Search Results (96)

Background/Objectives: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Conventional computed tomography (CT) is the preferred imaging modality for evaluating pulmonary nodules because of its high spatial resolution; however, it primarily provides morphological information, including lesion size, shape, and density. Dual-energy CT (DECT), a more recent imaging technique, uses two different energy levels to enable material decomposition and quantitative parameter assessment. These parameters may provide additional information regarding tumor perfusion, vascularization, and tissue composition. This rapid review aimed to evaluate the current evidence regarding the clinical utility of DECT in the detection, characterization, and staging of lung tumors. Methods: This rapid review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A literature search was performed in the PubMed and Cochrane Library databases for studies published between 2005 and 2026. Studies were included if they evaluated the detection, characterization, or staging of lung tumors using quantitative DECT parameters. Case reports, editorials, duplicate studies, and studies without quantitative DECT data were excluded. Descriptive data analysis was performed using Microsoft Excel. Results: A total of 24 studies were included, comprising 18 retrospective (75%) and 6 prospective studies (25%). Only one study evaluated the role of DECT in lung tumor detection, demonstrating improved detection of mixed ground-glass nodules and invasive adenocarcinoma. Significant correlations were found between iodine uptake and tumor perfusion, highlighting the potential of DECT to improve differentiation between benign and malignant lesions. Several studies also demonstrated associations between DECT parameters and tumor biomarkers, including Ki-67 Proliferation Index (Ki-67) expression, Epidermal Growth Factor Receptor (EGFR) mutation status, Programmed Death-Ligand 1 (PD-L1) expression, and treatment response in non-small cell lung cancer. In addition, DECT provided complementary metabolic information regarding tumor malignancy and showed correlations between iodine uptake and fluorodeoxyglucose (FDG) parameters. Associations between iodine volume and tumor differentiation grade were also reported. One study demonstrated the potential role of DECT in tumor staging by predicting mediastinal lymph node metastasis. Across all included studies, iodine-based parameters (50%), radiomics and material decomposition parameters (16.67% each), and spectral attenuation parameters (12.50%) were the most frequently investigated DECT metrics. Conclusions: DECT appears to be a promising complementary imaging technique that provides quantitative perfusion-related and compositional surrogate information beyond the morphological assessment offered by conventional CT. However, the current evidence remains heterogeneous and is largely based on retrospective studies with relatively small patient cohorts. Larger prospective studies with standardized imaging protocols are necessary to further establish the clinical utility of DECT in lung tumors. Full article

Basic calcium phosphate (BCP) and calcium pyrophosphate dihydrate (CPPD) crystals drive the degenerative and inflammatory pathways that lead to crystal arthropathy. Although recent classification criteria and imaging recommendations have improved standardisation for CPPD disease, it remains underdiagnosed in practice. In contrast, BCP disease lacks validated classification criteria and standardised diagnostic descriptors, limiting translational research and clinical recognition. Accurate diagnoses are limited by varied reference standards, operator-dependent techniques, and the absence of validated bedside tools. As the population ages and the burden of crystal disease rises, there will be increased demand for reliable diagnostic tools in clinical practice. This review summarises current and emerging diagnostic tools for identifying BCP and CPPD, with emphasis on bridging the diagnostic gap from research to routine care. Polarised light microscopy remains a highly specific test for the diagnosis of CPPD but is limited by inter-observer variability and access to polarising light microscopes. Imaging tools such as ultrasound, conventional radiography, computed tomography (CT) and dual-energy CT can identify CPPD, although performance varies by anatomical site, disease stage and technical parameters. Ultrasound is a useful bedside tool for identifying BCP disease, whereas CT and DECT also have diagnostic utility but lack validation for routine use. Emerging technologies such as computational polarised light microscopy and Raman spectroscopy are promising techniques, but require further research to evidence their use in clinical practice. Development of clear diagnostic reference standards, classification criteria for BCP disease, and evidence-based multimodal diagnostic pathways are essential to bridge the gap between research and routine clinical diagnosis. Full article

