lncRNA799/TBL1XR1/ZEB1 Axis Forms a Feedback Loop to Promote the Epithelial-Mesenchymal Transition of Cervical Cancer Cells.

Cervical cancer is a common malignancy among women worldwide. Long non-coding RNAs (lncRNAs) are frequently involved in the pathogenesis of cervical cancer. Therefore, the present study aimed to investigate the potentials of lncRNA799 in cervical cancer. mRNA and protein expression were detected by reverse transcription-quantitative polymerase chain reaction and Western blot analysis, respectively. Cellular functions were assessed using CCK-8, wound healing and transwell analysis. The binding potential of zinc finger E-box-binding homeobox 1 (ZEB1) on the promoter of lncRNA799 was predicted utilizing the JASPAR database, and was then verified by luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, the gene interactions were assessed using RNA immunoprecipitation and co-immunoprecipitation assays. The results demonstrated that lncRNA799 was upregulated in cervical cancer cells. However, lncRNA799 deficiency suppressed the proliferation and epithelial-mesenchymal transition of cervical cancer cells. Furthermore, lncRNA799 could interact with eukaryotic translation initiation factor 4A3 to maintain the mRNA stability of transducin (ß)-like 1 X-linked receptor 1 (TBL1XR1) and promote the interaction between ZEB1 and TBL1XR1. Additionally, the results showed that ZEB1 could transcriptionally activate lncRNA799. Taken together, the present study suggested that the lncRNA799/TBL1XR1/ZEB1 axis could form a positive feedback loop in cervical cancer and could be, therefore, considered as a potential therapeutic strategy for cervical cancer.

Multiparametric US for Identifying Metabolic Dysfunction-associated Steatohepatitis: A Prospective Multicenter Study.

Background Noninvasive evaluation of metabolic dysfunction-associated fatty liver disease (MAFLD) with multiparametric US is essential, but multicenter studies are lacking. Purpose To evaluate the ability of multiparametric US with attenuation imaging (ATI) and two-dimensional (2D) shear-wave elastography (SWE) for predicting metabolic dysfunction-associated steatohepatitis (MASH) in participants with MAFLD, regardless of hepatitis B virus infection status. Materials and Methods This prospective cross-sectional multicenter study of consecutive adults with MAFLD who underwent multiparametric US with ATI and 2D SWE, as well as liver biopsy, from September 2020 to June 2022 was conducted in 12 tertiary hospitals in China. Multivariable logistic regression was performed to assess risk factors associated with MASH. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate diagnostic performance in predicting MASH in training and validation groups (6:4 ratio of participants), and for a post hoc subgroup analysis of hepatitis B virus infection and diabetes. Results A total of 424 participants (median age, 47 years; IQR, 34-59 years; 244 male) were evaluated, including 332 participants (78%) with MASH and 92 (22%) without. Attenuation coefficient (AC) (odds ratio [OR], 3.32 [95% CI: 1.94, 5.71]; P < .001), alanine aminotransferase (ALT) level (OR, 4.42 [95% CI: 1.78, 10.94]; P = .001), and international normalized ratio (INR) (OR, 0.59 [95% CI: 0.37, 0.95]; P = .03) were independently associated with MASH. A combined model (AC, ALT, and INR) had AUCs of 0.85 (95% CI: 0.79, 0.91) and 0.77 (95% CI: 0.69, 0.85) for predicting MASH in the training and validation groups, respectively. AUC values for the subgroups with and without diabetes were 0.83 (95% CI: 0.72, 0.94) and 0.81 (95% CI: 0.75, 0.87) and for the subgroups with and without hepatitis B were 0.82 (95% CI: 0.74, 0.90) and 0.79 (95% CI: 0.71, 0.87), respectively. Conclusion A model combining AC, ALT level, and INR showed good discrimination ability for predicting MASH in participants with MAFLD. Clinical trial registration no. NCT04551716 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Reuter in this issue.

The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.

BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario. METHODS: In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology. RESULTS: According to the 2e diagnostic criteria, 1543 nodules were classified by the arbitration committee, and the benign and malignant nature of 753 nodules was determined by pathological examinations. Taking pathological results as the evaluation standard, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the AI systems were 0.826, 0.815, 0.821, and 0.821. For those cases where diagnosis by the Arbitration Committee were taken as the evaluation standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.946, 0.966, 0.964, and 0.956. Taking the global 2e diagnostic criteria as the gold standard, the sensitivity, specificity, accuracy, and AUC of the AI system were 0.868, 0.934, 0.917, and 0.901, respectively. Under different criteria, AI was comparable to the diagnostic performance of senior radiologists and outperformed junior radiologists (all P < 0.05). Furthermore, AI assistance significantly improved the performance of junior radiologists in the diagnosis of thyroid nodules, and their diagnostic performance was comparable to that of senior radiologists when pathological results were taken as the gold standard (all p > 0.05). CONCLUSIONS: The proposed 2e diagnostic criteria are consistent with real-world clinical evaluations and affirm the applicability of the AI system. Under the 2e criteria, the diagnostic performance of the AI system is comparable to that of senior radiologists and significantly improves the diagnostic capabilities of junior radiologists. This has the potential to reduce unnecessary invasive diagnostic procedures in real-world clinical practice.

Quantitative assessment of left ventricular myocardial work in patients with different types of atrial fibrillation by non-invasive pressure-strain loop technique.

OBJECTIVE: This study aimed to analyze myocardial work in patients with atrial fibrillation (AF) using a noninvasive pressure strain loop (PSL) technique to provide a basis for the quantitative assessment of left ventricular (LV) systolic function. METHODS: LV myocardial work of 107 AF patients (56 with paroxysmal atrial fibrillation and 51 with persistent atrial fibrillation) and 55 healthy individuals were assessed by the noninvasive PSL and then compared. RESULTS: Global longitudinal strain (GLS) in absolute values, global work index (GWI), global constructive work (GCW), and global work efficiency (GWE) were significantly lower in the AF group than control group, whereas peak strain dispersion (PSD) and global wasted work (GWW) were significantly higher (P < .05). Further subdivision according to the AF type revealed that, compared with the controls, GLS in absolute values and GWE decreased significantly; PSD and GWW increased significantly in the paroxysmal AF group (P < .05). Nevertheless, GWI and GCW were not significantly different between paroxysmal AF and control groups (P > .05). Compared to paroxysmal AF, persistent AF induced a further decrease in absolute GLS and GWE and a further increase in GWW (P < .05), but PSD did not increase further (P > .05). Multiple linear regression analysis showed that GWI and GCW were independently associated with systolic blood pressure. GWW was associated with types of AF and left atrial volume index (LAVI). GWE was correlated with age, types of AF, disease duration, and LAVI. Receiver operating characteristic curve analysis showed that the area under the curve predicting myocardial injury was higher for GWE and GWW than for GLS (area under the curve:  .880,  .846, and  .821, respectively). CONCLUSIONS: Non-invasive PSL can quantitatively assess LV systolic function in patients with different kinds of AF and detect early subclinical myocardial injury in patients with paroxysmal AF. GWE and GWW outperform GLS and LV ejection fraction when assessing myocardial injury. Systolic blood pressure, type of AF, LVAI, disease duration, and age may be associated with myocardial injury in patients with AF.

Three-Dimensional Crystal Vue Imaging technology assessment of Sylvian fissures at 20-32+6 weeks' normal gestation.

OBJECTIVE: Assess developmental pattern of Sylvian fissures (SF) with Three-Dimensional Crystal Vue Imaging (3D-CVI) at 20-32+6 weeks of gestation. METHODS: This was a prospective cross-sectional study. Assess 20-32+6 weeks' gestation normal development of fetal brain SF with 3D-CVI imaging. Measure the uncovered area and perimeter of the insula on the Three-Dimensional (3D) image and establish reference ranges for the uncovered area and perimeters of the insula during normal pregnancy 20-32+6 weeks' gestation. Examine intra- and interobserver repeatability of measurements of the uncovered area and perimeter of the insula. RESULTS: A total of 286 normal fetuses from 20 to 32+6 weeks of gestation were studied. The SF first was trapezoidal in the 25 weeks of gestation, gradually becoming triangular as gestational age (GA) increased, and then closing from posterior up to anterior down. The uncovered area and dimension of the insula showed a parabolic curve that first increased and then decreased as GA and head circumference (HC) increased. Reference ranges for measurements of the uncovered area and perimeters of the insula during normal pregnancy 20-32+6 weeks' gestation were established. The intra- and interobserver agreements were reproducible (all ICC > 0.850); there were more than 95% dots in the Bland-Altman plots (95 limits of agreement (LOA)) scale in every figure. CONCLUSIONS: 3D-CVI can be used to observe the morphological changes of SF during middle and late pregnancy, which is an intuitive supplementary means for prenatal evaluation of cerebral cortex development, guiding subsequent follow-up and referral for assessment by expert neurosonologists. KEY POINTS: • A new imaging technique was found to visualize the SF of fetal brain surface. • This technique has the advantages of good consistency and repeatability, simple operation, short time-consuming, and low cost. • Its 3D visualization images can be used to the development and changes of the sulci on the brain surface, it provides a new method to evaluate the development of cerebral cortex.

