Expert review of medical devices最新文献

Introduction: Essential tremor (ET) is a common neurological disorder characterized by involuntary, rhythmic shaking, primarily of the hands. While not life-threatening, ET significantly impairs quality of life. Pharmacological treatments, like beta-blockers or anticonvulsants, often have limited efficacy, leading patients to more aggressive alternatives such as surgical intervention. Recently, magnetic resonance-guided focused ultrasound has emerged as an alternative to surgical procedures, offering incisionless lesioning of the thalamus, resulting in immediate and sustained tremor reduction.

Areas covered: This review explores the MRgFUS technique in the treatment of ET, reviewing clinical efficacy, safety, and procedural advances. A literature search was conducted using PubMed for articles published between January 2015 and March 2024, with the terms: 'MRgFUS,' 'essential tremor,' 'focused ultrasound thalamotomy,' and 'bilateral thalamotomy.' Key points such as patient selection, skull density ratio, monitoring, thermal effects and tractography are discussed.

Expert opinion: MRgFUS has transformed the treatment of ET by providing a precise, incisionless alternative now included in clinical guidelines. Challenges such as SDR limitations or restricted approved-indications limit its extended use. Advances in targeting, thermometry and other biological effects such as histotripsy could expand accessibility and indications. By 2035, MRgFUS could become a standard outpatient procedure for ET and other brain disorders.

Introduction: Over the last several decades, echocardiography has made numerous technological advancements, with one of the most significant being the integration of artificial intelligence (AI). AI algorithms assist novice operators to acquire diagnostic-quality images and automate complex analyses.

Areas covered: This review explores the integration of AI into various echocardiographic modalities, including transthoracic, transesophageal, intracardiac, and point-of-care ultrasound. It examines how AI enhances image acquisition, streamlines analysis, and improves diagnostic performance across routine, critical care, and complex cardiac imaging. To conduct this review, PubMed was searched using targeted keywords aligned with each section of the paper, focusing primarily on peer-reviewed articles published from 2020 onward. Earlier studies were included when found to be foundational or frequently cited. The findings were organized thematically to highlight clinical relevance and practical applications.

Expert opinion: Challenges persist in clinical application, including algorithmic bias, ethical concerns, and the need for clinician training and AI oversight. Despite these, AI's potential to revolutionize cardiovascular care through precision and accessibility remains unparalleled, with benefits likely to far outweigh obstacles if appropriately applied and implemented in cardiac ultrasonography.

Introduction: Benign prostate hyperplasia (BPH) is common among men. Typical treatments include lifestyle modifications, medical management, and surgical therapy, including minimally invasive surgical therapies (MIST). iTind is a new minimally invasive option for treating BPH.

Areas covered: This review is an objective assessment of the iTind device for BPH, based on published studies. The authors searched major databases for published articles that included 'iTind' and related search terms. A market overview, safety, efficacy, and durability of the device is discussed. Alternatives are compared and contrasted.

Expert opinion: iTind is a safe option for the treatment of BPH in select populations, specifically those who wish to preserve ejaculatory function. It has been shown to be efficacious in treating BPH symptoms; however, available data suggest a higher rate of retreatment when compared to traditional surgery. Emerging long-term data will provide a better understanding of long-term results.

Objective: This paper aims to compare the diagnostic value of 24-hour Holter monitoring and conventional electrocardiogram (ECG) in arrhythmia.

Methods: The diagnostic results of 24-hour Holter monitoring and conventional ECG for these patients were compared. The diagnostic efficacy, including sensitivity, specificity, and accuracy, of the two types of ECGs was compared. Additionally, the detection rates of ventricular premature contractions in bigeminy and trigeminy, paired ventricular premature contractions, atrial premature contractions in bigeminy and trigeminy, paired atrial premature contractions, and atrioventricular conduction block by both methods were compared. Patient satisfaction with the diagnostic results of two methods was also compared.

Results: Compared to the conventional ECG, 24-hour Holter monitoring exhibited higher sensitivity, specificity, and accuracy; higher detection rates of ventricular premature contractions in bigeminy and trigeminy, paired ventricular premature contractions, atrial premature contractions in bigeminy and trigeminy, paired atrial premature contractions, and atrioventricular conduction block; higher patient satisfaction.

Conclusion: The 24-hour Holter monitoring demonstrates superior sensitivity, specificity, accuracy, and detection rate in diagnosing arrhythmia compared to conventional ECG. Additionally, it offers higher patient satisfaction, making it more valuable for clinical application.

