CONTENTS

Cover, Foreword and Content
2024, 8 (4): 0-0.
Abstract ( 18 ) PDF ( 785KB ) ( 21 ) 　　

Review Articles

Noninvasive Evaluation of Left Ventricular-Arterial Coupling: Methodologies and Clinical Relevance

Xin Zhang, MD, Yun Yang, MD, Ruize Zhang, MD, Linyue Zhang, MD, Yuji Xie, MD, Wenqian Wu, MD, PhD, Jing Zhang, MD, PhD, Qing Lv, MD, PhD, Jing Wang, MD, PhD, Mingxing Xie, MD, PhD

2024, 8 (4): 149-158. DOI:10.37015/AUDT.2024.240063

Abstract ( 39 ) HTML ( 2 ) PDF ( 2463KB ) ( 35 ) 　　

Left ventricular-arterial coupling (VAC) is essential for understanding both cardiovascular physiology and pathophysiology. Traditionally assessed through invasive techniques, recent advancements have introduced noninvasive methods that employ imaging modalities and physiological parameters to evaluate ventricular pressure, volume, and arterial load characteristics. This review examines commonly used noninvasive VAC assessment methods, including echocardiographic single-beat method, myocardial work, wave intensity, the ratio of pulse wave velocity to global longitudinal strain, and imaging-based pressure-volume loops. These methodologies have demonstrated potential in clinical applications, such as evaluating cardiac function, personalizing treatment plans, monitoring therapeutic effects, and assessing prognosis. The incorporation of advanced imaging and computational techniques is anticipated to further enhance the accuracy and clinical relevance of VAC assessment in the management of cardiovascular diseases.

Left Ventricular-Arterial Coupling in Cardiovascular Health: Development, Assessment Methods, and Future Directions

Anni Chen, MS, Lan Yang, MS, Zhenyi Li, MS, Xinqi Wang, MS, Ya Chen, MS, Lin Jin, MD, Zhaojun Li, MD

2024, 8 (4): 159-171. DOI:10.37015/AUDT.2024.240057

Abstract ( 35 ) HTML ( 2 ) PDF ( 538KB ) ( 43 ) 　　

Left ventricular-arterial coupling (LVAC) represents a critical physiological mechanism that characterizes the interaction between left ventricular (LV) contractility and the arterial system's resistance and elasticity. The balance within LVAC is essential for efficient energy transfer from the heart, which underpins optimal cardiovascular function. In a healthy state, the balance between LV contractility and arterial elasticity and resistance allows the heart to maintain normal circulation with minimal energy expenditure. However, with the progression of age and diseases such as atherosclerosis and hypertension, arterial stiffness increases, LV function decreases, and the LVAC balance is disrupted, leading to a significantly increased risk of cardiovascular events. This imbalance is particularly significant in patients with heart failure (HF) and coronary artery disease (CAD), where LVAC imbalance is strongly associated with increased cardiac load and decreased energy efficiency. Thus, understanding and evaluating LVAC are crucial for elucidating cardiovascular physiology and guiding therapeutic strategies for diseases such as HF, hypertension, and CAD. Methods for assessing LVAC include invasive pressure-volume loops and cardiac catheterization, as well as non-invasive techniques such as echocardiography and arterial pulse wave analysis (PWA). Despite the higher accuracy of invasive methods, non-invasive methods are commonly used in clinical practice to assess LVAC because of their lower risk. With cardiac magnetic resonance imaging (CMR) and 3D/4D imaging techniques advancing, more precise structural and functional analysis of the heart and arterial system will be possible in the future. In this review, we describe the physiological mechanisms, assessment methods, influencing factors, and clinical significance of LVAC, as well as interdisciplinary studies with biomechanics and metabolism, which provide new ideas for personalized treatment of LVAC.

Current Status and Progress in Arterial Stiffness Evaluation: A Comprehensive Review

Yun Yang, MD, Xin Zhang, MD, Ruize Zhang, MD, Jingrong Jiang, MD, Yuji Xie, MD, Lingyun Fang, MD, PhD, Jing Zhang, MD, PhD, Mingxing Xie, MD, PhD, Jing Wang, MD, PhD

2024, 8 (4): 172-182. DOI:10.37015/AUDT.2024.240064

Abstract ( 30 ) HTML ( 2 ) PDF ( 911KB ) ( 33 ) 　　