Abrupt formation of intracardiac thrombus during patent foramen ovale closure by three-dimensional transesophageal echocardiography.

We report a rare case of abrupt formation of intracardiac thrombus during patent foramen ovale closure by three-dimensional transesophageal echocardiography. This case highlights transesophageal echocardiography allows timely detection and management of intracardiac thrombus formation.

Diagnosis of fetal congenitally unguarded tricuspid valve orifice by echocardiography.

OBJECTIVE: To review the imaging characteristics and evaluate the diagnostic value of echocardiography for fetal congenitally unguarded tricuspid valve orifice (CUTVO). METHODS: Doppler echocardiography was performed and the images were compared with operative and necropsy findings in ten fetuses with CUTVO. The aim of the study was to summarize the characteristics of fetal echocardiography and analyze the causes of missed diagnoses and misdiagnoses. RESULTS: There were six cases with complete absence (60%) and four cases with partial absence of the tricuspid leaflet (40%). Among all cases, six cases were consistent with the ultrasonic diagnosis. CUTVO ultrasonographic characteristics consist of the atrioventricular connection with normal arteries and the tricuspid valve device partially or completely absent. The annulus of the tricuspid valve can be described as "empty" in the apical four-chamber view, Doppler evaluation shows to-and-fro flow across the tricuspid orifice with low velocity and two-way spectrum. CONCLUSION: Fetal echocardiography can accurately diagnose CUTVO, but missed diagnosis and misdiagnosis should be reduced.

Classification of Thyroid Nodules by Using Deep Learning Radiomics Based on Ultrasound Dynamic Video.

OBJECTIVES: We aimed to design a radiomics model for differential diagnosis of thyroid carcinoma based on dynamic ultrasound video, and compare its diagnostic performance with that of radiomics model based on static ultrasound images. METHODS: Between January 2019 and May 2021, 890 patients with 1015 thyroid nodules (775 for training, 240 for validation) were prospectively enrolled. In total 890 patients underwent thyroidectomy within 1 month, and ultrasound dynamic video and static images were both acquired. Two deep learning (DL) models, namely DL-video and DL-image models, were proposed to diagnose thyroid nodules by analyzing ultrasound video and static images respectively. The performance of models was assessed by areas under the receiver operating characteristic curve (AUC). The DL model on ultrasound cines was re-visualized to help radiologists understand its potential working mechanism. RESULTS: The AUC of DL-video were 0.947 (95% CI: 0.931-0.963) and 0.923 (95% CI: 0.892-0.955) in training and validation cohorts, respectively. For DL-image model, the AUC were 0.928 (95% CI: 0.910-0.945) and 0.864 (95% CI: 0.819-0.910), respectively. The diagnosis performance of the DL-video was superior to that of DL-image, and there was significant difference between the AUC of DL-video and DL-image model in validation cohort (P = .028). The visualization demonstrated certain important ultrasound features that could be recognized by human eyes. CONCLUSIONS: The proposed DL radiomics model based on dynamic ultrasound video can accurately and individually classified thyroid nodules. The constructed DL-video model combining ultrasound video holds good potential for benefiting the management of patients with thyroid nodules.

A Foxtail mosaic virus Vector for Virus-Induced Gene Silencing in Maize.

