all p < 0.05). When at least one out of the three discriminant CEUS features were present, the best sensitivity of 100% for malignancy identification was obtained with the specificity of 66.7% and the AUC of 0.833. When at least two of the three discriminant CEUS features were present, the best area under the receiver operating characteristic curve (AUC) of 0.924 for malignancy identification was obtained. The combination of at least two discriminant CEUS features showed much better diagnostic performance than the optimal combination of ultrasound features in terms of AUC (0.924 vs 0.608, p < 0.0001), sensitivity (94.0% vs 42.0%, p < 0.0001), and specificity (90.7% vs 79.6%, p = 0.210) for the indeterminate tumors. CONCLUSION: The combination CEUS features of enlargement of enhancement area, infiltrative enhancement boundary and intratumoral arrival time difference are valuable to improve the discriminating performance for indeterminate soft-tissue tumors on conventional ultrasound. ADVANCES IN KNOWLEDGE: The combination of peritumoral and arrival-time CEUS features can improve the discriminating performance for indeterminate soft-tissue tumors on conventional ultrasound.

The association between vitamin D levels and heart rate variability in patients with type 2 diabetes mellitus.

To assess the association between serum vitamin D levels and heart rate variability in patients with type 2 diabetes mellitus (T2DM). This study included 469 patients who were retrospective assessed for eligibility from Changzhou Second People's Hospital, Affiliated Nanjing Medical University, between March 2013 and June 2020. A total of 191 T2DM patients were recruited and divided into 3 groups. A total of 191 patients were recruited. A significant difference was noted among groups for HbA1c (P < .001), serum uric acid (P = .048), and urea nitrogen (P = .043). The Vitamin D level in deficiency, insufficiency, and sufficient was 23.17, 38.89, and 63.01 nmol/L, respectively. The insufficient group had lower levels of percentage of normal-to-normal intervals differing by more than 50 milliseconds, and the square root of the mean of the squares of the differences between adjacent normal-to-normal R peak-to-R-peak time intervals than the sufficient vitamin D group. Furthermore, patients in deficiency and insufficiency group were associated with high level of low frequency power/high frequency power as compared with sufficient vitamin D group. Finally, serum 25-hydroxyvitamin D (25(OH)D) levels were positively correlated with rMSSD (P = .002). This study found that low serum 25(OH)D levels were associated with reduced heart rate variability parameters in patients with T2DM.

The contribution of type 2 diabetes mellitus to hypothalamic inflammation and depressive disorders in young patients with obesity.

Background: To explore the contribution of type 2 diabetes mellitus (T2DM) to hypothalamic inflammation and depressive disorders in young patients with obesity. Methods: According to the diagnostic criteria for T2DM, all of patients with obesity were divided into the diabetic and the non-diabetic groups. The severity of depressive disorders was assessed by self-rating depression scale (SDS). The signal intensity (SI) ratio of the T2-weighted phase of the superior hypothalamus/amygdala (H/A) was measured using a quantitative magnetic resonance imaging (MRI) technique to evaluate hypothalamic inflammation. Univariate and multivariate logistic regression analysis was used to find the influencing factors of depressive disorder. The prediction equation's sensitivity and specificity for the depressive disorder were calculated based on the receiver operating characteristic (ROC) curve. Results: In young patients with obesity and diabetes, the incidence of depression is 79.49%, which was much higher than that in patients without diabetes (P<0.001). The SI of the left H/A in young patients with obesity and diabetes is significantly higher than that in non-diabetic patients (P<0.001). The relative risks of depression are fasting blood glucose (FBG) (OR 1.60; CI: 1.26-2.05), HbA1c (OR 1.94; CI: 1.40-2.68) and triglycerides (OR 1.40; CI: 1.03-1.90). Only FBG enters the predictive equation for depressive disorder, with a 52.8% sensitivity and 84.5% specificity. Conclusions: In young diabetic patients with obesity, the incidence of depressive disorder is high, a mechanism possibly related to the left hypothalamus inflammation. Elevated FBG can be an independent predictor of depressive disorder in young patients with obesity.

Management of Sonographically Suspicious Thyroid Nodules 1 cm or Smaller and Candidacy for Active Surveillance: Experience of a Tertiary Center in China.

