Value of High-Frequency Ultrasonography in the Qualitative and Semi-Quantitative Assessment of Immunoglobulin G4-Related Submandibular Sialadenitis.

OBJECTIVE: To assess the value of high-frequency ultrasonography in the evaluation of immunoglobulin G4-related submandibular sialadenitis (IgG4-SS). METHODS: Thirty-four submandibular glands in 17 patients with IgG4-SS were retrospectively enrolled, as well as 34 submandibular glands in 17 healthy control subjects. Qualitative ultrasonic features including submandibular gland size, border, echogenicity, and vascularity were reviewed. Two different scoring systems (0-16 and 0-48, respectively) were used for semi-quantitative analysis of imaging features. Comparison of both qualitative and semi-quantitative ultrasonic analysis were made between patients with IgG4-SS and healthy controls. Spearman correlation was used to explore relationships between variables. RESULTS: The submandibular glands with IgG4-SS presented with enlarged size, rough border, increased vascularity, and abnormal echogenicity (All P < .05). The most common echogenicity pattern for IgG-SS was diffuse hypoechoic foci pattern (44.1%), followed by superficial hypoechoic pattern (20.6%), tumor-like pattern (14.7%), and diffuse hypoechogenicity pattern (11.8%). Most IgG4-SS glands presented linear hyperechogenicity in parenchyma (91.2%). Based on both scoring system, scores of IgG4-SS were significantly higher than those of the controls (All P < .05). Association analysis of both scoring systems showed positive correlation of scores with vascularity in the gland parenchyma (All P < .05). CONCLUSION: The ultrasonic features of IgG4-SS comprise enlarged gland, rough border, increased vascularity, and abnormal echogenicity, which correlate with its pathological characteristics. The most common echogenicity pattern for IgG4-SS was diffuse hypoechoic foci pattern. Semi-quantitative analysis systems could be useful in the assessment of IgG4-SS. Ultrasound is a potential, valuable, and non-invasive tool for the diagnosis and evaluation of IgG4-SS.

Risk factors and the potential of nomogram for predicting hospital-acquired pressure injuries.

This 1:5 case-control study aimed to identify the risk factors of hospital-acquired pressure injuries (HAPIs) and to develop a mathematical model of nomogram for the risk prediction of HAPIs. Data for 370 patients with HAPIs and 1971 patients without HAPIs were extracted from the adverse events and the electronic medical systems. They were randomly divided into two sets: training (n = 1951) and validation (n = 390). Significant risk factors were identified by univariate and multivariate analyses in the training set, followed by a nomogram constructed. Age, independent movement, sensory perception and response, moisture, perfusion, use of medical devices, compulsive position, hypoalbuminaemia, an existing pressure injury or scarring from a previous pressure injury, and surgery sufferings were considered significant risk factors and were included to construct a nomogram. In both of the training and validation sets, the areas of 0.90 under the receiver operating characteristic curves showed excellent discrimination of the nomogram; calibration plots demonstrated a good consistency between the observed probability and the nomogram's prediction; decision curve analyses exhibited preferable net benefit along with the threshold probability in the nomogram. The excellent performance of the nomogram makes it a convenient and reliable tool for the risk prediction of HAPIs.

The CpG Dinucleotide Adjacent to a κB Site Affects NF-κB Function through Its Methylation.

NF-κB is an important transcription factor that plays critical roles in cell survival, proliferation, inflammation, and cancers. Although the majority of experimentally identified functional NF-κB binding sites (κB sites) match the consensus sequence, there are plenty of non-functional NF-κB consensus sequences in the genome. We analyzed the surrounding sequences of the known κB sites that perfectly match the GGGRNNYYCC consensus sequence and identified the nucleotide at the -1 position of κB sites as a key contributor to the binding of the κB sites by NF-κB. We demonstrated that a cytosine at the -1 position of a κB site (-1C) could be methylated, which thereafter impaired NF-κB binding and/or function. In addition, all -1C κB sites are located in CpG islands and are conserved during evolution only when they are within CpG islands. Interestingly, when there are multiple NF-κB binding possibilities, methylation of -1C might increase NF-κB binding. Our finding suggests that a single nucleotide at the -1 position of a κB site could be a critical factor in NF-κB functioning and could be exploited as an additional manner to regulate the expression of NF-κB target genes.