Plant viruses have been widely used as vectors for foreign gene expression and virus-induced gene silencing (VIGS). A limited number of viruses have been developed into viral vectors for the purposes of gene expression or VIGS in monocotyledonous plants, and among these, the tripartite viruses Brome mosaic virus and Cucumber mosaic virus have been shown to induce VIGS in maize (Zea mays). We describe here a new DNA-based VIGS system derived from Foxtail mosaic virus (FoMV), a monopartite virus that is able to establish systemic infection and silencing of endogenous maize genes homologous to gene fragments inserted into the FoMV genome. To demonstrate VIGS applications of this FoMV vector system, four genes, phytoene desaturase (functions in carotenoid biosynthesis), lesion mimic22 (encodes a key enzyme of the porphyrin pathway), iojap (functions in plastid development), and brown midrib3 (caffeic acid O-methyltransferase), were silenced and characterized in the sweet corn line Golden × Bantam. Furthermore, we demonstrate that the FoMV infectious clone establishes systemic infection in maize inbred lines, sorghum (Sorghum bicolor), and green foxtail (Setaria viridis), indicating the potential wide applications of this viral vector system for functional genomics studies in maize and other monocots.

Replication protein A subunit 3 and the iron efficiency response in soybean.

In soybean [Glycine max (L.) Merr.], iron deficiency results in interveinal chlorosis and decreased photosynthetic capacity, leading to stunting and yield loss. In this study, gene expression analyses investigated the role of soybean replication protein A (RPA) subunits during iron stress. Nine RPA homologs were significantly differentially expressed in response to iron stress in the near isogenic lines (NILs) Clark (iron efficient) and Isoclark (iron inefficient). RPA homologs exhibited opposing expression patterns in the two NILs, with RPA expression significantly repressed during iron deficiency in Clark but induced in Isoclark. We used virus induced gene silencing (VIGS) to repress GmRPA3 expression in the iron inefficient line Isoclark and mirror expression in Clark. GmRPA3-silenced plants had improved IDC symptoms and chlorophyll content under iron deficient conditions and also displayed stunted growth regardless of iron availability. RNA-Seq comparing gene expression between GmRPA3-silenced and empty vector plants revealed massive transcriptional reprogramming with differential expression of genes associated with defense, immunity, aging, death, protein modification, protein synthesis, photosynthesis and iron uptake and transport genes. Our findings suggest the iron efficient genotype Clark is able to induce energy controlling pathways, possibly regulated by SnRK1/TOR, to promote nutrient recycling and stress responses in iron deficient conditions.

Fully-Automatic Detection and Diagnosis System for Thyroid Nodules Based on Ultrasound Video Sequences by Artificial Intelligence.

Background: Interpretation of ultrasound findings of thyroid nodules is subjective and labor-intensive for radiologists. Artificial intelligence (AI) is a relatively objective and efficient technology. We aimed to establish a fully automatic detection and diagnosis system for thyroid nodules based on AI technology by analyzing ultrasound video sequences. Patients and Methods: We prospectively acquired dynamic ultrasound videos of 1067 thyroid nodules (804 for training and 263 for validation) from December 2018 to January 2021. All the patients underwent hemithyroidectomy or total thyroidectomy. Dynamic ultrasound videos were used to develop an AI system consisting of two deep learning models that could automatically detect and diagnose thyroid nodules. Average precision (AP) was used to estimate the performance of the detection model. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of the diagnostic model. Results: Location and shape were accurately detected with a high AP of 0.914 in the validation cohort. The AUC of the diagnostic model was 0.953 in the validation cohort. The sensitivity and specificity of junior and senior radiologists were 76.9% vs 78.3% and 68.4% vs 81.1%, respectively. The diagnostic performance of the AI diagnostic model was superior to that of junior radiologists (P = 0.016) and was not significantly different from that of senior radiologists (P = 0.281). Conclusion: We established a fully automatic detection and diagnosis system for thyroid nodules based on ultrasound video using an AI approach that can be conveniently applied to optimize the management of patients with thyroid nodules.

Diagnostic value of contrast-enhanced ultrasound in the diagnosis of papillary thyroid microcarcinoma: A systematic review and meta-analysis.

