OBJECTIVES
Renal cystic lesions are exceedingly common and typically benign, though accurate diagnostic techniques are required to recognize the subset of malignant lesions that require timely intervention. Ultrasound (US) is the preferred first line test for renal cyst evaluation because it is safe, widely accessible, and low cost. US imaging, however, is limited in individuals with obesity, as subcutaneous fat introduces imaging artifacts (eg, aberration) that obscure features critical for assessing a cyst's malignant potential.
METHODS
In this work, we propose a 2-stage image-correction algorithm to improve the resolution, contrast, and potential diagnostic utility of US images of renal cysts. The method combines sound speed correction for beamforming with masking based on the spatial coherence of the beamformed signals.
RESULTS
In a pilot cohort of 10 subjects, we observed improved image sharpness and contrast-to-noise ratio in nearly all cases compared to baseline images (mean improvements of approximately 5 and 10%, respectively). Additionally, 2 expert readers preferred nearly universally the corrected images in a blinded review.
CONCLUSION
Together, the results from this pilot study suggest that our method has translational potential to improve US image quality and enhance clinical confidence in managing the common and clinically important challenge of renal cysts.
S. Schoen, Theodore T. Pierce, Sai Dhanush Reddy Jeggari et al.· Journal of ultrasound in med...· 0 citations
Highlights What are the main findings? Portable MRI enabled safe bedside imaging in emergency and intensive care settings, although detection of very small (<5–6 mm) ischemic lesions remained less reliable than conventional high-field MRI. Diagnostic performance was influenced by lesion size and field strength, with low-field MRI reliably detecting most clinically relevant infarcts. What are the implications of the main findings? Low-field and portable MRI can expand timely access to stroke imaging where conventional MRI is unavailable, delayed, or unsafe, particularly in emergency departments, ICUs, and resource-limited settings. Continued improvements in hardware, imaging sequences, and multicenter validation studies are needed before low-field MRI can be adopted as a routine alternative to conventional high-field MRI for acute stroke evaluation. Abstract Background: Magnetic resonance imaging (MRI) has a central role in acute ischemic stroke (AIS) and transient ischemic attack (TIA) diagnosis; however, conventional high-field MRI remains limited by infrastructure requirements, patient transport, and restricted accessibility. Low-field and portable MRI systems have emerged as potential solutions for point-of-care neuroimaging in emergency, intensive care, and resource-limited settings. Methods: A systematic review was conducted according to PRISMA 2020 guidelines. PubMed, Scopus, Web of Science, and Cochrane Library databases were searched from inception through May 2026. Studies evaluating low-field or portable MRI systems (≤0.55 T) in adults with AIS, TIA, sub-acute ischemic stroke, or suspected stroke were included. Diagnostic accuracy, feasibility, safety, workflow, and clinical utility outcomes were extracted. Risk of bias was assessed using QUADAS-2. Results: Eleven studies encompassing portable and low-field MRI platforms ranging from 0.064 T to 0.55 T were included. Portable MRI demonstrated feasibility in bedside ICU and emergency department settings without major device-related adverse events. Diagnostic performance varied by field strength, lesion size, and imaging protocol. Conclusions: Low-field and portable MRI show promising diagnostic potential for AIS and TIA, particularly when conventional MRI is unavailable, delayed, or impractical. However, current evidence is limited by small, predominantly single-center studies with substantial risk of bias, and further prospective multicenter validation is required before these technologies can be incorporated into routine clinical decision-making.
Rachana R. Borkar, Sai Dhanush Reddy Jeggari, Kamal Kandel et al.· Brain Science· 0 citations
