Diffusion-weighted imaging (DWI) is a fundamental non-contrast sequence in multiparametric breast magnetic resonance imaging (MRI), measuring water diffusion to assess tissue microstructure. The derived apparent diffusion coefficient (ADC) effectively discriminates between malignant lesions, which typically exhibit lower ADC due to high cellularity, and benign ones. Advanced models, such as intravoxel incoherent motion, diffusion kurtosis imaging, restriction spectrum imaging (RSI), and time-dependent DWI, provide further quantification of micro-perfusion and tissue heterogeneity. This review covers technical advancements in DWI (including optimized single-shot echo-planar imaging, ultra-high b-value DWI, and synthetic DWI), its diagnostic performance [RSI achieves an area under the curve (AUC) of up to 0.982; DWI combined with other MRI sequences boosts the AUC to 0.960], and its clinical applications (predicting neoadjuvant chemotherapy response, with an AUC of up to 0.840; correlating with biomarkers such as estrogen receptor, progesterone receptor, and Ki-67; and non-contrast screening with a 99.5% negative predictive value). Artificial intelligence (AI) and radiomics further enhance its utility, with two-dimensional convolutional neural networks performing on par with radiologists (AUC ≈ 0.88). Limitations include artifacts, parameter variability, and poor resolution. Future directions involve ultra-high field MRI and AI-driven analysis. DWI is pivotal for personalized breast cancer care, though standardized protocols and further refinement are needed for broader clinical adoption.
Most artificial intelligence (AI) models used in radiology are black boxes-they produce predictions without explaining the basis of their outputs, raising concerns about clinical safety, accountability, and trust. To address this, a growing body of methods has been developed to help clinicians understand and evaluate AI predictions. This field, known as explainable AI (XAI), aims to help clinicians interrogate, interpret, and critically evaluate AI predictions by identifying factors associated with model outputs. In this educational and practical review, we provide an accessible overview of XAI tailored for practicing radiologists and physicians. We cover the major categories of explanation methods, including saliency maps, perturbation-based and feature-attribution approaches, concept- based methods, and example-based reasoning, as well as uncertainty quantification as a complementary approach for assessing prediction reliability, along with common misconceptions and emerging regulatory obligations. We aim to make XAI easier for healthcare professionals to understand, as effective oversight of AI tools has become a core competency for the modern radiologist.
Pituitary macroadenomas (PMAs) are among the most common intracranial tumors and pose significant surgical challenges, especially when the tumor consistency is increased due to high fibrous content. Accurate preoperative assessment of tumor consistency is crucial for optimizing surgical strategies and patient outcomes. Although conventional T2-weighted magnetic resonance imaging (MRI) is widely employed, its predictive value remains uncertain. Emerging techniques, such as diffusion-weighted imaging and magnetic resonance elastography, provide insights into tumor stiffness by assessing microstructural and mechanical properties, enhancing the prediction of PMA consistency. Furthermore, advancements in machine learning (ML) and deep learning, particularly convolutional neural networks (CNNs) and hybrid CNN-transformer models, have improved the extraction of complex imaging features, leading to greater predictive accuracy. This review summarizes recent developments in MRI and MR-driven imaging techniques for predicting PMA consistency, emphasizing their clinical application and the role of ML-based methods in refining predictive models. Despite numerous candidate imaging biomarkers, the field remains constrained by insufficient reproducibility, limited cross-study comparability, heterogeneity in MRI acquisition and post-processing protocols, and poor model generalizability. Continued integration of advanced MRI with ML-driven imaging analyses may further enhance preoperative prediction of PMA consistency and facilitate surgical planning.