BACKGROUND: Using meta-analysis to evaluate the diagnostic value of contrast-enhanced ultrasound (CEUS) in the diagnosis of papillary thyroid microcarcinoma (PTMC). METHODS: For this systematic review and meta-analysis, we searched PubMed, Cochrane Library, Web of Science, WanFang Data, VPCS Data, and China National Knowledge Infrastructure electronic databases for diagnostic studies on PTMC by CEUS from January 2013 to November 2022. Data were not available or incomplete such as case reports, nonhuman studies, etc, were excluded. Random-effects meta-analyses were used to evaluate the diagnostic accuracy of CEUS in diagnosing PTMC. The quality of the evidence was assessed with the QUADAS-2 scale. This study is registered on PROSPERO, number CRD42023409417. RESULTS: Of 1064 records identified, 33 were eligible. The results showed that the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CEUS in diagnosing PTMC were 0.84 (95% confidence interval [CI] = 0.83-0.86), 0.82 (95% CI = 0.80-0.83), 3.90 (95% CI = 3.23-4.72), 0.21 (95% CI = 0.18-0.25), and 20.01 (95% CI = 14.97-26.74), respectively, and the area under the summary receiver operating characteristic curve was 0.8930 (the Q index was 0.8239). The Deek funnel plot indicated publication bias (P ˂.01). CONCLUSION: This meta-analysis provides an overview of diagnostic accuracy of CEUS in diagnosing PTMC which indicates CEUS has a good diagnostic value for PTMC. The limitations of this study are publication bias and strong geographical bias.

Plant Growth Promotion and Plant Disease Suppression Induced by Bacillus amyloliquefaciens Strain GD4a.

Botrytis cinerea, the causative agent of gray mold disease (GMD), invades plants to obtain nutrients and disseminates through airborne conidia in nature. Bacillus amyloliquefaciens strain GD4a, a beneficial bacterium isolated from switchgrass, shows great potential in managing GMD in plants. However, the precise mechanism by which GD4a confers benefits to plants remains elusive. In this study, an A. thaliana-B. cinerea-B. amyloliquefaciens multiple-scale interaction model was used to explore how beneficial bacteria play essential roles in plant growth promotion, plant pathogen suppression, and plant immunity boosting. Arabidopsis Col-0 wild-type plants served as the testing ground to assess GD4a's efficacy. Additionally, bacterial enzyme activity and targeted metabolite tests were conducted to validate GD4a's potential for enhancing plant growth and suppressing plant pathogens and diseases. GD4a was subjected to co-incubation with various bacterial, fungal, and oomycete pathogens to evaluate its antagonistic effectiveness in vitro. In vivo pathogen inoculation assays were also carried out to investigate GD4a's role in regulating host plant immunity. Bacterial extracellular exudate (BEE) was extracted, purified, and subjected to untargeted metabolomics analysis. Benzocaine (BEN) from the untargeted metabolomics analysis was selected for further study of its function and related mechanisms in enhancing plant immunity through plant mutant analysis and qRT-PCR analysis. Finally, a comprehensive model was formulated to summarize the potential benefits of applying GD4a in agricultural systems. Our study demonstrates the efficacy of GD4a, isolated from switchgrass, in enhancing plant growth, suppressing plant pathogens and diseases, and bolstering host plant immunity. Importantly, GD4a produces a functional bacterial extracellular exudate (BEE) that significantly disrupts the pathogenicity of B. cinerea by inhibiting fungal conidium germination and hypha formation. Additionally, our study identifies benzocaine (BEN) as a novel small molecule that triggers basal defense, ISR, and SAR responses in Arabidopsis plants. Bacillus amyloliquefaciens strain GD4a can effectively promote plant growth, suppress plant disease, and boost plant immunity through functional BEE production and diverse gene expression.

Evaluation of Left Atrial Function in Patients with Paroxysmal Atrial Fibrillation Using Left Atrial Automatic Myocardial Functional Imaging Ultrasonography.