Adopting Quaternion Wavelet Transform to Fuse Multi-Modal Medical Images.

Medical image fusion plays an important role in clinical applications such as image-guided surgery, image-guided radiotherapy, noninvasive diagnosis, and treatment planning. In this paper, we propose a novel multi-modal medical image fusion method based on simplified pulse-coupled neural network and quaternion wavelet transform. The proposed fusion algorithm is capable of combining not only pairs of computed tomography (CT) and magnetic resonance (MR) images, but also pairs of CT and proton-density-weighted MR images, and multi-spectral MR images such as T1 and T2. Experiments on six pairs of multi-modal medical images are conducted to compare the proposed scheme with four existing methods. The performances of various methods are investigated using mutual information metrics and comprehensive fusion performance characterization (total fusion performance, fusion loss, and modified fusion artifacts criteria). The experimental results show that the proposed algorithm not only extracts more important visual information from source images, but also effectively avoids introducing artificial information into fused medical images. It significantly outperforms existing medical image fusion methods in terms of subjective performance and objective evaluation metrics.

Ultrasonic features of automated breast volume scanner (ABVS) and handheld ultrasound (HHUS) combined with molecular biomarkers in predicting axillary lymph node metastasis of clinical T1-T2 breast cancer.

Background: In the post-American College of Surgeons Oncology Group Z0011 trial era, clinicians are attempting to preoperatively evaluate axillary lymph node (ALN) status using ultrasound. However, the value of preoperative ultrasound examination remains uncertain. The study aimed to investigate the ultrasonic features of automated breast volume scanner (ABVS) and handheld ultrasound (HHUS), in combination with molecular biomarkers, to predict the risk of ALN metastasis (ALNM) in clinical T1-T2 breast cancer. Methods: A retrospective case-control analysis was conducted on 168 patients with clinical T1-T2 breast cancer at Peking University First Hospital between January 2013 and August 2021. Preoperative ABVS and HHUS examinations were performed. According to the pathology results of the ALN, patients were divided into metastatic and nonmetastatic groups. Logistic regression analyses were used to analyze the ultrasonic characteristics of ABVS and HHUS on clinical T1-T2 breast cancer, and molecular biomarkers were incorporated to predict the risk of ALNM. Results: Of the 168 patients, 88 (52.4%) had ipsilateral ALNM while 80 (47.6%) had no ipsilateral ALNM. The univariate analysis showed that shorter tumor-skin distance (P=0.011), the Adler blood flow grade of II-III (P=0.014), and larger tumor size on ABVS (P<0.001) were associated with ALNM. The multivariate logistic analysis showed that these three risk factors, including the tumor-skin distance [odds ratio (OR) =0.279; P=0.024], the Adler blood flow grade (OR =2.164; P=0.046), and the tumor size on ABVS (OR =1.033; P=0.002), were independent predictive parameters. Conclusions: The tumor-skin distance, tumor size on ABVS, and Adler blood flow grade have diagnostic value for ALNM in clinical T1-T2 breast cancer.

Ultrasound and clinical factors predicting central lymph node metastases in patients with unilateral multifocal papillary thyroid carcinoma.

OBJECTIVE: This retrospective study involving a large dataset of unilateral multifocal papillary thyroid carcinoma (UM-PTC) sought to identify factors that predict central lymph node metastases (CLNM) in patients. METHODS: We identified a cohort of 158 patients who underwent cervical ultrasonography followed by UM-PTC diagnosis based on postoperative pathology. The relationship between CLNM and UM-PTC clinical ultrasound features was evaluated using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to determine the ability of total tumor diameter (TTD) to predict CLNM. RESULTS: Among the 158 UM-PTC patients, the incidence of CLNM was 29.7% (47/158). Univariate and multivariate analyses revealed that a number of similarity of sonographic features (NSSF) ≥4 (odds ratio [OR] = 11.335, 95% confidence interval [CI]: 3.95-32.50, p = 0.000), microcalcifications (OR = 3.54, 95% CI: 1.30-9.70, p = 0.014), a TTD of ≥2 cm (OR = 4.48, 95% CI: 1.62-12.34, p = 0.004), number of nodules ≥3 (OR = 13.17, 95% CI: 3.24-53.52, p = 0.000), and Lateral cervical lymph node metastasis (LLNM) (OR = 5.57, 95% CI: 1.59-19.48, p = 0.007) were independently associated with CLNM in UM-PTC. ROC curve analysis revealed that the TTD cut-off of 1.795 cm had a sensitivity of 0.723 and a specificity of 0.676 for predicting CLNM. CONCLUSIONS: Patients with UM-PTC are at high risk of CLNM. NSSF ≥4, microcalcifications, TTD of ≥2 cm, LLNM, and a number of nodules ≥3 were independently associated with CLNM. Our data show that ultrasound may guide surgical decisions in the treatment of UM-PTC.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India.