PURPOSE:This study aimed to assess whether multimodal large language models (LLMs) can distinguish cholesteatoma from non-cholesteatomatous chronic otitis media (COM) on representative key-image temporal bone high-resolution computed tomography (HRCT) and to evaluate the short-interval reproducibility of their outputs. METHODS:This retrospective, single-center study (2019-2024) included 101 patients (48 with cholesteatoma, 53 with non-cholesteatomatous COM) who underwent surgical treatment. The reference standard was intraoperative diagnosis with histopathological confirmation for cholesteatoma and surgical documentation for COM. For each case, six anonymized representative HRCT images reflecting standard diagnostic criteria were selected by consensus between a 4th-year radiology resident and a board-certified head and neck radiologist, both unaware of the diagnosis. Subsequently, the same images were analyzed by the GPT-5 and Gemini 2.5 Pro LLMs through their official web interfaces, utilizing structured prompts and a zero-shot approach. These evaluations were conducted in two distinct sessions (S1 and S2) with a 1-week interval. The primary endpoint was accurate binary classification. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated with 95% confidence intervals [(CIs); Wilson method] agreement with the reference standard and between sessions and models was assessed with the Cohen kappa (κ) coefficient; and differences in classification were assessed with the McNemar test. RESULTS:The radiologist achieved an accuracy of 96.0% (95% CI: 90.3-98.4) with almost perfect agreement with the reference standard (κ: 0.921). In S1, GPT-5 and Gemini 2.5 Pro achieved accuracies of 43.6% and 49.5%, and in S2, 46.5% and 47.5%, respectively. Both models combined high sensitivity (83.3%-97.9%) with low specificity (1.9%-13.2%), and balanced accuracy ranged from 0.45 to 0.52. Between-session reproducibility was fair for GPT-5 (κ: 0.360) and moderate for Gemini 2.5 Pro (κ: 0.485), and inter-model agreement was slight at both sessions (κ: 0.035 at S1 and κ: 0.086 at S2). Accuracy did not differ significantly between the two models (P = 0.211). CONCLUSION:In this single-center study, GPT-5 and Gemini 2.5 Pro, in the versions evaluated, combined high sensitivity with low specificity and showed only fair-to-moderate between-session reproducibility and exhibited slight inter-model agreement on temporal bone key-image HRCT. These findings do not support their use as independent second readers, and broader generalization to other multimodal LLMs would require the evaluation of additional models. CLINICAL SIGNIFICANCE:The evaluated models lacked the spatial precision and consistency required for the accurate assessment of complex middle ear structures. This finding underscores the necessity for verification by a radiologist and continuous monitoring.
PURPOSE:Early hematoma expansion (HE) after intracerebral hemorrhage (ICH) critically affects patient outcomes. Identifying HE risk using emergency non-contrast computed tomography (NCCT) features and clinical data is important for early risk stratification and evaluation. This study analyzed factors associated with early HE and evaluated the value of NCCT features combined with clinical data for HE identification. METHODS:A total of 571 patients with spontaneous supratentorial ICH admitted between January 2022 and December 2025 were enrolled. Five NCCT signs were evaluated at baseline. Four signs significantly associated with HE (black hole, swirl, blend, and satellite signs) were summed to construct a primary comprehensive sign score (0-4); a 5-sign score additionally including the island sign was examined in a sensitivity analysis. Patients were stratified by HE status, sign score quantiles, sex, and hematoma morphology, then randomly assigned to training (n = 391) and validation (n = 180) sets. Univariate and multivariate logistic regression identified independent HE factors and constructed a combined prediction model. Model performance was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). HE was defined as an absolute volume increase > 6 mL or a relative increase > 33% on follow-up CT compared with baseline CT. RESULTS:Among 571 patients, 292 (51.1%) experienced early HE. Multivariate analysis showed that the 4-sign score [odds ratio (OR): 1.850, 95% confidence interval (CI): 1.505-2.274, P < 0.001], irregular hematoma morphology (OR: 2.071, 95% CI: 1.262-3.399, P = 0.004), time from onset to initial CT (OR: 0.845, 95% CI: 0.750-0.953, P = 0.006), male sex (OR: 1.500, 95% CI: 1.028-2.189, P = 0.036), and baseline CT attenuation (OR: 0.964, 95% CI: 0.934-0.995, P = 0.024) were independently associated with HE. The primary combined model achieved an area under the curve (AUC) of 0.731 (95% CI: 0.682-0.781) in the training set and 0.716 (95% CI: 0.641-0.791) in the validation set. The 5-sign sensitivity model showed similar discrimination (AUC: 0.722 and 0.704, respectively), with no significant difference (P = 0.188 and P = 0.283). Calibration and DCA were broadly comparable between models. CONCLUSION:A 4-sign comprehensive imaging score, irregular hematoma morphology, time from onset to initial CT, male sex, and baseline CT attenuation were independently associated with early HE in patients with ICH. CLINICAL SIGNIFICANCE:A model based on NCCT features combined with clinical data may provide a practical adjunct for early HE risk stratification in patients with ICH.