Introduction: Functional electrical stimulation (FES) is a therapeutic tool that may augment motor recovery after spinal cord injury/disease (SCI). It involves applying an electrical current to muscles and/or peripheral nerves to facilitate functional movements, such as walking and reaching. Despite the potential therapeutic benefits of FES, and the considerable investment into its research and development, FES is not widely used in clinical practice.

Areas covered: In this narrative review, we examine this research-to-practice gap. PubMed and Google Scholar were searched using keywords related to the population, constructs and context of interest. We provide an orientation to SCI and summarize how FES may facilitate motor recovery. Using the Knowledge-to-Action Framework as a guide, we demonstrate how co-design and implementation strategies can be incorporated into FES device development and research to aid clinical translation in SCI rehabilitation. Based on prior literature, we provide recommendations for researchers and technology developers: 1) collaborate with implementation scientists, 2) adopt participatory methods, 3) use a knowledge translation framework as a guide, 4) thoroughly understand implementation barriers and facilitators, and 5) budget time for implementation.

Expert opinion: Greater focus on clinical implementation is needed in the FES research field to address the current research-to-practice gap.

Introduction: With the ever-expanding increase in the availability of electronic devices that can monitor everything from a patient's daily step count to more detailed devices that can measure or estimate pulmonary artery pressures in patients with heart failure, the amount of data measured by these devices produces mountains of information.

Areas covered: Our review will examine the various options and developments of both consumer-facing and professional medical devices. We discuss provider-facing cardiac devices including pacemakers, implantable cardioverter-defibrillators, Holter monitors, implantable loop recorders, left ventricular assist devices, patch monitors, and pulmonary artery pressure sensors, as well as consumer-facing cardiac medical devices including the Apple Watch and the Fitbit wearable device. We searched through the available studies on the PubMed, Cochrane Library, and Embase databases for information on these devices. The role of artificial intelligence in the analysis and interpretation of data currently and in the future is also discussed.

Expert opinion: We expect future consumer-facing cardiac medical devices to focus on ventricular arrhythmias especially given their clinical impact. We also expect clinical data and patient-specific information to play a larger role as artificial intelligence advances, and it becomes more capable of drawing conclusions using multiple variables from a single patient.

Introduction: Contrast-enhanced ultrasound (CEUS) is performed to non-invasively confirm a diagnosis of hepatocellular carcinoma (HCC) in high-risk patients. Typical imaging characteristics for HCC include non-rim arterial phase hyperenhancement (APHE), a washout appearance during the portal phase, and a defect in the Kupffer phase on CEUS using perflubutane microbubbles (Sonazoid). CEUS can show high diagnostic accuracy for HCC; however, we sometimes encounter challenging situations for diagnosing HCC.

Areas covered: Some HCCs do not show APHE or the washout appearance, and other hepatic malignancies may exhibit similar imaging findings and be misdiagnosed as HCC. In addition, HCC needs to be differentiated from various types of hypervascular benign liver lesions. This review focuses on atypical imaging findings for HCC and typical imaging findings for common mimics of HCC as well as appropriate diagnostic workups for these lesions. Additionally, the literature review methodology, encompassing searches in PubMed, from January 1995 to January 2025, is briefly outlined.

Expert opinion: Clinicians need to carefully consider the histopathological features, imaging characteristics, and differential diagnoses of hypervascular liver lesions in order to prevent a misdiagnosis and select appropriate treatment plans. A detailed understanding of typical and atypical imaging features may prevent the false-positive diagnosis of HCC.

Introduction: The integration of Artificial Intelligence (AI) and Machine Learning (ML) has significantly enhanced the development of self-healing composites, especially in biomedical fields including tissue engineering, medication delivery, and implantable devices. These materials are designed to self-repair damage, enhancing durability, patient safety, and operational reliability. Considering that traditional materials may deteriorate under physiological conditions, intelligent self-healing composites augmented by AI/ML offer a revolutionary alternative.

Areas covered: This work examines current progress in AI- and ML-facilitated design, selection, and optimization of self-healing composites for biomedical applications. Attention is directed toward the application of supervised and unsupervised learning methodologies - such as Bayesian optimization, neural networks, and support vector machines to improve healing efficiency by 30-50%, decrease formulation time by approximately 40%, and achieve predictive accuracies of over 90% regarding failure or healing behavior in specific studies.

Expert opinion: The research examines ethical aspects, encompassing data protection, algorithmic transparency, and adherence to regulatory standards such as FDA and ISO 10,993. The paper emphasizes the transformational potential of AI/ML in facilitating intelligent, responsive, and patient-specific composite designs, while also addressing possible issues such as dataset bias and algorithmic opacity. The results indicate that AI-enhanced self-healing systems will be pivotal in the future of customized medicine.