OBJECTIVE: Our objective was to investigate the management of patients with asymptomatic suspicious thyroid nodules ≤1 cm. METHODS: We retrospectively reviewed medical records of patients with sonographically suspicious thyroid nodules ≤1 cm and without distant metastases, suspicious lymph node metastasis (LNM), or extrathyroidal extension (ETE). RESULTS: Of the 386 enrolled patients, 174 (45.1%) had immediate surgery (IS), while 212 (54.9%) underwent active surveillance (AS). In the IS group, 166 (95.4%) patients were confirmed as having papillary thyroid microcarcinoma. LNM and ETE were observed in 24.7% and 2.4% cases, respectively. In the AS group, nodule size increased by ≥3 mm in 11 (5.2%) patients and 39 (18.4%) had a >50% increase in nodule volume after a median follow-up of 12 months. Nodules with smaller volume at diagnosis were more likely to increase in volume later. Newly suspicious LNM was detected in 23 (10.8%) patients. Delayed surgery (DS) was performed in 101 patients, with 27 showing disease progression. ETE and LNM were detected in 3% and 36%, respectively, of patients with papillary thyroid microcarcinoma. Compared with IS, tumors in the DS group more frequently showed lateral LNM and capsular invasion (P < .05). No patient had recurrence or died of thyroid cancer during postoperative follow-up (median 26 [4-60] months). CONCLUSIONS: IS or DS of patients with asymptomatic suspicious thyroid nodules ≤1 cm was relatively high in China. The inertia of low-risk nodules and the effectiveness of DS for those that progressed make AS a feasible strategy.

Combining the Ultrasound Features of Primary Tumor and Axillary Lymph Nodes Can Reduce False-Negative Rate during the Prediction of High Axillary Node Burden in BI-RADS Category 4 or 5 Breast Cancer Lesions.

The purpose of this study was to determine whether incorporation of the ultrasound (US) features of the primary tumor and axillary lymph node (ALN) could improve the prediction of high axillary nodal burden (HNB) and, thus, avoid unnecessary sentinel lymph node biopsy (SLNB). A total of 347 patients with Breast Imaging Reporting and Data System US category 4 or 5 breast cancer lesions were included. Their pre-operative US features and post-operative pathologic results were collected. The patients were then divided into the following groups based on surgical histology: limited nodal burden (LNB: 0-2 LNs involved) and heavy nodal burden (HNB: ≥3 metastatic LNs). Univariate and multivariate logistic regression analyses were conducted to determine the most valuable variables for HNB prediction. Receiver operating characteristic curves were obtained to assess their values. We found that a non-circumscribed margin, cortical thickness (≥3 mm) and number (≥3) of suspicious ALNs are indicators for HNB prediction. The false-negative rate (FNR) in model 1 (cortical thickness + number of suspicious ALNs) was 15.5% versus 3.4% in model 2 (non-circumscribed margin + cortical thickness + number of suspicious ALNs). Our results indicate that combining the US features of the primary tumor and ALNs can reduce the FNR during HNB prediction.

[Effect of electroacupuncture on tissue elasticity and expression of muscular MyoD and myogenin in rats with acute gastrocnemius contusion].

OBJECTIVE: To observe the effect of electroacupuncture (EA) at "Ashi" acupoint and "Kunlun" (BL60) on elastic modulus, histopathological changes and expression of myogenic regulatory factors in gastrocnemius(GM) contusion rats, so as to explore the therapeutic effect of local acupoint selection and acupoint selection along channel. METHODS: Male SD rats were randomly divided into blank control (n＝5), model (n＝15), Ashi-point (n＝15) and BL60 (n＝15) groups. The acute GM contusion model was established by striking (free falling) the GM with a homemade hitter. EA (0.5 to 1.0 mA, 2 Hz/10 Hz) was applied to Ashi-point (local focus) and BL60 for 30 min 24 h after muscle injury. The elasticity maximum (Emax) of gastrocnemius muscle was measured by using an ultrasonic device. Histopathological changes were observed after H．E. stain, and the number of Myogenic differentiation(MyoD)- and Myogenin (MyoG)-positive cells was detected by using immunohistochemistry. RESULTS: After mdeling, the Emax value of GM was significantly increased from the 3rd h to 7th day in comparison with pre- injury of muscle (P<0.05), and was markedly increased on the 3rd day and obviously lower on day 7 in the Ashi-point group than in the model group (P<0.05). The numbers of MyoD- and MyoG-positive cells of GM were significantly increased on day 7 in the model group than in the blank control group (P<0.05), and both further increased in Ashi-point on day 3 and 5, and MyoG-positive cells further increased in BL60 group on day 5 and in Ashi-point group on day 7 relevant to the model group(P<0.05). The therapeutic effect of EA-Ashi-point was apparently superior to that of BL60 in up-regulating Emax on day 3 and in up-regulating the number of MyoD-positive cells on day 3 and 5 (P<0.05). H．E. stain showed disordered arrangement of muscle fibers, infiltration of inflammatory cells, increase of intercellular space, and edema on day 3 after modeling (which was milder in the Ashi-point group); and gradual fusion and thickening of new born muscle fibers with obvious connective tissue hyperplasia converged to the lesioned region on day 7 in the model group (convergence of new born muscle cells to the lesion region in both EA groups, and more complete tissues in the Ashi-point group). CONCLUSION: EA of Ashi-point and BL60 can up-regulate the expression of myogenic regulatory factors MyoD and MyoG of GM tissue in GM contusion rats, which may contribute to its function in promoting recovery of muscle elasticity. The role of EA-Ashi-point is superior to that of EA-BL60.