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Modular Approach to Creating Functionalized Surface Arrays of Molecular Qubits.

The quest for developing quantum technologies is driven by the promise of exponentially faster computations, ultrahigh performance sensing, and achieving thorough understanding of many-particle quantum systems. Molecular spins are excellent qubit candidates because they feature long coherence times, are widely tunable through chemical synthesis, and can be interfaced with other quantum platforms such as superconducting qubits. A present challenge for molecular spin qubits is their integration in quantum devices, which requires arranging them in thin films or monolayers on surfaces. However, clear proof of the survival of quantum properties of molecular qubits on surfaces has not been reported so far. Furthermore, little is known about the change in spin dynamics of molecular qubits going from the bulk to monolayers. Here, a versatile bottom-up method is reported to arrange molecular qubits as functional groups of self-assembled monolayers (SAMs) on surfaces, combining molecular self-organization and click chemistry. Coherence times of up to 13 µs demonstrate that qubit properties are maintained or even enhanced in the monolayer.

Diagnostic Value of Ultrasound Elastography in the Differentiation of Breast Invasive Ductal Carcinoma and Ductal Carcinoma In situ.

BACKGROUND: Ultrasound elastography (US-E) has been shown superior to the conventional US in diagnosing benign and malignant breast lesions. In contrast, the role of US-E in the differentiation of breast invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) has been poorly described. OBJECTIVE: This study was designed to examine the diagnostic value of US-E in the differentiation of IDC and DCIS. METHODS: Medical records of all patients who underwent preoperative US-E evaluation and were diagnosed with IDC or DCIS at our hospital from April-December 2019 were retrieved and analyzed. Those who had prior surgical treatment, chemotherapy or radiotherapy were excluded. RESULTS: Twenty women with DCIS and 111 women with IDC were included in this study. There were no significant differences in age, maximum lesion diameter and tumor volume between the two groups. While shear wave velocity (SWV) inside the lesion and in the surrounding tissue, strain ratio and tumor area ratio were not substantially different between the two groups, SWV at the edge of the lesion was significantly higher in IDC cases, which had an AUC value of 0.66 with a sensitivity of 65.8% and a specificity of 60.0% for the differential diagnosis of IDC and DCIS. CONCLUSION: Edge SWV is significantly higher in IDC than that in DCIS, which had a moderate diagnostic value for the differentiation of IDC and DCIS, similar to the performance of diffusion-weighted magnetic resonance imaging as reported in the literature. In terms of cost-effectiveness, US-E could be very useful while waiting for further evaluations to determine whether US-E combined with other diagnostic modalities improves the diagnostic performance.

Influence of physicians' seniority on efficacy of silver needle therapy for low back fasciitis: A prospective, cohort study.

BACKGROUND: Physicians' seniority has always been the focus of patients. Silver needle therapy (SNT) has been applied for more than 60 years. It is similar to moxibustion and has a good therapeutic effect on soft tissue pain. This study aimed to determine the influence of physicians' seniority on the efficacy of SNT for patients with low back fasciitis. METHODS: This was a prospective cohort study at the Affiliated Hospital of Qingdao University. Patients diagnosed with low back fasciitis were split into junior physician (JP) and senior physician (SP) groups (n = 30) based on the seniority of the physician. The numerical rating scale (NRS) was administered during the SNT, and operation time was recorded. The NRS, Oswestry Disability Index (ODI), and Short-Form 12 of quality of life (SF-12) scores at 1, 2, 6, and 12 months after the treatment and autonomic nervous system (ANS) activity were also observed. RESULTS: Compared with the SP group, the NRS score during the SNT (5.20 ±â€…0.71 vs 2.53 ±â€…0.94) and operation time (11.7 ±â€…1.6 minutes vs 6.8 ±â€…1.1 minute) were higher in the JP group (P < .05). The NRS, ODI score, SF-12 score, and ANS activity after treatment were not significantly different between SP and JP groups. Additionally, in the multivariate linear regression analysis model, the physicians' seniority was an independent factor affecting the NRS score during the SNT and operation time (P < .05). CONCLUSION: SNT could attenuate the pain of patients with low back fasciitis in the short and long term without severe complications. The physicians' seniority did not influence the efficacy of SNT, but the JP group showed an increased operation time and a higher degree of pain during the operation.

