Array-based ultrasound combines bedside access with flexible spatial sampling for neurovascular monitoring and vascular characterization. This Clinical Application Review links array design, acoustic access, acquisition, reconstruction, and physiological interpretation across transcranial Doppler, functional ultrasound, contrast-enhanced ultrasound, and ultrasound localization microscopy. Array geometry and acoustic access determine spatial sampling, whereas acquisition windows, physiological response times, and reconstruction pipelines jointly determine the temporal information available for monitoring. Together, these constraints explain why arterial-velocity tracking, regional functional imaging, and microvascular characterization require different system designs and validation strategies. Clinical studies demonstrate complementary gains: robotic and conformal systems extend arterial targeting and recording, intraoperative functional ultrasound maps task-related hemodynamics, and localization microscopy reveals small vessels beyond conventional Doppler in selected patients. Ultrafast acquisition supports these applications by increasing temporal sampling; functional ultrasound uses hemodynamic signals to investigate functional changes. We compare engineering parameters, reported timings, measurement agreement, and clinical information gained, and identify trade-offs involving skull calibration, motion, systemic physiology, and microbubble sampling. Established large-artery monitoring and emerging microvascular characterization occupy different stages of translation; continuous quantitative perfusion monitoring through the intact adult skull remains an unresolved objective.
Thirty years on from the introduction of deep brain stimulation as a therapy for Parkinson’s disease, adaptive deep brain stimulation (aDBS) is poised to transform neural stimulation for the treatment of motor disorders. Implementation of aDBS has been facilitated by the identification of biomarkers that reflect patients’ clinical states and the introduction of hardware allowing simultaneous sensing and stimulation. However, the most appropriate algorithms for aDBS remain unclear. This review provides an overview of control algorithms used in computational, animal and human studies of aDBS in Parkinson’s disease to date. Although shown to be effective and well-tolerated, only relatively simple aDBS algorithms have been used clinically. Computational studies have explored a wider range of more advanced algorithms which promise superior performance but need to be rigorously tested and compared against clinically-tested techniques before translating to patients. The need for comparative studies is further driven by advances in machine learning, which promise patient-specific programming solutions but require large datasets and have high computational requirements. Understanding the advantages and limitations of these different algorithms is critical for aDBS to reach its potential and enable personalized treatment to provide maximum patient benefit.
Microfluidic technology offers a transformative approach for biomedical diagnostics by enabling miniaturization and automation of analytical procedures. Its integration into Point-of-Care Testing (POCT) holds promise for rapid, decentralized, and accessible diagnostics. However, translating laboratory microfluidics into practical POCT devices faces key challenges, including the handling of complex clinical samples, integration of multiple functions on a single chip, ensuring reliable analytical performance in clinical deployment scenarios, and meeting regulatory requirements. This review explores the evolution of microfluidic technology and the unique requirements for POCT, while highlighting the main challenges in translating laboratory systems into practical applications. Representative case studies and recent technological advances are presented to illustrate progress and solutions, and future directions are discussed with a focus on strategies to bridge the gap between laboratory research and effective, real-world POCT deployment.
Ultrasound Computed Tomography (USCT) represents a paradigm shift in medical imaging, offering quantitative, high-resolution tissue characterization for diverse anatomical regions including breast, musculoskeletal system, brain, and lungs. By capturing the full ultrasonic wavefield through dedicated transducer arrays, USCT enables reconstruction of intrinsic tissue properties such as sound speed, attenuation, and acoustic impedance. Unlike conventional ultrasound, USCT provides three fundamental advantages: full-angle tomographic reconstruction, quantitative multi-parameter imaging capabilities, and operator-independent standardized acquisition—all while maintaining ultrasound’s inherent safety and cost-effectiveness. While clinical adoption is still evolving, the technology has achieved significant milestones with several commercially available systems receiving regulatory approval for breast imaging. This review synthesizes recent advances across five critical domains: system hardware design, reflection imaging, quantitative multi-parameter reconstruction (particularly through full-waveform inversion), precision calibration methodologies, and expanding clinical applications. Additionally, we have offered a comprehensive review of the application of deep learning-related technologies in USCT. By comprehensively analyzing current challenges and emerging trends, this work provides researchers and clinicians with an essential reference for understanding the state of the art and identifying pivotal pathways toward widespread clinical implementation of USCT technology.
Invasive medical interventions or abrupt reductions in ambient pressure can result in intravascular gas embolism. The accumulation of gas bubbles initiates a cascade of pathophysiological phenomena progressing from platelet activation to ischemia and neurological dysfunction. This review integrates current knowledge of the biophysical mechanisms of bubble nucleation, progression, and vascular occlusion into a framework aligned with the adverse physiological consequences on circulation. The discussion further addresses the present state of clinical practice, diagnostic approaches, and therapeutic interventions. Initial studies on gas embolism utilized in vivo models, and recent in vitro and in silico platforms have provided reproducible and cost-efficient experimental approaches. The initial symptoms of gas embolism often overlap with stroke, myocardial infarction, or sepsis. Reliable detection of intravascular gas bubbles is constrained by the sensitivity, resolution, and accessibility of existing imaging modalities, particularly in systemic cases. Current treatment frameworks emphasize hyperbaric oxygen therapy, while adjunct pharmacological strategies to improve clinical outcomes are under investigation. The challenges responsible for the persistent neglect of gas embolism in both clinical and academic contexts are discussed, and a forward-looking perspective on strategies to overcome these barriers is presented.