Background: Dual-energy computed tomography (DECT) with virtual non-calcium (VNCa) reconstruction is emerging as an alternative method for identifying bone marrow edema (BME) in cases of inflammatory sacroiliitis, especially when magnetic resonance imaging (MRI) is contraindicated or unavailable. Objectives: The aim of this systematic review and meta-analysis is to evaluate the diagnostic performance of DECT with VNCa reconstruction for detecting BME in inflammatory sacroiliitis, using MRI as the reference standard. Methods: Following PRISMA-DTA guidelines and a pre-registered PROSPERO protocol (CRD420251103652), we searched PubMed, Web of Science, and the Cochrane Library up to June 2025. Seven studies comprising 358 patients and 591 sacroiliac joints were included. Quality assessment was performed using QUADAS-2. Pooled sensitivity and specificity were calculated using a bivariate random-effects regression model. Heterogeneity was evaluated using the I² statistic. Subgroup analyses were performed for anatomical site and slice thickness, along with a meta-regression according to anatomical site. Publication bias was assessed using Deeks’ test. Results: Quality assessment revealed a moderate risk of bias, primarily related to patient selection. The pooled sensitivity and specificity of DECT VNCa were 78% (95% CI: 65–88%) and 83% (95% CI: 71–91%), respectively. The area under the SROC curve was 0.91 (95% CI: 0.88–0.93), indicating good diagnostic accuracy. Heterogeneity was moderate for sensitivity (I² ≈ 68%) and high for specificity (I² ≈ 88%), largely driven by one outlier study. Sensitivity was lower for sacral BME than for iliac BME (69% vs 79%), although this difference did not reach statistical significance (p ≈ 0.07). Specificity tended to be higher with slice thickness ≥1 mm than with <1 mm (90% vs 84%), although the difference was not statistically significant (p ≈ 0.06). Exclusion of one outlier study (Deppe et al.) increased pooled specificity to 92% and reduced heterogeneity. Deeks’ test did not reveal significant publication bias. Conclusions: DECT VNCa has been shown to be highly accurate in the diagnosis of inflammatory sacroiliac BME. Its high specificity makes it suitable for confirming inflammatory activity when an MRI scan is not feasible. However, its sensitivity is moderate and variable, with a trend towards lower values for sacral lesions. This precludes its use as a standalone test to rule out active inflammatory sacroiliitis, especially in young patients. Standardization of acquisition protocols and site-specific diagnostic thresholds is recommended for optimal clinical implementation. Clinical Impact: Clarifying the diagnostic performance of VNCa of DECT to define its role as a complementary tool to MRI for assessing BME in inflammatory sacroiliitis. These results could guide appropriate patient selection and highlight the need for standardized protocols. Full article

Background/Objectives: We aim to evaluate whether digital imaging and communications in medicine (DICOM)-level deep learning-based iodine-boosting applied to dual-source dual-energy computed tomography (DECT) source DICOM improves image quality in low-iodine-dose abdominal DECT in adults undergoing post-procedure follow-up computed tomography (CT). Methods: This retrospective study included 43 adults (April–September 2025) who underwent dynamic dual-source DECT using a low-iodine protocol. Three CT reconstructions were compared: mixed images, conventional 50-keV virtual monoenergetic images (VMIs), and 50-keV VMIs generated after applying DICOM-based deep learning iodine-boosting/denoising to the tube-specific dual-energy source DICOM series prior to VMI/iodine-map reconstruction (deep learning-based reconstruction [DLR]-VMI). Iodine material density (IMD) images were compared between the conventional and DLR-processed datasets. Quantitative attenuation and signal-to-noise ratio (SNR) were assessed using paired and repeated-measures tests. Image quality was scored by two readers using a five-point Likert scale. Results: Attenuation varied across CT reconstructions for all regions of interest in both phases (all overall p < 0.001). Liver attenuation increased from 94.9 ± 22.0 Hounsfield units (HU) (VMI) to 114.5 ± 34.6 HU (DLR-VMI) during the arterial phase and from 127.6 ± 25.6 HU to 166.6 ± 39.9 HU during the portal venous phase (both p < 0.001). Liver SNR improved with DLR-VMI compared to VMI (arterial: 9.11 ± 3.62 vs. 6.06 ± 1.90; portal: 12.74 ± 3.56 vs. 7.90 ± 1.82; both p < 0.001). On IMD images, DLR increased HU-equivalent values and liver SNR (arterial: 5.20 ± 2.89 vs. 2.61 ± 1.39; portal: 9.22 ± 2.81 vs. 4.48 ± 1.28; both p < 0.001). Qualitatively, DLR-VMI yielded the highest overall image-quality scores for both reviewers in both phases (Reviewer 1, arterial/portal: 4 (4–5)/5 (4–5); Reviewer 2, arterial/portal: 4 (3–4)/4 (4–4)). DLR also improved the overall image quality of IMD images for both reviewers (all p < 0.001). Conclusions: Raw DICOM-level iodine-boosting DLR applied to dual-source DECT-source DICOM enabled enhanced image quality and improved quantitative and qualitative metrics in low-iodine-dose abdominal DECT. Full article