Although digital subtraction angiography remains the gold standard for the diagnosis and treatment planning of intracranial arteriovenous shunts (AVS), including arteriovenous malformations and arteriovenous fistulas, non-invasive imaging is increasingly sought for comprehensive evaluation. Magnetic resonance imaging (MRI) plays a crucial role in AVS detection, identification of feeding arteries and draining veins, localization of shunt points, classification of subtypes, assessment of venous reflux and congestion, and evaluation of post-treatment residual or recurrent lesions. Clinical techniques such as time-of-flight MR angiography (MRA), contrast-enhanced time-resolved MRA, susceptibility-weighted imaging, and arterial spin labeling (ASL) are established for these assessments. Recent advances have expanded MRI capabilities: Ultrashort echo time MRA can overcome turbulent flow-related signal loss and susceptibility artifacts, improving visualization of complex nidus architecture; compressed sensing substantially accelerates three-dimensional and four-dimensional (4D)-MRA while maintaining diagnostic quality; ASL-based 4D-MRA provides high-temporal-resolution dynamic evaluation without contrast, with vessel-selective techniques enabling independent assessment of individual vascular territories; and high-resolution vessel wall imaging shows promise for risk stratification. Emerging artificial intelligence applications enable automated AVS segmentation and characterization, with potential to enhance image quality and reduce scan times. This review summarizes current MRI techniques, recent innovations, and future perspectives in the non-invasive assessment of intracranial AVS.
PURPOSE:To evaluate the real-world multimetric performance of four commercially available computed tomography (CT)-based artificial intelligence (AI) solutions for acute intracranial hemorrhage (AIH). METHODS:Patients who underwent non-contrast brain CT for suspected AIH in our emergency room between February and March 2024 were screened. After applying the inclusion and exclusion criteria, 436 CT scans were included in the final analysis. Three neuroradiologists established the ground truth for AIH and hemorrhage volume. For detection performance, the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and Brier score were calculated based on the available probability score, whereas sensitivity, specificity, precision, and F1 score were calculated based on binary classification. Bland-Altman analysis was performed to assess volumetric agreement for AIH between each algorithm's calculations and the neuroradiologists' measurements. RESULTS:A total of 436 patients (mean age, 62 years ± 20; male patients, 209) were enrolled. The AUROC (0.96 to 0.99) and sensitivity (0.85 to 0.92) were high across all solutions, with no statistically significant differences in pairwise comparisons (P > 0.05). However, solution B demonstrated the highest AUPRC [0.98, 95% confidence interval (CI): 0.94, 1.00] and the lowest Brier score [0.02 (95% CI: 0.02, 0.03)]. In binary performance, both solutions B and D exhibited significantly higher specificity (1.00 and 0.99), precision (0.90 to 0.98), and F1 score (0.87 to 0.94) than the other solutions (P < 0.05). For volumetric agreement of AIH, solution D showed the lowest mean difference [-0.87 mm3 (95% CI: -1.47, -0.27)] and the narrowest limits of agreement (-13.4 to 11.6) relative to the neuroradiologists' measurements. CONCLUSION:In a real-world emergency setting, all four commercially available CT-based AI solutions for AIH demonstrated uniformly excellent performance; however, meaningful differences emerged in confirmatory performance and volumetric agreement. These distinct, algorithm-specific trade-offs provide practical guidance for selecting and integrating appropriate AI solutions to improve AIH diagnosis and management workflows. CLINICAL SIGNIFICANCE:The algorithm-specific performance trade-offs identified in this study suggest that no single AI solution is universally optimal; solutions with superior confirmatory performance may reduce unnecessary notifications in high-volume emergency settings, whereas those with more consistent volumetric agreement may better support treatment planning and longitudinal monitoring. A structured, multimetric evaluation aligned with institutional priorities is essential for evidence-based AI procurement in acute stroke imaging.
