REVIEW ARTICLE

Ultrasound-guided Transperineal Prostate Thermal Ablation: Advances in Benign Prostatic Hyperplasia

Zhan Cuiping, Han Xiao, Huang Qingbo, Shi Xian-Quan

2026, 10 (3): 127-136. DOI:10.26599/AUDT.2026.260019

Abstract ( 15 ) HTML ( 3 ) PDF ( 989KB ) ( 19 ) 　　

Benign prostatic hyperplasia (BPH) is a prevalent condition in middle-aged and elderly men, often leading to lower urinary tract symptoms. Although traditional surgical interventions are effective, their limitations include high invasivity and prolonged recovery periods. In recent years, ultrasound-guided transperineal prostate thermal ablation has emerged as a minimally invasive alternative, gaining prominence due to its enhanced precision and low complication rates. This review examines the clinical advancements of three transperineal thermal ablation techniques: transperineal laser ablation (TPLA), transperineal radiofrequency ablation (TPRFA), and transperineal microwave ablation (TPMA). By analyzing recent clinical studies and trials, the procedural methodologies of each technique are elaborated, along with their respective clinical outcomes and associated complications. Furthermore, this work consolidates existing evidence to underscore the role of transperineal thermal ablation in personalized BPH management. This review aims to inform clinical decision-making and expand minimally invasive therapeutic options for BPH treatment.

Ultrasound Image Segmentation in Cardiovascular Disease: A Review of Techniques and Clinical Applications

Li Zuoyan, Du Lianfang, Li Fan

2026, 10 (3): 137-147. DOI:10.26599/AUDT.2026.250063

Abstract ( 12 ) HTML ( 1 ) PDF ( 3596KB ) ( 16 ) 　　

This review provides a comprehensive overview of echocardiographic image segmentation techniques in representative clinical contexts, including valvular heart disease (VHD), congenital heart disease (CHD), and left ventricular (LV) dysfunction and heart failure. The article first outlines the standardized workflow for ultrasound (US) image segmentation, establishing a technical framework for comparing and evaluating different approaches. This is followed by a brief overview of the pathophysiological characteristics of these conditions, highlighting their anatomical segmentation requirements and clinical implications. Subsequently, the review summarizes the evolution and key contributions of traditional image processing, machine learning (ML), and deep learning (DL) methods across different disease types. Comparative analysis indicates that DL models, with their end-to-end training strategies and hierarchical feature representation, demonstrate substantial advantages in segmentation automation and accuracy. Finally, the article discusses current challenges in data acquisition, model generalizability, and clinical integration, and explores future research directions to promote the development and translational application of intelligent echocardiographic analysis.

Current Applications and Advances of Ultrasound in Predicting Adverse Pregnancy Outcomes in Pregnant Women with Pre-eclampsia

He Xiang, Hu Rong, Deng Xuejia, Yang Fan

2026, 10 (3): 148-157. DOI:10.26599/AUDT.2026.260026

Abstract ( 11 ) HTML ( 2 ) PDF ( 1081KB ) ( 11 ) 　　

Pre-eclampsia is a pregnancy-specific complication characterized by new-onset hypertension and proteinuria or other target organ dysfunction after 20 weeks of gestation, posing serious threats to maternal and fetal health. In recent years, early prediction of adverse pregnancy outcomes associated with pre-eclampsia has become an important research direction. This review summarizes the research progress on the application of ultrasound parameters in this field, focusing on the clinical value of grayscale ultrasound, Doppler ultrasound technology, three-dimensional ultrasound technology, and microvascular flow imaging technology. The advantages and existing limitations of each technique are analyzed, and future development directions including the integration of multimodal parameters, combination with serological biomarkers, and artificial intelligence are discussed, aiming to provide references for early warning and optimization of clinical management of pre-eclampsia.

Fetal Ventricular-arterial Coupling: Development, Physiology, and Ultrasonographic Advances

Jiang Xingting, Fang Wenling, Hu Panpan, Yu Rong, Ma Jing, Wang Ning, Wu Tianyu, Ye Lin, Ruan Wenhui, Li Zhaojun, Jin Lin

2026, 10 (3): 158-168. DOI:10.26599/AUDT.2026.250112

Abstract ( 11 ) HTML ( 2 ) PDF ( 5834KB ) ( 12 ) 　　