Historically, stage T4 non-small cell lung cancer (NSCLC) with direct spinal invasion was considered a definitive surgical contraindication due to the perceived inability to achieve negative margins without catastrophic morbidity. This paradigm has shifted through the advancement of specialized surgical techniques, which facilitate radical en-bloc resection in highly selected candidates by adhering to the en-bloc concept. This concept mandates the retrieval of the tumor and invaded vertebral segments as a single, contiguous unit to prevent intralesional transgression and local recurrence. Achieving microscopic negative margins (R0) stands as the most critical prognostic factor, as radical resection offers a significantly improved potential for long-term survival. Technical success requires a meticulously planned multidisciplinary approach encompassing varied surgical corridors—ranging from combined anterior–posterior windows to single-stage posterior-only approaches—tailored to the tumor’s anatomical level. Furthermore, preoperative hemostatic optimization using dual-energy computed tomography (DECT) for vascular assessment and transarterial embolization (TAE) has become indispensable for managing the hypervascularity of the invaded vertebral bone. This review synthesizes these evolving strategies, illustrated by a case of a 74-year-old male with stage T4 NSCLC where an R0 resection was achieved through a two-stage approach integrating uniportal video-assisted thoracoscopic surgery (VATS). Ultimately, en-bloc management provides a feasible and potential surgical strategy toward long-term survival for localized, spine-invasive lung cancer within a multidisciplinary treatment framework. Full article

Background/Objectives: Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan, has been identified as a promising target for both the diagnosis and treatment of hepatocellular carcinoma (HCC). However, the diagnosis of GPC3 expression mainly depended on invasive procedures. This study aimed to investigate the potential of dual-energy computed tomography (DECT)-derived parameters for noninvasive prediction of GPC3 expression in HCC. Methods: This retrospective study included 79 HCC patients with confirmed GPC3 immunohistochemistry and pretreatment contrast-enhanced DECT. Qualitative imaging features and quantitative DECT parameters, including iodine density of HCC (ID_Ca), normalized iodine density (NID), slope of spectral attenuation curve (λ_HU), and effective atomic number (Z_eff), were evaluated in both arterial and portal venous phases. Univariate and multivariate logistic regression analyses were employed to identify independent predictors, and a combined model was subsequently constructed. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic efficiency of imaging parameters in predicting GPC3 expression. Interobserver agreement of DECT parameters was evaluated using intraclass correlation coefficients (ICC). Results: GPC3-positive HCCs demonstrated significantly higher arterial phase (AP) ID_Ca, NID, λ_HU, and Z_eff (all p ≤ 0.001) than GPC3-negative HCCs. Multivariate logistic regression analysis identified NID-AP [Odds ratio (OR) = 2.00, p = 0.010] and peritumoral enhancement (OR = 9.25, p = 0.046) as independent predictors. The model combining NID-AP and peritumoral enhancement achieved the best diagnostic performance (AUC = 0.781, sensitivity = 67.86%, specificity = 78.26%) for predicting GPC3 expression. All DECT-derived parameters showed excellent interobserver reproducibility (ICC > 0.75 for all). Conclusions: Parameters derived from DECT, especially combining NID-AP and peritumoral enhancement, may be a potential tool to noninvasively predict GPC3 expression in HCC. Full article

Background: Computed tomography (CT)-guided lung biopsy plays a pivotal role in diagnosing thoracic lesions. However, its diagnostic yield may be compromised in large, necrotic, or heterogeneous tumours due to inadvertent sampling of non-viable tissue. Dual-energy CT (DECT) iodine mapping provides functional imaging by identifying iodine-avid, perfused areas, thereby offering the potential to improve biopsy targeting. Methods: This single-centre retrospective study evaluated the clinical feasibility and diagnostic performance of DECT-guided biopsy. Adult patients with suspected necrotic lung or mediastinal lesions who underwent DECT iodine mapping prior to CT-guided biopsy between April 2021 and December 2022 were evaluated. DECT iodine maps were generated using dual-source CT and used to identify viable tumour regions for targeted biopsy. The primary outcome was diagnostic yield, defined as obtaining a definitive histopathological diagnosis. Secondary outcomes included safety and adequacy of samples for molecular testing. Results: Twenty patients were included. A definitive diagnosis was obtained in 18/20 biopsies (90%). Diagnostic yield was 9/11 (81.8%) for pulmonary lesions and 9/9 (100%) for mediastinal/pleural lesions. Diagnoses included non-small-cell lung cancer (n = 8), Hodgkin lymphoma (n = 4), thymoma (n = 3), and other malignancies (n = 3). Biopsy material was sufficient for additional molecular testing in 13/20 cases (65%). Complications were minor (one pneumothorax not requiring drainage and two self-limited bleeding events). Conclusions: DECT iodine map-guided targeting was feasible in this retrospective cohort and was associated with high diagnostic yield, low complication rates, and frequent acquisition of tissue suitable for molecular analyses. Prospective controlled studies are needed to quantify benefit over conventional CT guidance. Full article