Catheterization of the left gastric artery (LGA) is often challenging due to acute angulations that compromise catheter stability. We describe the Simmons (SIM)-lock technique, a novel approach using a standard 5-Fr SIM-1 catheter and a coaxial microcatheter. The microcatheter is first advanced into a distal branch to serve as an anchor, allowing the SIM1 catheter to be deep-seated within the celiac trunk. Upon removal of the microcatheter, the SIM1 catheter assumes its functional recurved shape, with the tip oriented cranially. A controlled pullback maneuver then causes the free tip to slide and lock securely into the LGA ostium. This method transforms a typically unstable engagement into a controlled, stepwise procedure, providing a stable platform for intervention while utilizing standard, cost-effective equipment.
PURPOSE:Prostate cancer (PCa) is the second most common cancer and cause of cancer deaths among American men. Existing risk prediction methods have limited accuracy and reproducibility, resulting in difficulty in predicting treatment outcomes. We demonstrate the development and external validation of an automated multimodal artificial intelligence (AI) algorithm using biparametric magnetic resonance imaging (bpMRI) and clinical covariates for predicting biochemical recurrence (BCR) after radical prostatectomy (RP) in patients with PCa. METHODS:The development cohort included 80% of patients from center 1 (n = 240) who underwent prostate MRI prior to RP between January 2008 and December 2018, with a minimum of 2 years of follow-up after RP. The test cohort included the remaining 20% of center 1 patients (n = 71) and an external validation cohort from center 2 (n = 168). Center 2 patients included those who underwent prostate MRI and RP between January 2015 and January 2024, with a minimum of 2 years of follow-up. Clinical comparisons were made using the Cancer of the Prostate Risk Assessment Postsurgical (center 1) and International Society of Urological Pathology Gleason Grade Group (ISUP GGG) scoring systems from post-RP pathology (center 2). The models developed were as follows: clinical (M0), automated clinical (M1), radiomics (M2), and a multimodal model (M3). Clinical variables (M0) included prostate-specific antigen (PSA), age, primary Gleason, and ISUP GGG. Automated clinical variables (M1 and M3) included PSA and age. Radiomic features (M2 and M3) were extracted from bpMRI using a lesion detection AI model. Accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated, and log-rank tests compared BCR-free survival to assess the models' ability to discriminate relative to clinical standards. Intermediate-risk groups were also assessed. RESULTS:The multimodal model (M3) had the highest AUC across test sets (combined: 0.71; center 1: 0.70; center 2: 0.75). This was the only model that significantly differentiated BCR-free survival outcomes in intermediate-risk groups across both centers (P < 0.05). CONCLUSION:This automated multimodal model leveraging radiomics and clinical covariates can predict BCR after RP, approaching clinical gold standards, and may enhance imaging-based prognostication following further validation. CLINICAL SIGNIFICANCE:Given that this model demonstrated the potential to outperform pre-surgical and post-surgical clinical gold standards in an external cohort's intermediate-risk patient subgroup (for whom it is more challenging to predict disease trajectory), this model may contribute to enhanced personalized care in PCa after further validation.