Arterial stiffness (AS) represents a pathological process characterized by reduced arterial elasticity and compliance, closely linked to aging and cardiovascular diseases, including hypertension, atherosclerosis, diabetes, and chronic kidney disease. As an important predictor of cardiovascular risk, AS evaluation plays a crucial role in early detection, disease monitoring, and therapeutic guidance. This review aims to systematically summarize current advancements in AS evaluation, focusing on non-invasive techniques such as pulse wave velocity, ultrasound-based methods, and arterial pressure waveform analysis. We discuss the advantages, limitations, and clinical applications of these methods, highlighting the recent integration of artificial intelligence and machine learning to enhance diagnostic accuracy and automation. The review also explores emerging biomarkers and novel imaging techniques, such as shear wave elastography and ultrafast ultrasound imaging, which offer promising insights for early AS detection and risk stratification. Despite significant progress, challenges remain in standardizing measurement protocols and improving sensitivity across various populations. Future research directions emphasize the development of wearable technologies, artificial intelligence-based diagnostic tools, and standardized methodologies to advance AS evaluation and improve cardiovascular outcomes.

The Application and Research Progress of Cardiac Magnetic Resonance in the Assessment of Right Ventricular-Pulmonary Arterial Coupling

Ya Chen, MS, Xinqi Wang, MS, Anni Chen, MS, Zhenyi Li, MS, Lan Yang, MS, Zhaojun Li, MD, Lin Jin, MD, Xifu Wang, MD

2024, 8 (4): 183-194. DOI:10.37015/AUDT.2024.240062

Abstract ( 27 ) HTML ( 1 ) PDF ( 1193KB ) ( 21 ) 　　

Right ventricular-pulmonary arterial coupling refers to the interaction and functional matching between the right ventricle and the pulmonary artery. When the coupling is disrupted, it can lead to a series of cardiovascular diseases, such as pulmonary hypertension, congenital heart disease, heart failure and so on. Therefore, it is important to evaluate cardiovascular structure and function. Cardiac magnetic resonance has the advantage of multi-parameter, multi-sequence, and high-resolution imaging, which can be used to comprehensively evaluate the cardiovascular system through cardiac magnetic resonance feature tracking technology, cardiac magnetic resonance cine imaging technology, T1 mapping, and T2 mapping imaging, and so on. This review summarizes the application and research progress of cardiac magnetic resonance technology in the assessment of the right ventricle and the pulmonary artery (RV-PA) coupling.

Left and Right Ventricular Interaction: Insight from Echocardiography Imaging

Zhenyi Li, MS, Ya Chen, MS, Xinqi Wang, MS, Lan Yang, MS, Anni Chen, MS, Zhaojun Li, MD, Lin Jin, MD

2024, 8 (4): 195-204. DOI:10.37015/AUDT.2024.240058

Abstract ( 27 ) HTML ( 2 ) PDF ( 826KB ) ( 29 ) 　　

The left ventricle (LV) and right ventricle (RV) are interdependent, as both structures are nestled within the pericardium, share a common septum, and are encircled by interconnected myocardial fibers. Interventricular interaction refers to the dynamic relationship between LV and RV, particularly how changes in one ventricle influence the geometry and function of the other. Imaging, particularly echocardiography, is vital for characterizing interventricular interactions by assessing geometric indices, septal motion, Doppler flow patterns, and changes in strain, remodeling, and diastolic filling associated with the loading conditions of the contralateral ventricle. In this review, we summarized the physiological and anatomical basis of ventricular interaction, echocardiographic imaging indices, and their clinical utilities and limitations. The goal is to systematically review the research advancements in echocardiographic assessment of LV-RV coupling and to provide guidance for clinical practice.

Evaluation Methods and Progress of Right Ventricular-pulmonary Artery Coupling

Xinqi Wang, MS, Anni Chen, MS, Lan Yang, MS, Ya Chen, MS, Zhenyi Li, MS, Zhaojun Li, MD, Lin Jin, MD

2024, 8 (4): 205-216. DOI:10.37015/AUDT.2024.240059

Abstract ( 32 ) HTML ( 2 ) PDF ( 858KB ) ( 22 ) 　　

Right ventricular-pulmonary artery coupling (RV-PAC) serves as an indicator of the efficiency of energy transfer from the right ventricle to the pulmonary circulation. It plays a critical role in the diagnosis, clinical treatment, and prognosis of conditions such as pulmonary hypertension, heart valve disease, and heart failure. Various non-invasive evaluation methods have recently been proposed for assessing RV contractility and arterial afterload, based on the end-systolic elastance to arterial elastance ratio (Ees/Ea), which is derived from invasive pressure-volume loops. In this review, we summarize the fundamental concepts, physiological mechanisms, examination methods, influencing factors, and clinical significance of RV-PAC to provide a valuable reference for clinical practice.