Comparison of the diagnostic performance and clinical role of different ultrasound-based thyroid malignancy risk stratification systems for medullary thyroid carcinoma.

Background: This study sought to investigate the applicability of different ultrasound (US) thyroid risk stratification systems in diagnosing medullary thyroid carcinoma (MTC) and determining the need for biopsy. Methods: In total, 34 MTC nodules, 54 papillary thyroid carcinoma (PTC) nodules, and 62 benign thyroid nodules were examined in this study. All the diagnoses were histopathologically confirmed postoperatively. All the thyroid nodule sonographic features were recorded and categorized by 2 independent reviewers according to the Thyroid Imaging Reporting and Data System (TIRADS) of the American College of Radiology (ACR), the American Thyroid Association (ATA) guidelines, the European Thyroid Association (EU) TIRADS, the Kwak-TIRADS, and the Chinese TIRADS (C-TIRADS). The sonographic differences and risk stratifications of the MTCs, PTCs, and benign thyroid nodules were analyzed. The diagnostic performance and recommended biopsy rates for each classification system were evaluated. Results: The risk stratifications of MTCs were all higher than the benign thyroid nodules (P<0.01) and lower than PTCs (P<0.01) with each classification system. Hypoechogenicity and malignant marginal features were independent risk factors for identifying malignant thyroid nodules, and the area under the receiver operating characteristic curve (AUC) for identifying MTCs was lower than that for identifying PTCs (0.873 vs. 0.954, respectively). The AUCs, sensitivity, specificity, positive predictive values, negative predictive values, and accuracy values of the 5 systems for MTC were all lower than those for PTC. The best cut-off values for diagnosing MTC were TIRADS (TR) 4 in the ACR-TIRADS, intermediate suspicion in the ATA guidelines, TR 4 in EU-TIRADS, and TR 4b in both the Kwak-TIRADS and the C-TIRADS. The Kwak-TIRADS had the highest recommended biopsy rate for MTCs (97.1%), followed by the ATA guidelines, the EU-TIRADS (88.2%), the C-TIRADS (85.3%), and the ACR-TIRADS (79.4%). Conclusions: The US-based thyroid malignancy risk stratification systems analyzed in this study were able to satisfactorily identify MTC and recommend biopsy, but the diagnostic performance of these systems for MTC was not as good as that for PTC.

Efficient N-Type Organic Electrochemical Transistors and Field-Effect Transistors Based on PNDI-Copolymers Bearing Fluorinated Selenophene-Vinylene-Selenophenes.

n-Type organic electrochemical transistors (OECTs) and organic field-effect transistors (OFETs) are less developed than their p-type counterparts. Herein, polynaphthalenediimide (PNDI)-based copolymers bearing novel fluorinated selenophene-vinylene-selenophene (FSVS) units as efficient materials for both n-type OECTs and n-type OFETs are reported. The PNDI polymers with oligo(ethylene glycol) (EG7) side chains P(NDIEG7-FSVS), affords a high µC* of > 0.2 F cm-1  V-1  s-1 , outperforming the benchmark n-type Pg4NDI-T2 and Pg4NDI-gT2 by two orders of magnitude. The deep-lying LUMO of -4.63 eV endows P(NDIEG7-FSVS) with an ultra-low threshold voltage of 0.16 V. Moreover, the conjugated polymer with octyldodecyl (OD) side chains P(NDIOD-FSVS) exhibits a surprisingly low energetic disorder with an Urbach energy of 36 meV and an ultra-low activation energy of 39 meV, resulting in high electron mobility of up to 0.32 cm2  V-1  s-1 in n-type OFETs. These results demonstrate the great potential for simultaneously achieving a lower LUMO and a tighter intermolecular packing for the next-generation efficient n-type organic electronics.