Ventricular-arterial coupling (VAC) is a key determinant of cardiovascular function, reflecting the interaction between cardiac pump performance and arterial load, and plays a crucial role during fetal development. The fetal cardiovascular system undergoes a continuous process from cardiac tube formation and chamber septation to vascular remodeling, providing the structural and functional basis for postnatal circulatory adaptation. Physiologically, VAC represents a dynamic balance between myocardial contractility, ventricular compliance, arterial resistance, and elasticity, ensuring hemodynamic stability and adequate oxygen delivery in utero. During the transition from fetal to neonatal circulation, the closure of placental circulation and the opening of pulmonary circulation induce profound hemodynamic changes, leading to remodeling of VAC with important implications for long-term cardiovascular health. Recent advances in echocardiography and Doppler techniques have enabled comprehensive evaluation of fetal VAC by integrating cardiac functional indices with hemodynamic parameters, facilitating early detection of abnormalities and potential risks. Emerging modalities, including speckle-tracking echocardiography, three-dimensional imaging, and artificial intelligence-assisted analysis, are expected to allow more precise and reproducible quantification of fetal VAC, thereby supporting risk stratification, optimized surveillance, and individualized prenatal management. Thus, research on fetal VAC not only deepens our understanding of cardiovascular developmental and adaptive mechanisms but also provides a clinically relevant framework for ultrasound-based assessment and decision-making in fetal medicine.

ORIGINAL RESEARCH

3D Dynamic Contrast-Enhanced Ultrasound for Personalized RRx-001 Dosing: A Preclinical and Clinical Pilot Study

Oronsky Bryan, Li Dandan, Wang Morgan, Vo-Phamhi Jenny M., Caroen Scott, Abrouk Nacer, Reid Tony, Alizadeh Babak, Hristov Dimitre, Fisher George, Kaffas Ahmed El

2026, 10 (3): 169-177. DOI:10.26599/AUDT.2026.250086

Abstract ( 14 ) HTML ( 1 ) PDF ( 1601KB ) ( 4 ) 　　

Background and Purpose Tumor blood vessels are abnormal and contribute to therapy resistance. RRx-001, an NLRP3 inhibitor, has been shown to remodel tumor vascular properties, enhancing the effects of cytotoxic or immune-promoting agents. However, optimizing timing and dosing of combined treatment regimens is challenging on a patient-by-patient basis; tools for longitudinal imaging to guide such treatment strategy are necessary. Our aim was to evaluate the feasibility of 3D dynamic contrast-enhanced ultrasound (3D DCE-US) to detect acute and subtle tumor perfusion changes following RRx-001 therapy in both mice and humans.
Methods RRx-001 was administered intraperitoneally at varying doses to determine its effect on perfusion in a mouse model of colon cancer. Blood flow and volume were assessed semi-quantitatively using 3D DCE-US within hours and at subsequent time-points. Additionally, we assessed 3D DCE-US in three patients enrolled in a Phase 2 RRx-001 clinical trial (NCT02096354) by imaging them longitudinally.
Results In mice (n = 38), 6 mg/kg RRx-001 led to a 1.5% increase in AUC (P = 0.02) and MTT at 24 hours; 12 mg/kg showed no acute effect. In patients (n = 3), 66 mg weekly dosing produced variable perfusion changes within hours to days. Two patients with stable disease showed transient perfusion increases (survival 9-15 months); one with progressive disease showed early perfusion loss (survival 4 months). No grade 3/4 toxicities occurred.
Conclusion These findings highlight the potential of 3D DCE-US as a noninvasive, bedside tool for real-time monitoring of RRx-001-induced perfusion changes, supporting the feasibility of personalized dosing strategies in both preclinical and clinical settings.

Ultrasound-targeted Microbubble Destruction Mediated miR-200a/PEG10 Axis Promotes Autophagy to Alleviate MAFLD

Zhao Xiaohui, Shen Xueqin, Zhao Haiyue, Jin Diansheng, Zhang Yu, Yang Dongfang, Lan Xiuyan, Liu Yang, Liu Xin, Li Shunan, Shi Xianquan

2026, 10 (3): 178-192. DOI:10.26599/AUDT.2026.250114

Abstract ( 8 ) HTML ( 1 ) PDF ( 13184KB ) ( 8 ) 　　