This work presents a novel deep learning workflow for estimating porosity and permeability from combined data, where numerical variables such as high-resolution bulk density (RHOB) and photoelectric factor (PEF) data are integrated with X-ray computed tomography (X-CT) image data, using a dual-energy X-CT approach (DECT). Convolutional neural networks (CNNs) were calibrated with routine core analysis (RCAL) laboratory measurements from one well from Sinú-San Jacinto Basin (Colombia). The CNN architecture combines two main branches: An image branch, in which a CNN extracts spatial features from normalized X-CT sections using 3 × 3 convolution layers, ReLU activation, batch normalization, and maxPooling, and a numerical branch, which processes the input vectors corresponding to RHOB and PEF using fully connected dense layers and dropout regularization. Both branches are concatenated in a fusion layer, from which the model’s final predictions are made. Results indicate a strong correlation between porosity, permeability, RHOB and PEF logs, and CT images. The porosity model achieved excellent predictive performance, with an R² = 0.996, MAE = 3.96 × 10⁻³, MSE = 3.82 × 10⁻⁵, and 0.064 maximum error. The permeability model also performed well, with a linear R² = 0.983, though metrics reflected the wide dynamic range of permeability. Consequently, artificial neural networks (ANNs) can accurately predict porosity and permeability at various depths where no corresponding laboratory data exists, demonstrating excellent predictive capabilities over several rock intervals, in a high vertical resolution because of X-CT data scale (0.625 mm). Full article

Background: Computed tomography (CT)-based image-guided surgery (IGS) is of great importance in functional endoscopic sinus surgery (FESS) and requires IGS-specific imaging protocols to ensure high intraoperative accuracy. This study aimed to compare photon-counting CT (PCCT), dual-energy dual-source CT (DECT), and spectral detector CT (SDCT) of the paranasal sinuses with respect to image quality, IGS accuracy and radiation dose. Methods: A formalin-fixed cadaver skull was examined using PCCT, DECT and SDCT at 100 kV tube voltage with descending tube currents (mAs). The setup of electromagnetic IGS was evaluated using a visual analog scale. Accuracy was analyzed endoscopically using defined anatomical landmarks. Diagnostic image quality as well as bone and soft tissue noise were assessed qualitatively using a 5-point Likert scale and quantitatively by determination of signal-to-noise ratio. Radiation dose was evaluated using the dose length product. Results: While PCCT datasets could be registered and navigated accurately down to 10 mAs (1.5 mm error at 10 mAs), both DECT and SDCT exhibited significantly increased inaccuracies below 40 mAs (4.35/5.15 mm for DECT/SDCT at 25 mAs). Using PCCT therefore enabled a 45% radiation dose reduction at the minimally required dose length product using PCCT. Quantitative and qualitative image quality were superior for PCCT compared to DECT and SDCT. Conclusions: PCCT provides excellent accuracy of anatomical landmarks in IGS with superior image quality of the paranasal sinuses in low-mA scans and substantially reduced radiation exposure. Full article

Objectives: The potential use of electron density (ED) and effective atomic number (Zeff) derived from dual-energy computed tomography (DECT) as novel quantitative imaging biomarkers for differentiating malignant brain tumors was investigated. Methods: Data pertaining to 136 patients with a pathological diagnosis of brain metastasis (BM), glioblastoma, and primary central nervous system lymphoma (PCNSL) were retrospectively reviewed. The 10th percentile, mean and 90th percentile values of conventional 120-kVp CT value (CTconv), ED, Zeff, and relative apparent diffusion coefficient derived from diffusion-weighted magnetic resonance imaging (rADC: ADC of lesion divided by ADC of normal-appearing white matter) within the contrast-enhanced tumor region were compared across the three groups. Furthermore, machine learning (ML)-based diagnostic models were developed to maximize diagnostic performance for each tumor classification using the indices of DECT parameters and rADC. Machine learning models were developed using the AutoGluon-Tabular framework with rigorous patient-level data splitting into training (60%), validation (20%), and independent test sets (20%). Results: The 10th percentile of Zeff was significantly higher in glioblastomas than in BMs (p = 0.02), and it was the only index with a significant difference between BMs and glioblastomas. In the comparisons including PCNSLs, all indices of CTconv, Zeff, and rADC exhibited significant differences (p < 0.001–0.02). DECT-based ML models exhibited high area under the receiver operating characteristic curves (AUC) for all pairwise differentiations (BMs vs. Glioblastomas: AUC = 0.83; BMs vs. PCNSLs: AUC = 0.91; Glioblastomas vs. PCNSLs: AUC = 0.82). Combined models of DECT and rADC demonstrated excellent diagnostic performance between BMs and PCNSLs (AUC = 1) and between Glioblastomas and PCNSLs (AUC = 0.93). Conclusion: This study suggested the potential of DECT-derived ED and Zeff as novel quantitative imaging biomarkers for differentiating malignant brain tumors. Full article