Effects of sampling strategy in rivers on load estimation for Nitrate-Nitrogen and total Phosphorus in a lowland agricultural area.

The transport of nutrients into water bodies is one of the main causes of water eutrophication. It is therefore important to estimate the loads of nutrients. Discharge and nutrient concentrations are the fundamental elements to estimate the loads of nutrients, the latter can be affected by sampling strategies. As conducting sampling campaign and laboratory analysis are both expensive, it is necessary to find the best effective sampling strategy. The aim of this paper is to show how autocorrelation and standard statistical methods can be used to test the effects of different sampling strategies on the nutrient load estimation and to find the optimal sampling strategy. The data set in this study is from the 50 km² Kielstau catchment, a UNESCO demo site for ecohydrology in Northern Germany and consists of 14 years daily values of climate, hydrology, and water quality from 2006 to 2019. We calculated the autocorrelation (AC) of discharge (Q), precipitation, Nitrate-Nitrogen (NO3-N) and total Phosphorus (Ptot). Then we tested the effects of sampling intervals from 7 to 56 days (1-8 weeks) on the nutrient loads. Our results showed a high AC of Q and NO3-N for a long period, but the AC of Ptot and precipitation decreased very fast. An increase of the sampling interval (less frequent) increased the error of estimating the concentrations and loads. Consequently, we recommend that (1) the optimal sampling strategy for nutrient load estimation in an agriculture-dominant catchment should be continuously monitoring discharge combined with periodic grabbed samples; (2) the sampling frequency for NO3-N is suggested to be monthly (every 28 days) and for Ptot weekly (every 7 days). The information will help those tasked with catchment monitoring to design appropriate sampling strategy to ensure adequate data for nutrients load estimation in lowland rivers.

CNNG: A Convolutional Neural Networks With Gated Recurrent Units for Autism Spectrum Disorder Classification.

As a neurodevelopmental disorder, autism spectrum disorder (ASD) severely affects the living conditions of patients and their families. Early diagnosis of ASD can enable the disease to be effectively intervened in the early stage of development. In this paper, we present an ASD classification network defined as CNNG by combining of convolutional neural network (CNN) and gate recurrent unit (GRU). First, CNNG extracts the 3D spatial features of functional magnetic resonance imaging (fMRI) data by using the convolutional layer of the 3D CNN. Second, CNNG extracts the temporal features by using the GRU and finally classifies them by using the Sigmoid function. The performance of CNNG was validated on the international public data-autism brain imaging data exchange (ABIDE) dataset. According to the experiments, CNNG can be highly effective in extracting the spatio-temporal features of fMRI and achieving a classification accuracy of 72.46%.

Using integrated models to analyze and predict the variance of diatom community composition in an agricultural area.

With the growing demand of assessing the ecological status, there is the need to fully understand the relationship between the planktic diversity and the environmental factors. Species richness and Shannon index have been widely used to describe the biodiversity of a community. Besides, we introduced the first ordination value from non-metric multidimensional scaling (NMDS) as a new index to represent the community similarity variance. In this study, we hypothesized that the variation of diatom community in rivers in an agricultural area was influenced by hydro-chemical variables. We collected daily mixed water samples using ISCO auto water samplers for diatoms and for water-chemistry analysis at the outlet of a lowland river for a consecutive year. An integrated modeling was adopted including random forest (RF) to decide the importance of the environmental factors influencing diatoms, generalized linear models (GLMs) combined with 10-folder cross validation to analyze and predict the diatom variation. The hierarchical analysis highlighted antecedent precipitation index (API) as the controlling hydrological variable while water temperature, Si2+ and PO4-P as the main chemical controlling factors in our study area. The generalized linear models performed better prediction for Shannon index (R2 = 0.44) and NMDS (R2 = 0.51) than diatom abundance (R2 = 0.25) and species richness (R2 = 0.25). Our findings confirmed that Shannon index and the NMDS as an index showed good performance in explaining the relationship between stream biota and its environmental factors and in predicting the diatom community development based on the hydro-chemical predictors. Our study showed and highlighted the important hydro-chemical factors in the agricultural rivers, which could contribute to the further understanding of predicting diatom community development and could be implemented in the future water management protocol.