Risk Factors of Ketosis in Obese Ketosis-Prone Diabetic Patients: A Case-Control Study.

INTRODUCTION: Different types of ketosis-prone obese diabetic patients are seen in the clinic. At present, the mechanism responsible for ketosis onset in these patients remains unclear, and we do not know how these patients should be optimally treated to prevent recurrent ketosis. Therefore, this study aims to investigate risk factors of ketosis in obese ketosis-prone diabetic (OB-KPD) patients. METHODS: In an observational case-control study, primary OB-KPD patients [body mass index (BMI) ≥ 28 kg/m2] were selected as the study group (OB-KPD group), and primary obese type 2 diabetes patients served as the control group (OB-T2DM group). Clinical diagnostic assessments of fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), blood lipid, area under curve of serum C-peptide (AUCC-P) after steamed bread meal, insulin sensitivity index (ISI), ß-hydroxybutyric acid (ß-HB) and free fatty acid (FFA) vlaues of the subjects were collected. Subjects in the OB-KPD group were followed up for 1 year to determine the likelihood of insulin therapy cessation and whether ketosis recurred by assessing clinical chemistry parameters at 1-year follow-up. RESULTS: Seventy-five subjects were screened, of which 15 were not included in the study for several identified clinical reasons. On enrollment, the OB-KPD group displayed significantly higher FPG, HbA1c and FFA levels than the OB-T2DM group (p < 0.01), while AUCC-P and ISI values were significantly lower than in the OB-T2DM group (p < 0.01 and p = 0.03). Statistical analysis showed that increases in ß-HB in the OB-KPD group were associated with increased blood glucose and FFA and decreased AUCC-P and ISI values. Furthermore, decreases in AUCC-P were closely associated with increased blood glucose values. CONCLUSION: The occurrence of ketosis in ketosis-prone obese diabetic patients may be related to glucose and lipid metabolism disorders, increased insulin resistance and decreased ß-cell secretory functions. TRIAL REGISTRATION: This work was registered at the Chinese Clinical Trial Registry with trial registration identifier no. ChiCTR1900025909.

Comparison of Diagnostic Efficacy Between Contrast-Enhanced Ultrasound and DCE-MRI for Mass- and Non-Mass-Like Enhancement Types in Breast Lesions.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) can provide angiogenesis information about breast lesions; however, its diagnostic performance in comparison with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has not been systematically investigated. This study aimed to evaluate the diagnostic efficacy of CEUS and DCE-MRI in mass-like and non-mass-like enhancement types of breast lesions. MATERIAL AND METHODS: A retrospective study was conducted on 252 patients with breast lesions who underwent CEUS and DCE-MRI before surgery between January 2016 and February 2020. Histopathological results were used as reference standards. All patients were classified into mass-like and non-mass-like enhancement lesion groups. The mass-like lesion group was further divided into three categories according to different sizes (group 1: <10 mm, group 2: 10-20 mm, and group 3: >20 mm). Sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic curve were analyzed to assess the diagnostic performance of these two modalities. RESULTS: For mass-like breast lesions, DCE-MRI (Az=0.981) manifested better diagnostic performance than CEUS (Az=0.940) in medium-sized (10-20 mm) tumors (Z=2.018, P=0.043), but both had similar diagnostic performance in smaller (<10 mm) and larger (>20 mm) tumors (P=0.717, P=0.394). For non-mass-like enhancement lesions, CEUS and DCE-MRI showed no significant difference (Z=1.590, P=0.119) and revealed good diagnostic performance (Az=0.859, Az=0.947) in differentiating the two groups. CONCLUSION: For mass-like breast lesions, DCE-MRI showed better diagnostic performance than CEUS in differentiating benign and malignant tumors of medium-sizes (10-20mm) but not of smaller (<10mm) and larger (>20 mm) sizes. For non-mass-like lesions, both modalities showed similar diagnostic performance.