Image-guided percutaneous cryoablation (CA) has become an increasingly accepted nephron-sparing treatment for small renal masses, including complex endophytic tumors. This narrative review synthesizes current evidence on technical considerations, oncologic outcomes, and safety profiles of CA for endophytic renal cell carcinoma (RCC), with critical evaluation of factors influencing local tumor control and complications. Dedicated endophytic cohorts report primary 5-year local tumor progression-free survival of approximately 64%-75%, improving to 87%-89% after re-ablation, with excellent cancer-specific survival and minimal impact on renal function. However, high anatomical complexity, size, and proximity to vascular or collecting system structures that suggest more endophytic locations pose significant technical challenges; furthermore, they are associated with increased risk of incomplete ablation and major complications compared with exophytic or mixed tumors. Advances in procedural techniques-including hydrodissection, pyeloperfusion, transarterial embolization, and selective arterial balloon occlusion-have expanded the boundaries of safely treatable disease. CA demonstrates similar safety and renal function preservation vs. partial nephrectomy, without the increase in rates of major adverse events or longer hospitalization. For appropriately selected patients with clinical T1 endophytic RCC, image-guided CA provides a safe and effective therapeutic option with durable oncologic outcomes and substantial quality-of-life benefits. Ongoing multicenter registry data and prospective studies are needed to refine risk stratification and optimize procedural strategies for challenging tumor locations.
Bile duct injury from laparoscopic cholecystectomy is an uncommon complication. Percutaneous cystic duct embolization has been used to treat bile leaks from the cystic duct in patients who are not surgical candidates or who have failed endoscopic retrograde cholangiopancreatography (ERCP). A case of a 48-year-old man who underwent cholecystectomy complicated by bile leak and biloma in the gallbladder fossa requiring drain placement is presented. The patient initially underwent ERCP with sphincterotomy of the major duodenal papilla and common bile duct stent placement. However, due to a persistent bile leak, a percutaneous cystic duct embolization procedure was performed through the gallbladder fossa using a microvascular plug and the LAVA® Liquid Embolic System (LES) in a retrograde fashion. The output from the preexisting drain in the gallbladder fossa stopped within 3 days, and the drain was removed after follow-up abdominal computed tomography at 1 week, which confirmed resolution of the biloma. The LAVA LES has not been reported in the literature with respect to cystic duct embolization.
PURPOSE:Randomized controlled trials (RCTs) comparing hydrogel-coated coils (HGCs) with bare platinum coils (BPCs) have yielded heterogeneous results, and the clinical relevance of longitudinal angiographic assessment remains uncertain. Following the publication of the HYBRID trial, which emphasized occlusion trajectory rather than static end points, a post-HYBRID updated meta-analysis is warranted to compare angiographic durability and safety outcomes between these coil types. METHODS:A systematic literature search of MEDLINE, Web of Science, and Scopus was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RCTs comparing HGCs with BPCs for the treatment of intracranial aneurysms were included. RESULTS:Six RCTs comprising 2,486 patients and 2,513 treated intracranial aneurysms were included in the analysis. There was no statistically significant difference between HGCs and BPCs in immediate complete occlusion [risk ratio (RR): 0.87; 95% confidence interval (CI), 0.70-1.09; I²: 63.0%] or immediate adequate occlusion (RR: 0.96; 95% CI, 0.85-1.07; I²: 31.0%). Immediate residual aneurysm was significantly more frequent with HGCs than with BPCs (RR: 1.12; 95% CI, 1.01-1.24; I²: 0.0%; P = 0.041). At the last available angiographic follow-up, complete occlusion, adequate occlusion, and residual neck rates remained comparable between HGCs and BPCs. However, residual aneurysm at follow-up was significantly less frequent with HGCs than with BPCs (RR: 0.75; 95% CI, 0.68-0.83; I²: 0.0%; P = 0.006). HGCs were also associated with a significantly lower rate of major recurrence than BPCs (RR: 0.71; 95% CI, 0.54-0.94; P = 0.024). Safety and clinical outcomes were similar between treatment groups. CONCLUSION:Despite comparable safety and clinical outcomes between HGCs and BPCs, HGCs demonstrated superior angiographic durability, as reflected by lower rates of residual aneurysm and major recurrence. CLINICAL SIGNIFICANCE:HGCs may offer improved long-term aneurysm durability compared with BPCs by reducing residual aneurysm and major recurrence without compromising safety or clinical outcomes. These findings support consideration of HGCs when durable occlusion is a priority in endovascular treatment planning for intracranial aneurysms.