Precision Imaging for Prostate Cancer Localization: How Multiparametric Ultrasound Stands Against Multiparametric MRI

Amr Mohammed, MD, Priscilla Machado, MD, Tania Siu Xiao, MD, Aylin Tahmasebi, MD, Mostafa Alnoury, MD, Edouard Trabulsi, MD, Ethan J. Halpern, MD, John R. Eisenbrey, PhD, Flemming Forsberg, PhD

2024, 8 (4): 217-230. DOI:10.37015/AUDT.2024.240047

Abstract ( 32 ) HTML ( 3 ) PDF ( 2761KB ) ( 19 ) 　　

Multiparametric MRI (mpMRI) is currently the standard imaging modality for the diagnosis of prostate cancer; however, studies have reported that targeted biopsy based on mpMRI may miss approximately 30% of clinically significant cases. Recent advances in ultrasound imaging have improved its accuracy for detection of prostate cancer. Newer techniques such as MicroUS, elastography, contrast-enhanced ultrasound (CEUS), and contrast ultrasound dispersion imaging (CUDI) have enabled a comprehensive, real-time, and relatively inexpensive approach to evaluate the prostate gland. Multiparametric ultrasound (mpUS) integrates multiple parameters from these techniques to generate multiparametric maps akin to those produced by mpMRI, to localize prostate cancer. This review aims to explore the performance of modern ultrasound techniques and mpUS for diagnosis of prostate cancer, comparing them with mpMRI.

Advancements in BaTiO₃-Based Ultrasound‐Triggered Piezoelectric Catalysis for Tumor Therapy

Shiti Shama, PhD, Xinxin Xie, MD, Ruiqi Wu, MD, Ping He, MD, Xiaoda Li, PhD, Qingfeng Chen, PhD, Xiaolong Liang, PhD

2024, 8 (4): 231-241. DOI:10.37015/AUDT.2024.240053

Abstract ( 26 ) HTML ( 3 ) PDF ( 4631KB ) ( 13 ) 　　

Barium titanate (BaTiO₃), as an emerging inorganic piezoelectric material with excellent piezoelectric catalytic effects, has showing advantages in tumor therapy. To achieve ultrasound-regulated tumor treatment using BaTiO₃, researchers have developed strategies including utilizing BaTiO₃ combined with ultrasound for tumor therapy, enhancing reactive oxygen species (ROS) generation through chemical modification of BaTiO₃, and employing combined therapy with other treatment methods. These strategies provide new insights and approaches for non-invasive and precision treatment of tumors. In this review, we first explain the principle of piezoelectric effect based on BaTiO₃. Subsequently, we introduce the application of BaTiO₃ as a piezoelectric material in tumor therapy and its combined therapy with other treatment modalities in tumor treatment. Finally, we summarize the current status and limitations of BaTiO₃ in ultrasound‐triggered piezoelectric therapy for tumors and propose future prospects.

Original Research

Evaluation of Liver Fibrosis on Grayscale Ultrasound in a Pediatric Population Using a Cloud-based Transfer Learning Artificial Intelligence Platform

Amr Mohammed, MD, Aylin Tahmasebi, MD, Sooji Kim, BS, Mostafa Alnoury, MD, Corinne E. Wessner, MS, MBA, RDMS, RVT, Tania Siu Xiao, MD, Sharon W. Gould, MD, Lauren A. May, MD, Heidi Kecskemethy, MS Ed, RDN, CBDT, David T. Saul, MD, John R. Eisenbrey, PhD

2024, 8 (4): 242-249. DOI:10.37015/AUDT.2024.240048

Abstract ( 31 ) HTML ( 3 ) PDF ( 989KB ) ( 21 ) 　　