[Association between obesity and sleep disorders among children in Lanzhou, China].

OBJECTIVE: To investigate the prevalence of obesity and sleep disorders and the association between them among children in Lanzhou, China. METHODS: The stratified cluster random sampling method was used to select 3 283 primary school students in four districts of Lanzhou of Gansu province. Physical examination and sleep questionnaire were conducted to screen out the children who met the criteria for sleep disorders or obesity as subjects. Among the 3 283 children, 200 healthy children without sleep disorders or obesity were enrolled as the control group. RESULTS: The prevalence rate of obesity among the 3 283 children was 5.76% (189/3 283). Among these 189 obese children, 80 (42.3%) had sleep disorders. The prevalence rate of sleep disorders was 16.24% (533/3 283), and the prevalence rate of obesity among the children with sleep disorders was 24.6% (131/533). Snoring was the most common sleep disorder in obese children. The prevalence rate of obstructive sleep apnea hypopnea syndrome was 45% (36/80) among obese children with sleep disorders. The obese children had a significantly higher prevalence rate of sleep disorders than the children with normal body weight [42.3% (80/189) vs 20% (40/200), P<0.01]. CONCLUSIONS: There is a close relationship between obesity and sleep disorders in children in Lanzhou, China.

Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer.

PURPOSE: To establish a radiomics nomogram integrating clinical factors and radiomics features from ultrasound for the preoperative diagnosis axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (EIBC). MATERIALS AND METHODS: Between September 2016 and December 2018, four hundred twenty-six ultrasound manually segmented images of patients with EIBC were enrolled in our retrospective study, which were divided into a primary cohort (n = 300) and a validation cohort (n = 126). A radiomics signature was built with the least absolute shrinkage and selection operator (LASSO) algorithm in the primary cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on radiomics signature and clinical variables. The performance of nomogram was quantified with respect to discrimination and calibration. The radiomics model was further evaluated in the internal validation cohort. RESULTS: The radiomics signature, consisted of fourteen selected ALN-status-related features, achieved moderate prediction efficacy with an area under the curve (AUC) of 0.78 and 0.71 in the primary and validation cohorts respectively. The radiomics nomogram, comprising tumor size, US-reported LN status and radiomics signature, showed good calibration and favorite performance for ALN detection (AUC 0.84 and 0.81 in the primary and validation cohort). The decision curve which was demonstrated the radiomics nomogram displayed good clinical utility. CONCLUSION: The radiomics nomogram could hold promise as a non-invasive and reliable tool in predicting ALN metastasis and may facilitate to develop more effective preoperative decision-making.

Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination.

PURPOSE: To validate and compare diagnostic value of three newly-released Thyroid Imaging Reporting and Data Systems (TIRADS) for cancer risk determination. METHODS: Total 2031 patients with 2465 thyroid nodules were recruited for this study. Ultrasound (US) images were categorized based on three TIRADS editions established by Korean Society of Thyroid Radiology (KSThR), European Thyroid Association (ETA) and American College of Radiology (ACR). ROC curves were established to compare diagnostic value. RESULTS: Total 1460 benign and 1005 malignant nodules were enrolled. The malignancy rates of each category in KSThR-TIRADS were 2.8%, 5.1%, 33.7% and 79.6%, respectively. For European-TIRADS, 0, 3.1, 22.8, and 73.5% of nodules categorized as 2 to 5 were malignant. Distribution of carcinomas among ACR-TIRADS categories was 0%, 2.3%, 7.5%, 40.1% and 81.4%, respectively. In terms of diagnostic value, KSThR-TIRADS had highest AUC (0.855) and specificity (87.4%), while lowest (71.4%) sensitivity. ACR-TIRADS showed best sensitivity (96.6%) with lowest specificity (52.9%) and the AUC (0.846) was slightly lower than KSThR-TIRADS. Total 56.1, 45.4, and 37.4% fine-needle aspiration biopsy (FNAB) were recommended by KSThR, ETA and ACR, revealing 42.8%, 44.5% and 53.6% malignant lesions, respectively. The rate of unnecessary FNAB was lowest with the ACR (17.3%), followed by ETA (25.2%) and KSThR (32.1%). CONCLUSION: All these US models showed great value in predicting thyroid malignancy. Among them, KSThR-TIRADS showed the most effective diagnostic performance in specificity, while ACR-TIRADS yielded best sensitivity. As for FNAB criteria, ACR-TIRADS showed the lowest rate of unnecessary FNAB and highest rate of malignancy in FNAB.