We describe a simple securing suture designed to prevent the accidental dislodgement of long-term, Dacron-cuffed tunneled central venous catheters during the interval before fibrous ingrowth fixes the cuff. A 3-0 nylon suture is placed at the exit site around the plastic shaft of the tunneler before the catheter is pulled through the subcutaneous tunnel; after the catheter is positioned and the Dacron cuff is seated cranial to the suture loop, the suture is tied around the catheter. The technique was applied in 207 consecutive patients (108 men, 99 women; mean age 42.4 years) over a 15-month period, with a 100% technical success rate, no procedure-related catheter injury, and no dislodgement on follow-up chest radiography at 1 to 2 weeks. The suture is performed before catheter insertion, requires no additional incision, and can be removed at the bedside, providing a safe and efficient adjunct for catheter fixation.
PURPOSE:To investigate the accuracy of hematoma volume (V), surface area (S), and surface regularity (SR) measured on dual-energy computed tomography angiography (DECTA), using non-contrast computed tomography (NCCT) as the reference standard. METHODS:A total of 129 patients with spontaneous intracerebral hemorrhage (sICH) who underwent both NCCT and DECTA scans were retrospectively studied. Patients were stratified by V: Group 1 (< 30 mL), Group 2 (30-60 mL), and Group 3 (> 60 mL); and by morphology: regular, irregular, and lobular. DECTA data were post-processed to generate conventional computed tomography angiography (CTA) and 60 keV virtual monoenergetic imaging (VMI). These, along with NCCT images, were imported into 3D Slicer software to obtain V and S; SR was subsequently calculated. Deviation percentages (ΔV, ΔS, ΔSR) of conventional CTA and 60 keV VMI relative to NCCT were calculated. We assessed correlations using simple linear regression, compared different modalities with unpaired t-tests or Mann-Whitney U tests, evaluated agreement via Bland-Altman analysis, and compared deviation percentages across groups using one-way analysis of variance or Kruskal-Wallis H tests. Inter-reader consistency was assessed using the intraclass correlation coefficient (ICC). RESULTS:The average V was 28.86±24.15 mL. All ICCs were excellent (0.991-0.999). Strong correlations were found for V and S between conventional CTA/60 keV VMI and NCCT (r: 0.987-0.996). Bland-Altman analysis for V showed mean biases of 0.21 mL (conventional CTA) and -0.04 mL (60 keV VMI) against NCCT, with 95% limits of agreement of -4.72 to 5.14 mL and -4.51 to 4.43 mL, respectively. However, SR values from both conventional CTA and 60 keV VMI were significantly lower than those from NCCT (all P < 0.001). In volume-based stratification, no significant differences in ΔS (conventional CTA) or ΔV, ΔS, and ΔSR (60 keV VMI) were found among groups (all P ≥ 0.410). For conventional CTA, ΔV was significantly smaller in Group 3 (> 60 mL) than in Group 1 (3.07% vs. 5.57%, adjusted P = 0.047), whereas ΔSR was larger (13.26% vs. 9.88%, adjusted P = 0.040). Morphology-based stratification revealed no significant differences in ΔV, ΔS, or ΔSR across groups for either modality (all P values ≥ 0.085). CONCLUSION:Hematoma volume measurements from DECTA show good agreement with NCCT measurements, suggesting potential utility for follow-up assessment in certain clinical scenarios. However, DECTA-derived SR measurements are significantly lower than those from NCCT. Volume measurement accuracy of conventional CTA was higher for large hematomas (> 60 mL). CLINICAL SIGNIFICANCE:Accurate hematoma measurement is crucial for prognosis and management in sICH. This study indicates that V measurements from DECTA are comparable to those from NCCT in certain clinical scenarios, offering potential added value when CTA is clinically indicated.
