Physics Insights into Liver MRI: Educational Guidance for Protocol Optimization.

Accelerating prostate MRI: a practical review of modern acquisition strategies.

WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion.

OBJECTIVE Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or magnetic resonance imaging (MRI), using electromagnetic (EM) tracking to enable precise spatial correlation between modalities. This technology is increasingly used for liver imaging and interventions, especially when conventional B-mode US fails to provide adequate lesion visualization. The aim of this technical review and position statement is to evaluate the technical accuracy (target registration errors) and lesion visibility of ultrasound fusion imaging based on published evidence and expert consensus. METHODS This manuscript was designed as the technical component of a two-part World Federation for Ultrasound in Medicine and Biology (WFUMB) position statement. A systematic review was conducted using a PICO framework focused on two core questions: (i) to evaluate EM-tracked fusion target registration errors (PICO T1), and (ii) whether fusion improves visibility of lesions in difficult-to-image liver lesions (PICO T2). Literature from January 2012 to January 2025 was searched across PubMed, Scopus, Embase, and IEEE Xplore, with manual citation tracking and AI-assisted query generation. Eligible studies included research on US/CEUS fusion with CT/MRI, reporting technical accuracy and lesion conspicuity. RESULTS The technical accuracy of fusion imaging was consistently high, with target registration errors (TRE) of ∼1-3 mm in ideal phantom settings and ∼4-14 mm in clinical studies. Automatic registration methods were faster and similarly accurate as manual registration, possibly reducing operator dependence. Fusion imaging improved the detectability of lesions not visible (occult) on conventional B-mode US, increasing the diagnostic yield and enabling successful interventions (e.g., ablation) in up to 90%-95% of cases. Safety profiles across studies were favorable, with major complication rates generally below 2%. Furthermore, fusion imaging might prove especially beneficial for treating tumors in difficult locations (e.g., caudate lobe, peribiliary lesions). CONCLUSION Ultrasound fusion imaging significantly enhances the spatial accuracy of liver interventions by aligning real-time US with CT/MRI datasets. It improves interventional procedures guidance and maintains a low complication profile as compared to conventional US alone. Advancements in artificial intelligence (AI) and augmented reality (AR) are expected to further optimize image co-registration workflows and clinical outcomes. This technical review supports the broader adoption of fusion imaging as a key tool in liver imaging and intervention.

Diagnostic Value and Operational Recommendations for Late Iodine Enhancement and ECV Quantification in Single-Energy Computed Tomography: A Narrative Review

While traditionally focused on coronary anatomy, cardiac computed tomography now enables non-invasive myocardial tissue characterization. By evaluating late iodine enhancement (LIE) and extracellular volume (ECV), single-energy CT (SECT) provides a valuable alternative to cardiac magnetic resonance for assessing ischemic and non-ischemic pathologies. However, clinical implementation of SECT faces technical challenges, primarily the low contrast-to-noise ratio (CNR) of iodine and the reliance on image subtraction for ECV quantification, both of which increase radiation exposure and susceptibility to spatial misregistration. To address these issues, protocol optimization is essential. Evidence-based recommendations include using low tube voltages to shift the X-ray spectrum closer to the iodine K-edge, paired with high reference tube currents. Additionally, delayed acquisition timing should be tailored to specific pathological targets to account for differences in contrast kinetics, and advanced iterative or deep learning image reconstructions should be implemented to mitigate noise. Optimized SECT demonstrates diagnostic and prognostic utility in conditions like acute myocardial infarction, hypertrophic cardiomyopathy, cardiac amyloidosis, and left ventricular thrombus detection. While spectral imaging represents the future, optimizing SECT through technical adjustments and standardized training is crucial for integrating myocardial characterization into routine workflows.

Optimized Coherence Masking Improves Ultrasound Imaging of Kidney Cysts.

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.

Dual-Energy CT: Current Principles, Clinical Applications, And Future Perspectives

Dual-energy computed tomography (DECT) has transformed modern computed tomography by enabling the acquisition of imaging data at two different energy spectra, thereby providing additional diagnostic information beyond conventional single-energy CT. By exploiting energy-dependent attenuation differences among tissues and materials, DECT allows improved tissue characterisation, material differentiation, and quantitative analysis. Recent technological developments, including dual-source systems, rapid kVp-switching techniques, dual-layer detector technology, and photon-counting CT, have significantly enhanced the clinical applicability of spectral imaging. Advanced reconstruction methods such as virtual monoenergetic imaging, virtual non-contrast imaging, iodine mapping, and material decomposition have expanded the diagnostic capabilities of DECT. These techniques improve lesion conspicuity, reduce imaging artefacts, optimize contrast enhancement, and provide valuable functional information.  As a result, DECT has found widespread applications in cardiothoracic, abdominal, gastrointestinal, musculoskeletal, neurological, oncological, and emergency imaging. Despite its advantages, challenges such as high equipment costs, variability among imaging platforms, and the need for standardised protocols continue to influence its broader implementation. Ongoing advancements in artificial intelligence, radiomics, quantitative imaging biomarkers, and photon-counting technology are expected to improve diagnostic accuracy and clinical utility further.  This review highlights the fundamental principles, technological developments, clinical applications, advantages, limitations, and prospects of DECT, emphasising its growing role in precision imaging and contemporary radiological practice.  

Optimizing gadolinium-enhanced CNS MRI: From physics to clinical practice.

Gadolinium-based contrast agents (GBCAs) are essential for the evaluation of central nervous system (CNS) disorders, enhancing lesion detection, characterization, and therapeutic monitoring. Despite their widespread use and overall safety, their application in daily practice may be, in some cases, suboptimal due to technical or interpretative issues, including incorrect dosing, inadequate timing of acquisition, and sequence parameter adjustments. Although multiple GBCAs demonstrate comparable diagnostic performance, safety concerns such as hypersensitivity reactions, nephrogenic systemic fibrosis, and gadolinium retention have led to increasing emphasis on optimized and justified use. Regulatory differences between agencies, alongside growing preference for macrocyclic agents, reflect efforts to balance diagnostic benefit and safety. From a physicochemical standpoint, relaxivity, molecular structure, and pharmacokinetics critically influence imaging performance, particularly through T1 signal enhancement. Recent advances support dose reduction strategies, especially with high-relaxivity agents, without compromising diagnostic accuracy. Technical factors, including magnetic field strength, acquisition timing, and sequence selection, further modulate enhancement quality. Beyond conventional imaging, advanced techniques such as perfusion MRI (Dynamic Susceptibility Contrast and Dynamic Contrast Enhanced), Dixon imaging, black-blood sequences, and susceptibility-weighted imaging provide complementary physiological and structural information, enhancing diagnostic precision. These approaches enable more efficient use of GBCAs and increase diagnostic accuracy. Moreover, emerging artificial intelligence applications may further transform contrast utilization by enabling high-quality imaging at lower doses. In conclusion, a comprehensive, technically optimized, and physiologically informed approach to GBCA use is crucial to maximizing diagnostic yield while minimizing potential risks in CNS MRI.