Aim: To evaluate volume and strain of the left atrium (LA) in people suffering from paroxysmal atrial fibrillation which is not valvular (NVPAF) using the new technology of left atrial automatic myocardial function imaging (AFILA) and to analyze prognostic factors in patients with NVPAF by follow-up. Methods: Between August 2019 and August 2022, a total of 80 NVPAF patients and 60 normal control patients who were hospitalized in the Department of Cardiology were included in the study. The LA volume and strain parameters of the two groups were analyzed. The differences in LA function (LAF) parameters were compared between the two groups to generate the receiver operating characteristic curve (ROC) and calculate the area under the curve (AUC), sensitivity, and specificity of each parameter. Follow-up was conducted on the 80 NVPAF patients included, their treatment methods after admission and their rehospitalization due to heart events were recorded, and independent risk factors influencing the prognosis of NVPAF were obtained. Results: A total of 140 patients participated in the study, including 80 in the NVPAF group and 60 in the normal control group. There was no statistically significant difference in age and sex between the two groups. Compared to the normal group, the LA minimum volume (LAVmin), LA maximum volume (LAVmax), and volume at onset of LA contraction (LAVpreA) in the NVPAF group were significantly increased. The LA emptying fraction (LAEF) was significantly decreased, and LA reservoir strain (S_R), LA conduit strain (S_CD), and LA contractile strain (S_CT) were significantly compromised (P < 0.05). There was no significant difference in LA evacuation volume (LAEV) reduction (P > 0.05). Logistic regression analysis of LAF parameters in NVPAF patients showed that LAEF and S_R were independently correlated with NVPAF (odds ratio values: 0.883 (0.827-0.943), P < 0.001; 0.916 (0.569-1.474), P = 0.047). The ROC curve results showed that LAEF had a high efficiency in the diagnosis of NVPAF, with P < 0.001, AUC of 0.843, sensitivity of 0.788, and specificity of 0.867. For the LA strain parameters, the S_R test efficiency was higher, with P < 0.001, AUC of 0.762, sensitivity of 0.713, and specificity of 0.783. There was a strong correlation between S_R and LAEF in patients with no end event and those with end event. The ROC curve revealed that the S_R was better than LAEF in predicting prognosis of patients with AF (AUC = 0.914, P < 0.0001 vs. AUC = 0.876, P < 0.0001). S_R of 10.5 and LAEF of 21 were the cut-off values for endpoint events in NVPAF patients, with sensitivity of 0.909 and 0.727 and specificity of 0.904 and 0.901, respectively. Conclusions: AFILA ultrasound technology comprehensively evaluated the LA size and function in patients with NVPAF. The LAEF and S_R were independently correlated with NVPAF and can determine the prognosis of patients with NVPAF.

Three-dimensional echocardiography and strain cardiac imaging in patients with prediabetes and type 2 diabetes mellitus.

Background: Several studies using two-dimensional speckle tracking echocardiography (2D-STE) have confirmed the presence of left ventricular (LV) systolic dysfunction in patients with diabetes mellitus (DM), but there is a paucity of studies on whether three-dimensional (3D)-STE is superior to 2D-STE. The aim of this study was to evaluate the clinical value of 3D-STE in assessing subclinical LV systolic dysfunction in prediabetic and diabetic patients with preserved LV ejection fraction (LVEF) and to investigate the independent risk factors for this medical disorder. Methods: This study included 40 diabetic patients, 35 prediabetic patients, and 33 healthy volunteers. All participants underwent LV peak systolic strain analysis using 3D- and 2D-STE, and the receiver operating characteristic (ROC) curve was constructed to determine the clinical diagnostic value of strain parameters for evaluating subclinical LV dysfunction in patients with prediabetes and type 2 DM (T2DM). Regression models were established to analyze independent risk factors for subclinical LV systolic dysfunction in patients with prediabetes and diabetes. Results: The results of the 3D-STE-based analysis showed that the global longitudinal strain (GLS) of the control, prediabetic, and diabetic groups were (18.64%±2.43%, 15.21%±1.49%, and 13.49%±2.36%, respectively), global circumferential strain (GCS) was (18.09%±2.37%, 14.62%±1.75%, and 12.95%±2.20%, respectively), global area strain (GAS) was (31.30%±3.88%, 27.51%±3.31%, and 24.80%±3.86%, respectively), and global radial strain (GRS) was (49.18%±5.91%, 39.17%±4.55%, and 35.72%±7.19%, respectively). All 3D-STE global strain parameters gradually decreased from the controls, through the prediabetic group to the diabetic group, and there was statistical significance between the three groups (P<0.001). The area under the curve (AUC) of the 3D-STE global strain parameters (GLS, GCS, GAS, and GRS) were 0.898, 0.831, 0.863, and 0.868, respectively. The AUC of the 2D-STE global strain parameters (GLS and GCS) were 0.867 and 0.636, respectively. Multivariate regression analysis identified increased glycosylated hemoglobin A1c (HbA1c) and body mass index (BMI) as independent risk factors for subclinical LV systolic dysfunction. Conclusions: Prediabetic and diabetic patients with preserved LVEF are at risk of subclinical LV systolic dysfunction. 3D-STE is a reliable imaging technique for evaluating early damage to LV myocardial mechanics. Early control of blood glucose (Glu) levels and weight can effectively prevent heart failure in the prediabetic and diabetic populations.