Objectives: The incidence of chronic liver diseases in children is increasing worldwide due to congenital, metabolic, autoimmune and viral diseases. Currently, liver biopsy for fibrosis assessment is considered the gold standard. However, this procedure is invasive, may result in unavoidable complications and is prone to sampling errors. These limitations have led to an increasing demand for noninvasive methods for fibrosis screening. Artificial intelligence integration in ultrasound diagnosis of liver fibrosis has gained interest in clinical research. In the current study we used a cloud-based artificial intelligence platform utilizing transfer learning to evaluate the accuracy of B-mode ultrasound based AI model compared to pediatric radiologists in detection of liver fibrosis in a pediatric population.
Methods: For this IRB approved study, charts of 190 pediatric patients who were referred for liver biopsy and ultrasound were reviewed. On average 14 images of different liver areas were selected and a single image per decision was used for both radiologist and AI reads. A supervised machine learning model for image classification was developed using Google Vision AutoML (Google Inc., Mountain View, CA, USA). Data was divided for model development (80% of cases (154 cases) = 2324 images) and a model validation cohort for external testing (20% (36 cases) = 360 images). As a comparator, three blinded radiologists read the ultrasound images of the validation cohort and provided a binary diagnosis of fibrosis versus non fibrotic liver appearance. Tissue sampling was used as the reference standard for all cases.
Results: There were 99 and 91 patients in the biopsy proven fibrosis and non-fibrosis group, respectively. The model’s internal evaluation resulted in precision of 78.2%, recall of 78.5% and average precision of 87.7%. In the external validation cohort, three radiologists (Mean ± Standard Deviation) and Google AutoML (confidence interval (CI)) achieved a sensitivity of 42.04% ± 0.04 and 70.56% (63.32% to 77.10% CI), specificity of 50.18% ± 0.04 and 45.00% (37.59% to 52.58% CI), positive predictive value of 45.76% ± 0.01 and 56.19% (52.17% to 60.14% CI), negative predictive value of 46.39% ± 0.01 and 60.45% (53.65% to 66.86% CI) and accuracy of 46.11% ± 0.01 and 57.78% (52.49% to 62.94% CI). When evaluating agreement across multiple images from the same patient, intra-reader agreement was 77.2% for AutoML and 90.8%-92.5% for the 3 radiologists. The models' F1 scores for the development and validation cohort were 0.78 and 0.62, respectively.
Conclusions: Liver fibrosis assessment in children is challenging without biopsy. An ultrasound-based AI model showed high sensitivity compared to radiologists, albeit still without suitable diagnostic performance for clinical use.

Performance of ChatGPT and Radiology Residents on Ultrasonography Board-Style Questions

Jiale Xu, MD, Shujun Xia, MD, Qing Hua, MD, Zihan Mei, MD, Yiqing Hou, MD, Minyan Wei, MD, Limei Lai, MD, Yixuan Yang, MD, Jianqiao Zhou, MD

2024, 8 (4): 250-254. DOI:10.37015/AUDT.2024.240002

Abstract ( 29 ) HTML ( 1 ) PDF ( 760KB ) ( 17 ) 　　

Objective: This study aims to assess the performance of the Chat Generative Pre-Trained Transformer (ChatGPT), specifically versions GPT-3.5 and GPT-4, on ultrasonography board-style questions, and subsequently compare it with the performance of third-year radiology residents on the identical set of questions.
Methods: The study, conducted from May 19 to May 30, 2023, utilized a selection of 134 multiple-choice questions sourced from a commercial question bank for American Registry for Diagnostic Medical Sonography (ARDMS) examinations and imported into the ChatGPT model (encompassing GPT-3.5 and GPT-4 versions). ChatGPT’s responses were evaluated overall, by topic, and by GPT version. An identical question set was assigned to three third-year radiology residents, enabling a direct comparison of performances with ChatGPT.
Results: GPT-4 correctly responded to 82.1% of questions (110 of 134), significantly surpassing the performance of GPT-3.5 (P = 0.003), which correctly answered 66.4% of questions (89 of 134). Although GPT-3.5’s performance was statistically indistinguishable from the average performance of the radiology residents (66.7%, 89.3 of 134) (P = 0.969), there was a notable difference in the accuracy in question-answering accuracy between GPT-4 and the residents (P = 0.004).
Conclusions: ChatGPT demonstrated significant competency in responding to ultrasonography board-style questions, with the GPT-4 version markedly surpassing both its predecessor GPT-3.5 and the radiology residents.

Case Reports

Gastroduodenal Intussusception Due to a Gastric Gastrointestinal Stromal Tumor in Adult from Sonographer's Perspective

Xifeng Ge, MD, Wenzheng Liu, MD, Wen Chen, MD, Fang Mei, MD, Ligang Cui, MD

2024, 8 (4): 255-258. DOI:10.37015/AUDT.2024.230048

Abstract ( 28 ) HTML ( 2 ) PDF ( 1128KB ) ( 19 ) 　　

A gastric GIST which causes gastroduodenal intussusception is rare. A Pubmed search only identified 21 published cases of gastroduodenal intussusception due to gastric GIST. Only 2 of them mentioned ultrasound without further analysis. Here, we report a case of gastroduodenal intussusception due to a gastric GIST with multiple imaging especially ultrasound. A 72-year-old Chinese woman was admitted to hospital because of epigastric pain, black stool lasting and occasional vomiting for 2 months. She underwent abdominal ultrasound, endoscopy, and contrast enhanced CT in turn. Abdominal ultrasound revealed a hypoechoic, medium-sized lesion beside pancreatic head. Endoscopy showed a submucosal lesion of gastric fundus overlapping into duodenum. The lesion manifested slight enhancement in the arterial phase on enhanced CT scans. The patient underwent laparoscopic exploration and partial gastrectomy. The histological examination revealed a low-risk gastric GIST of spindle-shaped cell type.