Microbubble contrast agent SonoVue: An efficient medium for the preoperative lymphatic mapping of thyroid carcinoma.

Objective: To assess the value of microbubble contrast agent SonoVue in the thorough preoperative lymphatic mapping of patients with thyroid carcinoma, including the lymphatic drainage region, the detection of sentinel lymph node (SLN), and the diagnosis of lymph node metastasis (LNM). Materials and methods: 55 patients with 62 thyroid malignancies proved by surgical pathology (59 papillary thyroid carcinomas and three medullary thyroid carcinomas) who underwent preoperative lymphatic contrast-enhanced ultrasound (LCEUS) with microbubble contrast agent SonoVue were enrolled. All LNM were confirmed by pathology. The location of thyroid lesions, ultrasonic features of lymph nodes, lymphatic drainage region, and detection of SLN were assessed. The diagnostic performance (sensitivity, specificity, positive predictive value, negative predictive value and accuracy) of different parameters for the LNM diagnosis was calculated. Results: SonoVue effectively demonstrated the lymphatic drainage region for all enrolled thyroid carcinomas. The most common lymphatic drainage region for thyroid carcinomas was region VI (93.55%), followed by region III (62.90%), region IV (48.39%) and region II (4.84%). When divided by the lesion location, the most common lymphatic drainage regions for the nodule in isthmus, superior lobe and inferior lobe of the thyroid were region VI, region III, and region VI respectively. SLN was detected in 96.77% (60/62) of cases. The two cases without SLN demonstration had pathologically proven LNM. The most common sonographic sign of LNM was perfusion defect (54.17%). The diagnostic accuracy of SonoVue in central and lateral compartment LNM was 86.67% and 91.67%, respectively. Conclusion: Microbubble contrast agent SonoVue is a valuable imaging contrast medium for thorough preoperative lymphatic mapping in patients with thyroid carcinoma, including the lymphatic drainage region, the detection of SLN, and the diagnosis of LNM. LCEUS with SonoVue alone has limitations of false negatives when there is lymphatic vessel obstruction and may need to be combined with other ultrasound modalities.

The value of ultrasound elastography combined with multi-parameters in the diagnosis of BI-RADS 4 breast lesions.

BACKGROUND: Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%) in the global cancer statistics 2020. OBJECTIVE: To evaluate the diagnostic value of ultrasound elastography combined with multi-parameters in differentiating category 4 benign and malignant lesions in the breast imaging reporting and data system (BI-RADS). METHODS: This study retrospectively analyzed 206 patients (213 breast lesions) who visited the Department of Breast Surgery and underwent a breast core needle biopsy in the Department of Ultrasound in Peking University First hospital from April to December 2019. The shear wave velocity (SWV) values were collected at the following locations by virtual touch tissue imaging quantification (VTIQ): breast lesion interior, breast lesion margin, surrounding glands, and surrounding fat. Simultaneously, the strain ratio (SR) of breast lesions to glands and the area ratio (AR) of breast lesions were collected under strain elastography and a two-dimensional ultrasound mode. RESULTS: Univariate analysis found that the SWV value, measured by ultrasound elastography parameters, and the AR between the elasticity and the two-dimensional ultrasound breast lesions showed statistical differences when differentiating benign and malignant lesions (p< 0.05). Binary logistic regression analysis found that the SWV values of the lesion interior and the surrounding glands were statistically significant. The joint predictors were calculated and analyzed by Receiver Operating Characteristic (ROC), and it was found that the joint predictors and the SWV values of the lesion interior have great diagnostic value. The cut-off value, sensitivity and specificity of the joint predictor and the SWV value of the lesion interior were > 3.65, 88.35% and 76.36% and > 5.55 m/s, 79.61% and 82.73%, respectively. CONCLUSIONS: Ultrasound elastography combined with multi-parameters has good diagnostic value in differentiating BI-RADS 4 breast lesions.

Value of Contrast-Enhanced Ultrasound in the Preoperative Evaluation of Papillary Thyroid Carcinoma Invasiveness.