Combination of Maximum Shear Wave Elasticity Modulus and TIRADS Improves the Diagnostic Specificity in Characterizing Thyroid Nodules: A Retrospective Study.

OBJECTIVES: The present study is aimed at evaluating the diagnostic value of combining shear wave elastography (SWE) parameters and the thyroid imaging reporting and data system (TIRADS) for differentiating between benign and malignant thyroid nodules. METHODS: Patients who underwent conventional ultrasonography (US) and SWE before surgery were enrolled in the current study. Each nodule was given a TIRADS risk score. The effectiveness of the SWE parameters was assessed by odds ratios (ORs). The SWE scoring risk stratification was proposed beyond 95% probability, and the desired values were obtained according to the log-normal distribution. The area under the receiver-operating characteristic (AUC) was used to compare the diagnostic performance between TIRADS-alone and TIRADS + SWE. RESULTS: A total of 262 patients with 298 thyroid nodules were enrolled in our study. The pathological analyses were conducted on 121 benign and 177 malignant nodules. The AUC values for TIRADS-alone and TIRADS + SWE were 0.896 (accuracy 83.2%) and 0.917 (accuracy 84.2%), respectively. However, the TIRADS + SWE scores showed a higher specificity (88.4%) and positive predictive value (91.2%) as compared with the TIRADS-alone of 73.6% and 83.2%, respectively. CONCLUSIONS: Combining SWE and TIRADS improves the specificity of TIRADS-alone in differentiating between benign and malignant thyroid nodules.

Liver X Receptor Gene Expression is Enhanced in Children with Obstructive Sleep Apnea-Hyperpnoea Syndrome and Cyclooxygenase-2 (COX-2) is Correlated with Severity of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS).

BACKGROUND Liver X receptor (LXR) is a nuclear receptor presenting in macrophages; it works indispensably in lipid metabolism control and also negatively regulates the expression of inflammatory genes in macrophages. There are many LXR-related studies in adults with metabolic syndrome but rare reports in obese children with obstructive sleep apnea-hypopnea syndrome (OSAHS). The aim of this study was to investigate the expression of LXR, cholesterol ester transfer protein (CETP), and cyclooxygenase-2 (COX-2) genes in obese children with OSAHS compared with obese children without OSAHS and non-obese children. MATERIAL AND METHODS Sleep monitoring was conducted in 80 obese children with sleep disorders. Fasting morning blood samples from the 80 obese children and 51 normal children were collected and separated, so that macrophages were obtained after culture. Fluorescence quantitative real-time PCR (RT-PCR) was used to detect expression levels of the LXR, CETP, and COX-2 genes. RESULTS LXR, COX-2, and CETP levels in the OSAHS group were higher than those in the other two groups (P<0.05), and the LXR levels in the group of obese children without OSAHS were higher than those in control group (P<0.05). COX-2 expression in the group with moderate to severe OSAHS was higher than that in the group with mild OSAHS (P<0.05). Meanwhile, there were no significant differences in the LXR and CETP levels between the moderate to severe OSAHS group and the mild OSAHS group (P>0.05). CONCLUSIONS LXR gene expression was significantly increased in obese children with OSAHS. The severity of OSAHS was positively correlated with COX-2 levels.

Thyroid nodule sizes influence the diagnostic performance of TIRADS and ultrasound patterns of 2015 ATA guidelines: a multicenter retrospective study.

To evaluate the impact of thyroid nodule sizes on the diagnostic performance of thyroid imaging reporting and data system (TIRADS) and ultrasound patterns of 2015 American Thyroid Association (ATA) guidelines. Total 734 patients with 962 thyroid nodules were recruited in this retrospective study. All nodules were divided into three groups according to the maximal diameter (d < 10 mm, d = 10-20 mm and d > 20 mm). The ultrasound images were categorized based on TIRADS and ATA ultrasound patterns, respectively. A total of 931 (96.8%) and 906 (94.2%) patterns met the criteria for TIRADS and ATA ultrasound patterns. The AUC (0.849) and sensitivity (85.3%) of TIRADS were highest in d = 10-20 mm group. However, ATA had highest AUC (0.839) and specificity (89.8%) in d > 20 mm group. ATA ultrasound patterns had higher specificity (P = 0.04), while TI-RADS had higher sensitivity (P = 0.02). In nodules d > 20 mm, the specificity of ATA patterns was higher than TIRADS (P = 0.003). Our results indicated that nodule sizes may influence the diagnostic performance of TIRADS and ATA ultrasound patterns. The ATA patterns may yield higher specificity than TIRADS, especially in nodules larger than 20 mm.