Use of left atrial automated functional myocardial imaging to identify patients with paroxysmal atrial fibrillation at high risk of stroke.

Background: Left atrial automated functional myocardial imaging (AFILA) is a new software program for analyzing the structure and function of the left atrium (LA). The present study sought to analyze the correlation between the LA function parameters as measured by AFILA echocardiography and the risk of cerebral ischemic stroke (CIS) in patients with non-valvular paroxysmal atrial fibrillation (NVPAF) to explore the diagnostic value of LA strain in patients with congestive heart failure, hypertension, age of ≥75 years (doubled), diabetes mellitus, stroke or transient ischemic attack (TIA) (doubled), age of 65-74 years, and sex category (female) (CHA2DS2-VASc) scores of <2. Methods: A total of 205 patients with NVPAF were included in the study and divided into the no-CIS group (154 patients) and the CIS group (51 patients). The baseline clinical data for the 2 groups were analyzed, and routine echocardiography examinations were performed. AFILA was used to evaluate the LA function of all the patients. Results: Compared to the no-CIS group, the LA emptying fraction and the LA reservoir strain were decreased, the LA contractile strain (S_CT) was increased, and the S_CT value changed from negative to positive in the CIS group, and the difference between the 2 groups were statistically significant (P<0.001). However, there were no significant differences in the volume at the onset of LA contraction, LA evacuation volume, LA minimum volume, LA maximum volume, and LA conduit strain between the 2 groups. The multifactorial regression analysis showed that age, hypertension, and the S_CT were independently associated risk factors for patients with CIS. After correcting for the clinical factors included in the CHA2DS2-VASc score, the S_CT was shown to predict to NVPAF with stroke [odds ratio (OR): 1.234, 95% confidence interval (CI): 1.101-1.383, P=0.000]. In addition, we included the CHA2DS2-VASc score (instead of age, diabetes, coronary artery disease, and hypertension) in a multiple regression analysis, and found that the S_CT was still significant (OR: 1.252, 95% CI: 1.118-1.402, P=0.000). The difference between the 2 groups in the CHA2DS2-VASc score for the S_CT was statistically significant, especially when the CHA2DS2-VASc score was <2. The S_CT equaled -4.5% was the cut-off value for the presence or absence of CIS in the NVPAF patients, with an area under the curve (AUC) of 0.866, sensitivity of 0.80, and specificity of 0.75 (P<0.0001). Conclusions: Comparison with LA volume parameter, measuring LA strain by AFILA provides a better index for the dynamic assessment of impaired LA function in patients with NVPAF combined with CIS, especially in those with a CHA2DS2-VASc score of <2. In addition, a LA S_CT of >-4.5% is a valuable cut-off for patients with NVPAF. The results of the current study may form the basis for a large prospective multicenter interventional study in which patients with impaired LA S_CT are randomized to receive oral anti-coagulant (OAC) therapy or no OAC therapy for the primary prevention of stroke.

DPAM-PSPNet: ultrasonic image segmentation of thyroid nodule based on dual-path attention mechanism.

Objective.Deep learning has demonstrated its versatility in the medical field, particularly in medical image segmentation, image classification, and other forms of automated diagnostics. The clinical diagnosis of thyroid nodules requires radiologists to locate nodules, diagnose conditions based on nodule boundaries, textures and their experience. This task is labor-intensive and tiring; therefore, an automated system for accurate thyroid nodule segmentation is essential. In this study, a model named DPAM-PSPNet was proposed, which automatically segments nodules in thyroid ultrasound images and enables to segment malignant nodules precisely.Approach.In this paper, accurate segmentation of nodule edges is achieved by introducing the dual path attention mechanism (DPAM) in PSPNet. In one channel, it captures global information with a lightweight cross-channel interaction mechanism. In other channel, it focus on nodal margins and surrounding information through the residual bridge network. We also updated the integrated loss function to accommodate the DPAM-PSPNet.Main results.The DPAM-PSPNet was tested against the classical segmentation model. Ablation experiments were designed for the two-path attention mechanism and the new loss function, and generalization experiments were designed on the public dataset. Our experimental results demonstrate that DPAM-PSPNet outperforms other existing methods in various evaluation metrics. In the model comparison experiments, it achieved performance with an mIOU of 0.8675, mPA of 0.9357, mPrecision of 0.9202, and Dice coefficient of 0.9213.Significance.The DPAM-PSPNet model can segment thyroid nodules in ultrasound images with little training data and generate accurate boundary regions for these nodules.