OBJECTIVE: To evaluate the diagnostic performance of preoperative contrast-enhanced ultrasound (CEUS) in the detection of extracapsular extension (ECE) and cervical lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) and the added value of CEUS in the evaluation of PTC invasiveness to conventional ultrasound (US). MATERIALS AND METHODS: A total of 62 patients were enrolled retrospectively, including 30 patients with invasive PTCs (Group A, ECE or LNM present) and 32 patients with non-invasive PTCs (Group B). All patients underwent US and CEUS examinations before surgery. US and CEUS features of PTCs and lymph nodes were compared between groups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of US, CEUS, and the combination of the two in the detection of ECE and LNM of PTCs were calculated. Logistic regression was used to analyze relationships between variables. RESULTS: The PTC size was larger in group A on both US and CEUS (P = 0.001, P = 0.003). More PTCs showed hyper-enhancement in group A (P = 0.013) than in group B. More PTCs had >25% contact between PTC and the thyroid capsule and discontinued capsule on US and CEUS (all P < 0.05) in group A than in group B. More absent hilum and calcification of lymph nodes were observed in group A (both P < 0.05) than in group B on US. More centripetal perfusion and enlarged lymph nodes were observed in group A (both P < 0.05) than in group B on CEUS. CEUS alone and US combined with CEUS manifested higher diagnostic accuracy (79.0%) than US alone (72.6%) in the detection of ECE. The combination of US and CEUS manifested the highest diagnostic accuracy (95.2%) than CEUS alone (90.3%) and US alone (82.2%) in the detection of LNM. Diagnoses of ECE and LNM by the combination of US and CEUS were independent risk factors for PTC invasiveness [odds ratio (OR) = 29.49 and 97.20, respectively; both P = 0.001]. CONCLUSION: CEUS or US combined with CEUS is recommended for the detection of PTC ECE, while the combination of US and CEUS is most recommended for LNM detection. CEUS plays an essential role in the preoperative evaluation of PTC invasiveness.

Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation.

Medical image fusion has an indispensable value in the medical field. Taking advantage of structure-preserving filter and deep learning, a structure preservation-based two-scale multimodal medical image fusion algorithm is proposed. First, we used a two-scale decomposition method to decompose source images into base layer components and detail layer components. Second, we adopted a fusion method based on the iterative joint bilateral filter to fuse the base layer components. Third, a convolutional neural network and local similarity of images are used to fuse the components of the detail layer. At the last, the final fused result is got by using two-scale image reconstruction. The contrast experiments display that our algorithm has better fusion results than the state-of-the-art medical image fusion algorithms.

[Short-time effects of inhalable particles and fine particles on children's lung function in a district in Beijing].

OBJECTIVE: To study short-term effects of PM10 (particulate matter of aerodynamic diameter <10 microm) and PM2.5 (particulate matter of aerodynamic diameter <2.5 microm) on children's lung function in one district in Beijing. METHODS: Two hundred and sixteen healthy students aged between 7 and 11 year-old were selected from two primary schools in Beijing in October 2008, and every subject was tested with eight lung function parameters. Levels of PM2.5 in the schoolyards were monitored. Temperature and relative humidity were also recorded. PM10 data was collected from the nearby monitoring sites. The association between children's lung function and PM10 and PM2.5 were analyzed by using ridge regression model. RESULTS: The decrements found in indicators reflecting large airway characteristics including slow vital capacity (SVC), forced vital capacity (FVC), forced expiratory volume in one second (FEV1.0), and in indicators reflecting small airway characteristics including forced expiratory flow between 25% and 75% of vital capacity (FEF25-75), forced expiratory flow after 25% of vital capacity has been expelled (FEF25), forced expiratory flow after 50% of vital capacity has been expelled (FEF50), were associated with accumulated 1-day lagged and 2-day lagged PM2.5 and PM10, while FVC and FEV1.0 decreased more significantly, and the declines of SVC, FVC and FEV1.0 in girls were slightly greater than that in boys. CONCLUSION: PM2.5 and PM10 had short-term adverse health effects on children's lung function. The effects on parameters reflecting large airway characteristics such as FVC and FEV1.0 were even more obvious. The large airways of girls might be more susceptible to ambient particulate matter.