This study included 468 patients and aimed to use multimodal ultrasound radiomic technology to predict the malignancy of TI-RADS 4-5 thyroid nodules. First, radiomic features are extracted from conventional two-dimensional ultrasound (transverse ultrasound and longitudinal ultrasound), strain elastography (SE), and shear-wave-imaging (SWE) images. Next, the least absolute shrinkage and selection operator (LASSO) is used to screen out features related to malignant tumors. Finally, a support vector machine (SVM) is used to predict the malignancy of thyroid nodules. The Shapley additive explanation (SHAP) method was used to intuitively analyze the specific contributions of radiomic features to the model’s prediction. Our proposed model has AUCs of 0.971 and 0.856 in the training and testing sets, respectively. Our proposed model has a higher prediction accuracy compared to those of models with other modal combinations. In the external validation set, the AUC of the model is 0.779, which proves that the model has good generalization ability. Moreover, SHAP analysis was used to examine the overall impacts of various radiomic features on model predictions and local explanations for individual patient evaluations. Our proposed multimodal ultrasound radiomic model can effectively integrate different data collected using multiple ultrasound sensors and has good diagnostic performance for TI-RADS 4-5 thyroid nodules.

A retrospective study was conducted to determine the value of shear wave elastography (SWE) and red blood cell distribution width (RDW) in the diagnosis of various forms of erectile dysfunction (ED). With the method of Nocturnal Penile Tumescence and Rigidity (NPTR) and the screening method of Color Duplex Doppler Ultrasound (CDDU), hematological data were collected from 131 individuals, among whom 24 are with psychogenic ED, 48 are with non-arterial ED(NAED) and 59 are with arterial ED(AED) with erectile dysfunction. SWE value of penile corpus cavernosum(CCP) and cavernous arterial flow velocity were measured before (flaccid state) and after (erect state) intracavernous injection (ICI) in all patients. Among the AED patients and other types of ED patients, there were statistically significant differences in the abridged five-item International Index of Erectile Function (IIEF-5), red blood cell distribution width-coefficient of variation (RDW-CV), red blood cell distribution width-standard deviation (RDW-SD), and SWE values (all P < 0.01). In the AED patients, the IIEF-5 scores had a significant negative relationship with RDW-CV, RDW-SD, and SWE values, with SWE values having the strongest correlation. (p < 0.001, r=-0.638). The combination of RDW level and SWE value demonstrated the greatest performance in diagnosing AED, according to the receiver-operator characteristic(ROC) curve analysis (AUC = 0.870, p < 0.0001, cut-off value of 0.75, sensitivity of 74.6%, specificity of 91.7%).RDW and SWE value may develop into an incredibly simple, practical tool for predicting and diagnosing AED. retrospectively registered.

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To investigate qualitative and quantitative microvascular biomarkers derived from ultrasound localization microscopy (ULM) for differentiating benign and malignant breast lesions, and to evaluate their added value in improving BI-RADS-based diagnosis. In this prospective study, 295 patients with 301 breast lesions classified as BI-RADS category 4–5 on conventional ultrasound (US) underwent contrast-enhanced ultrasound and ULM prior to surgery or biopsy. Qualitative vascular biomarkers and quantitative parameters were derived from ULM images. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. BI-RADS categories were further re-evaluated by integrating ULM-derived biomarkers. ULM qualitative vascular biomarkers classified microvascular morphology into five patterns: avascular, dot-strip, circular, chaotic, and radial. Benign lesions predominantly exhibited avascular, dot-strip, and circular patterns (5.6%, 23.4%, and 48.6%, respectively), whereas malignant lesions were mainly characterized by chaotic and radial patterns (56.7% and 28.4%, respectively; p < 0.001). The qualitative assessment achieved an AUC of 0.825 (95% CI: 0.780–0.871). All ULM quantitative biomarkers showed significant differences between benign and malignant lesions (all p < 0.05), among which maximum diameter demonstrated the highest diagnostic value (AUC = 0.898, 95% CI: 0.861–0.935). A combined quantitative biomarker (CQB) model further improved performance (AUC = 0.920). Integration of ULM qualitative and quantitative biomarkers with BI-RADS further improved diagnostic accuracy (AUC = 0.976; sensitivity 0.964; specificity 0.916) and may improve risk stratification beyond BI-RADS. ULM-derived qualitative and quantitative microvascular biomarkers provide complementary information beyond conventional ultrasound and may improve diagnostic performance and risk stratification in BI-RADS 4–5 breast lesions, but their role in safely reducing unnecessary biopsies requires further clinical validation.

Background Sepsis is a systemic inflammatory response syndrome caused by pathogen infection, which is associated with pyroptosis. Previous studies have shown that neutrophil pyroptosis may play an important role in sepsis; however, the potential prognostic and diagnostic value of pyroptosis-related genes in sepsis remains undefined. Methods The RNA-seq data and clinical data of sepsis were extracted from the Gene Expression Omnibus (GEO) database. Then, neutrophil-related pyroptosis genes (NRPGs) were filtered by overlapping neutrophil-related genes obtained from weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) between sepsis and healthy samples and pyroptosis-related genes (PRGs) retrieved from prior reviews. Subsequently, survival analysis was performed, and the correlation between the NRPGs and clinical traits was assessed. Furthermore, independent prognostic indicators were screened using Cox regression analyses, and independent prognostic genes were defined as biomarkers. Gene set enrichment analysis (GSEA) was performed to explore the potential biological pathway related to biomarkers. Correlation between prognostic indicators and immune cell infiltration were investigated. Eventually, the potential therapeutic drugs targeting biomarkers were predicted from ZINC15 database. Results A total of 6 NRPGs were filtered by overlapping 3109 neutrophil-related module genes, 4078 DEGs, and 33 PRGs. Meanwhile, 5 NRPGs (CASP6, GSDMB, CASP4, ELANE, and NLRP3) were related to the survival of sepsis. The correlation analysis results indicated that CASP6, GSDMB, CASP4, ELANE, and NLRP3 were significantly correlated with endotype class. In addition, the age, endotype class, and ELANE were regarded as independent prognostic indicators, and ELANE could be used as a biomarker. GSEA suggested that ELANE was markedly related to endocytosis, bacterial infection, autophagy, cell cycle and TNF signaling pathway. Additionally, NK cell, myeloid dendritic cell, and neutrophil were different in ELANE expression groups, and NK cells and neutrophil had a strongly negative correlation with ELANE. Ultimately, molecular docking results showed ZINC000164760756 had the lowest docking energy, which might be used to treat sepsis by targeting ELANE. Conclusion ELANE may be used as a biomarker for sepsis, which may provide a theoretical basis for the investigation of the molecular mechanisms of sepsis.