Background This study aimed to explore the therapeutic potential and mechanism of ultrasound-targeted microbubble destruction (UTMD) combined with the miR-200a/PEG10 axis in metabolic-associated fatty liver disease (MAFLD).
Methods This study was performed at clinical, cellular, and animal levels. Clinically, liver tissues from 10 MAFLD patients and 10 healthy controls were collected to detect miR-200a/PEG10 expression and their correlation. A cellular MAFLD model was induced by palmitic acid (PA)/oleic acid (OA), followed by rescue experiments to assess lipid accumulation, mitochondrial function, apoptosis, and autophagy-related indicators. Animal MAFLD models were established via a high-fat diet, and corresponding interventions were administered to assess hepatic pathological injury and autophagic status.
Results In patients with MAFLD, PEG10 expression was significantly upregulated, whereas miR-200a was downregulated, and their expression levels were negatively correlated. In both MAFLD cells and mouse models, UTMD combined with miR-200a mimics and siPEG10 significantly alleviated hepatic steatosis, reduced lipid accumulation, improved mitochondrial morphology and function, decreased apoptosis, increased the expression levels of autophagy-related proteins (Beclin1, LC3B, PINK1, and Parkin), and reduced P62 level. Rescue experiments further demonstrated that treatment with the autophagy inhibitor 3-methyladenine (3-MA) aggravated hepatocellular injury, whereas the autophagy activator rapamycin (Rapa) enhanced autophagic activity and ameliorated MAFLD pathology. These findings indicated that the combined intervention alleviated MAFLD, at least in part, through the promotion of autophagy.
Conclusion This study identified the miR-200a/PEG10 axis as a critical regulatory pathway in MAFLD and validated UTMD as an effective gene delivery approach for its modulation. These findings provide a novel therapeutic strategy and a theoretical basis for the development of targeted interventions for MAFLD.

Semiautomated Portable Hand-held 3D Ultrasound Imaging System for Carotid Atherosclerotic Plaque Scanning

Huang Yunqian, Shi Junni, Chen Chuanjian, Li Jiawen, Yan Wei, Zheng Rui, Chen Man

2026, 10 (3): 193-202. DOI:10.26599/AUDT.2026.250087

Abstract ( 11 ) HTML ( 1 ) PDF ( 9171KB ) ( 12 ) 　　

Objective To develop a portable handhold 3D Ultrasound imaging and diagnostic system, and to validate its reliability and accuracy in the clinical diagnosis of carotid atherosclerotic plaque.
Materials and methods First acquisition enrolled 55 carotid arteries images by a portable probe which was an important part of the 3D Ultrasound imaging and diagnostic system. 25 arteries were the training set and 30 for validation set. Second acquisition enrolled 84 arteries as an independent validation set. The diagnostic result of our System in carotid plaque including AUC, specificity, sensitivity, accuracy was calculated.
Results A set of learning-based method for automatic segmentation, reconstruction and diagnosis was established. In the validation set and independent validation set, the AUC, sensitivity, specificity and accuracy achieved 0.708 (95%CI: 0.509-0.908)/0.860 (95%CI: 0.773-0.953), 83.3%/83.9%, 58.3%/88.7%, 73.3%/86.9%, respectively.
Conclusion The proposed portable handhold 3D Ultrasound imaging and diagnostic system achieved a satisfactory sensitivity, specificity and accuracy in the diagnosis of carotid plaque. Although dependence on operators was an inevitable problem in routine ultrasound examination, the diagnosis results of our system were not highly dependent on examiner experience. In the future, the system could be applied to carotid atherosclerosis screening in communities or remote settings to help address the shortage of ultrasound examiners.

Discussion on the Application of Combined Transthoracic and Transesophageal Echocardiography in the 'Four-Step Repair Method' for Treating Rheumatic Heart Valve Disease and Its Short-Term Outcomes

Guo Fangqi, Lin Jing, Yang Qirui, Ji Qianwen, Zhao Jiaqi

2026, 10 (3): 203-215. DOI:10.26599/AUDT.2026.250085

Abstract ( 10 ) HTML ( 1 ) PDF ( 14415KB ) ( 5 ) 　　

Objective This study aims to evaluate the therapeutic effectiveness of using combined transthoracic and transesophageal echocardiography in the four-step repair method that preserves the mitral valve structure in patients with rheumatic heart disease (RHD), by assessing changes in structural and hemodynamic parameters before and after surgery.
Methods This study retrospectively collected clinical and imaging data from 105 patients with rheumatic heart disease who underwent heart valve repair surgery between February 2023 and July 2024. All patients underwent transthoracic and transesophageal echocardiography before and after the surgery. The mitral valve structural characteristics and quantitative hemodynamic analysis parameters were evaluated, including leaflet opening and closing angles, leaflet thickening, leaflet adhesion sites, papillary muscle fusion, chordal retraction, presence of thrombus, mitral valve flow velocity, mean pressure gradient, and instantaneous regurgitation area. Postoperative echocardiographic follow-up was performed prior to hospital discharge (median 6 days, range 5-7 days). Statistical methods such as the chi-square test and paired t-test were used to compare these parameters before and after surgery. Short-term outcomes were defined as in-hospital clinical events and echocardiographic findings at discharge.
Results Among the 105 patients with rheumatic mitral stenosis, pre-operative findings included left atrial enlargement (n = 68), atrial fibrillation (n = 44), left atrial thrombus (n = 3), and pulmonary hypertension (n = 24). Pre-operative TTE and TEE demonstrated strong concordance with intraoperative findings for diagnosing mitral leaflet thickening, as indicated by Cohen's κ values of 0.88 (95%CI: 0.80-0.96) and 0.86 (95%CI: 0.79-0.93), respectively. McNemar's test revealed no significant asymmetry in discordant pairs for leaflet thickening (P = 0.125 for TTE; P = 0.065 for TEE). For the assessment of subvalvular pathology including commissural adhesion, chordal retraction, and papillary muscle fusion, TEE exhibited excellent agreement with surgical observations (κ: 0.82-0.90), whereas TTE showed moderate to substantial agreement (κ: 0.45-0.78). The mean cardiopulmonary bypass time was 162.05 ± 42.01 minutes. Post-operative assessment confirmed technical success of the repair procedure in all 105 patients, characterized by the resolution of mitral stenosis and significant improvement in leaflet mobility. Residual mitral regurgitation was mild or less in 98% of patients, with three cases demonstrating moderate regurgitation that did not require immediate re-intervention.
Conclusion While TTE and TEE are equally accurate in detecting leaflet thickening, TEE provides superior visualization of subvalvular pathology. The combined perioperative use of TTE and TEE provides comprehensive multiparametric assessment and appears clinically useful for guiding and evaluating the four-step repair technique in rheumatic mitral valve disease. However, the incremental benefit of the combined approach over either modality alone cannot be quantified from this single-cohort design and warrants prospective comparative study.