An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images.

Breast and thyroid cancers are the two most common cancers among women worldwide. The early clinical diagnosis of breast and thyroid cancers often utilizes ultrasonography. Most of the ultrasound images of breast and thyroid cancer lack specificity, which reduces the accuracy of ultrasound clinical diagnosis. This study attempts to develop an effective convolutional neural network (E-CNN) for the classification of benign and malignant breast and thyroid tumors from ultrasound images. The 2-Dimension (2D) ultrasound images of 1052 breast tumors were collected, and 8245 2D tumor images were obtained from 76 thyroid cases. We performed tenfold cross-validation on breast and thyroid data, with a mean classification accuracy of 0.932 and 0.902, respectively. In addition, the proposed E-CNN was applied to classify and evaluate 9297 mixed images (breast and thyroid images). The mean classification accuracy was 0.875, and the mean area under the curve (AUC) was 0.955. Based on data in the same modality, we transferred the breast model to classify typical tumor images of 76 patients. The finetuning model achieved a mean classification accuracy of 0.945, and a mean AUC of 0.958. Meanwhile, the transfer thyroid model realized a mean classification accuracy of 0.932, and a mean AUC of 0.959, on 1052 breast tumor images. The experimental results demonstrate the ability of the E-CNN to learn the features and classify breast and thyroid tumors. Besides, it is promising to classify benign and malignant tumors from ultrasound images with the transfer model under the same modality.

Evaluating the effect of PD-1 inhibitors on left ventricular function in lung cancer with noninvasive myocardial work.

Background: The treatment of advanced lung cancer has been revolutionized by immune checkpoint inhibitors (ICIs) in recent years, largely driven by programmed cell death-1 (PD-1) inhibitors. However, patients with lung cancer who are treated with PD-1 inhibitors are prone to immune-related adverse events (irAEs), especially cardiac adverse events. Noninvasive myocardial work is a novel technique used to assess left ventricular (LV) function, which can effectively predict myocardial damage. Here, noninvasive myocardial work was used to evaluate changes in LV systolic function during PD-1 inhibitor therapy and to assess ICIs-related cardiotoxicity. Methods: From September 2020 to June 2021, 52 patients with advanced lung cancer in the Second Affiliated Hospital of Nanchang University were prospectively enrolled. In total, 52 patients underwent PD-1 inhibitor therapy. The cardiac markers, noninvasive LV myocardial work, and conventional echocardiographic parameters were measured at pretherapy (T0) and posttreatment after the first (T1), second (T2), third (T3), and fourth (T4) cycles. Following this, the trends of the above parameters were analyzed using analysis of variance with repeated measures and the Friedman nonparametric test. Furthermore, the relationships between disease characteristics (tumor type, treatment regimen, cardiovascular risk factors, cardiovascular drugs, and irAEs) and noninvasive LV myocardial work parameters were assessed. Results: Throughout the follow-up, the cardiac markers and conventional echocardiographic parameters showed no significant changes. Based on the normal reference ranges, patients with PD-1 inhibitor therapy had increased values of LV global waste work (GWW) and decreased global work efficiency (GWE) that began at T2. Compared with T0, GWW increased from T1 to T4 (42%, 76%, 87%, and 87%, respectively), while global longitudinal strain (GLS), global work index (GWI), and global constructive work (GCW) decreased in varying degrees (P<0.001). Most of the disease characteristics had no effect on the LV myocardial work parameters; however, the numbers of irAEs were closely associated with GLS (P=0.034), GWW (P<0.001), and GWE (P<0.001). Patients with 2 or more irAEs had higher values of GWW and lower GLS and GWE. Conclusions: Noninvasive myocardial work can accurately reflect myocardial function and energy utilization in patients with lung cancer who are undergoing PD-1 inhibitor treatment and may thus benefit the management of patients with ICIs-related cardiotoxicity.