PURPOSE:This study aimed to compare the safety and efficacy of two resorbable microparticles in a porcine kidney model, focusing on recanalization and tissue injury outcomes over a 7-day follow-up period. METHODS:This exploratory proof-of-concept study included 10 pigs, each undergoing embolization of the upper polar arteries in both kidneys, resulting in 20 treated kidneys (10 per group). Angiographic evaluations were performed on all 20 treated kidneys (10 per group) across the 10 animals at immediate, 2-hour, 1-day, and 7-day post-embolization time points. Histopathologic evaluations were performed on 5 animals per group (5 kidneys per group). The primary endpoint was complete angiographic recanalization at 7 days. Secondary endpoints included early recanalization at 2 hours and 1 day and histopathologic tissue injury. In Group A, the right upper polar artery was embolized with spherical gelatin microparticles (Nexsphere-F®), whereas in Group B, the left upper polar artery was embolized with irregular microparticles (KIPZA®). Approximately 5-10 mL of microparticle suspension was injected per kidney; the mean embolization time per kidney was 30 ± 5 minutes. RESULTS:At 2 hours post-embolization, complete recanalization was observed in all Nexsphere-F kidneys and in 9 of 10 KIPZA kidneys; 1 KIPZA kidney showed partial recanalization. Full recanalization was observed in all kidneys by day 7. Histopathologic evaluation (5 kidneys per group) revealed no residual emboli or parenchymal infarction in Group A. In Group B, minimal microparticle residue and focal infarction (mean infarcted area 2.78% ± 1.33%) were observed, along with endothelial proliferation in arcuate and interlobular arteries. CONCLUSION:In this exploratory pilot study, embolization with both Nexsphere-F and KIPZA microparticles resulted in early recanalization and minimal tissue injury. These proof-of-concept findings suggest that both microparticles may be suitable for temporary embolization when organ preservation is paramount, although larger powered studies with disease models and longer follow-up are needed. CLINICAL SIGNIFICANCE:These preliminary data support the potential of resorbable microparticles for temporary embolization, emphasizing their use in scenarios requiring parenchymal preservation and underscoring the need for further research.
Multinuclear magnetic resonance imaging (MRI), which uses nuclei other than protons (1H), has undergone a dramatic transformation with the advent of regulatory-approved radiofrequency coils. Phosphorus-31 magnetic resonance spectroscopy (³¹P-MRS) and sodium-23 MRI (²³Na-MRI) are now accessible at clinical sites equipped with commercially available surface coils, enabling advanced metabolic and tissue characterization without specialized research infrastructure or ultra-high-field systems. ³¹P-MRS provides a quantitative assessment of cellular energy metabolism and mitochondrial function while enabling the calculation of the intracellular pH. ²³Na-MRI visualizes the in vivo distribution of sodium, which is relevant since sodium ion distribution plays a critical role in cellular function and ionic homeostasis. Sodium concentration serves as an important biomarker of tissue health status. Both ³¹P-MRS and ²³Na-MRI have been widely utilized to assess multiple organ systems as well as diseases of the brain, heart, skeletal muscle, and tumors. However, clinical implementation using newly approved coils remains largely undefined, as the optimal acquisition protocols, target organ selection, coil positioning, interpretation criteria, and disease-specific imaging strategies have not been established. This review synthesized technical considerations for surface coil-based upper abdominal imaging, methodological approaches, and preliminary clinical findings from our initial clinical experience with ³¹P-MRS and ²³Na-MRI.