Efficient Fetal Ultrasound Image Segmentation with MFP-Unet: A Deep Learning Approach

Ruby A.Usha, Chandran.J George Chellin

2026, 10 (3): 216-222. DOI:10.26599/AUDT.2026.250052

Abstract ( 19 ) HTML ( 2 ) PDF ( 830KB ) ( 4 ) 　　

Background and purpose Fetal ultrasound image segmentation is a crucial component of prenatal diagnosis, enabling the accurate measurement of key biometric parameters and the early detection of abnormalities. Manual segmentation is prone to variability due to factors such as operator skill, image quality, and acquisition conditions. This study compares conventional and deep learning-based segmentation methods, proposing an enhanced Multi-Feature Pyramid U-Net (MFP-Unet) to improve accuracy, robustness, and clinical applicability.
Methods We utilised the HC18 Grand Challenge Dataset, which comprises 1,334 ultrasound images from 551 pregnancies without growth abnormalities. The proposed MFP-Unet integrates multi-scale feature pyramid fusion, dilated convolutions, and attention gates into the U-Net framework. Performance was compared with Dilated U-Net, U-Net, RU-Net, Attention U-Net, and R2U-Net using Dice Coefficient, Intersection over Union (IoU), and mean Average Precision (mAP). Preprocessing included Niblack’s adaptive thresholding and custom region extraction for femur length images.
Results MFP-Unet achieved the highest accuracy across all parameters: HC IoU = 90% (Dice = 0.95), FL IoU = 93% (Dice = 0.97), BPD IoU = 88% (Dice = 0.93), and overall mAP = 0.92. The architecture formed smoother anatomical boundaries, enhanced robustness to image variability, and compact measurement variations associated with other methods.
Conclusions The MFP-Unet approach shows strong promise for use in clinical fetal ultrasound analysis, offering reliable and precise biometric measurements that can aid in timely interventions and enhance prenatal care outcomes. Future research should validate performance on multi-centre datasets and explore real-time deployment.

Intelligent Sonographic Identification of Closed Fractures Using Deep Learning

Sun Siguo, Huang Jiahui, Ma Bin, Liu Zemin, Liu Xi

2026, 10 (3): 223-231. DOI:10.26599/AUDT.2026.260033

Abstract ( 16 ) HTML ( 1 ) PDF ( 4594KB ) ( 4 ) 　　

Objective Closed limb fractures are highly prevalent in disaster rescue scenarios, frontline battlefields, and routine military training. Their diagnosis and treatment require significant expertise and timeliness, as missed or delayed diagnosis can lead to more severe secondary trauma. This study aimed to utilize deep learning and ultrasonography for identifying closed limb fractures, constructing an intelligent sonographic recognition model and evaluating its diagnostic value.
Methods A total of 173 patients with X-ray confirmed closed limb fractures and 122 healthy volunteers were enrolled in. Collected ultrasound images were used for deep learning feature extraction. An intelligent diagnostic model for limb fractures based on DenseNet121 was constructed. Model performance was evaluated using accuracy, sensitivity, specificity, precision, and F1-Score.
Results For bone classification (6-class), the model achieved accuracy of 90%, sensitivity of 85%, and F1-Score 85%. For fracture/non-fracture classification (2-class), the results were 99% accuracy and 99% F1-Score.
Conclusion The DenseNet121-based model demonstrated promising results in identifying closed limb fractures from ultrasound images. The model may hold potential for aiding rapid identification and triage in emergency settings.