Background: Lumbar disk herniation is a common cause of low back pain and radiculopathy, significantly impacting patients’ life quality and functional capacity. Magnetic Resonance Imaging (MRI) remains the gold standard for its assessment due to its superior soft tissue contrast and multiplanar imaging capabilities. However, recent advances in spectral computed tomography (CT), particularly dual-energy CT (DECT), have introduced new diagnostic opportunities, offering improved soft tissue characterization. Objective: To evaluate the diagnostic performance of DECT in detecting and grading lumbar disk herniations using dedicated color-coded fat maps. Materials and Methods: A total of 205 intervertebral levels from 41 consecutive patients with lumbar symptoms were prospectively analyzed. All patients underwent both DECT and MRI within 3 days. Three radiologists with varying years of experience independently assessed DECT images using color-coded reconstructions. A five-point grading score was attributed to each lumbar level: 1 = normal disk, 2 = bulging/protrusion, 3 = focal herniation, 4 = extruded herniation, and 5 = migrated fragment. The statistical analysis included Pearson’s correlation for score consistency, Cohen’s Kappa for interobserver agreement, generalized estimating equations for a cluster-robust analysis, and an ROC curve analysis. The DECT diagnostic accuracy was assessed in a dichotomized model (grades 1–2 = no herniation; 3–5 = herniation), using MRI as reference. Results: A strong correlation was observed between DECT and MRI scores across all readers (mean Pearson’s r = 0.826, p < 0.001). The average exact agreement between DECT and MRI was 79.4%, with the highest concordance at L1–L2 (86.7%) and L5–S1 (80.4%). The interobserver agreement was substantial (mean Cohen’s κ = 0.765), with a near-perfect agreement between the two most experienced readers (κ = 0.822). The intraclass correlation coefficient was 0.906 (95% CI: 0.893–0.918). The ROC analysis showed excellent performance (AUC range: 0.953–0.986). In the dichotomous model, DECT demonstrated a markedly higher sensitivity than conventional CT (95.1% vs. 57.2%), with a comparable specificity (DECT: 99.0%; CT: 96.5%) and improved overall accuracy (98.4% vs. 90.0%). Subgroup analyses by age and disk location revealed no statistically significant differences. Conclusions: The use of DECT dedicated color-coded fat map reconstructions showed high diagnostic performance in the assessment of lumbar disk herniations compared to MRI. These findings support the development of dedicated post-processing tools, facilitating the broader clinical adoption of spectral CT, especially in cases where MRI is contraindicated or less accessible. Full article

Contrast-induced encephalopathy (CIE) is a rare complication after percutaneous coronary intervention (PCI) that mimics intracranial hemorrhage (ICH). Its computed tomography (CT) findings (cortical contrast enhancement, sulci effacement) overlap with cerebrovascular conditions (e.g., cerebral infarction, subarachnoid hemorrhage). Dual-energy CT (DECT) differentiates blood/calcification from iodinated contrast medium (CM) extravasation via material decomposition, contributing to the accurate diagnosis of CIE. We report a CIE case highlighting DECT’s value. A 74-year-old woman underwent PCI. 50 min post-PCI, she had moderate headache (Numeric Rating Scale 4), dizziness, non-projectile vomiting (no seizures); vital signs were stable, no focal deficits, mannitol ineffective. Non-contrast CT demonstrated a left parietal 75 Hounsfield unit (HU) high-attenuation lesion, indistinguishable from acute intracerebral hemorrhage. Conventional non-contrast CT revealed a high-attenuation lesion (75 HU) in the left parietal lobe—indistinguishable from ICH. DECT clarified the diagnosis: virtual non-contrast maps showed CM extravasation, iodine concentration maps confirmed focal CM accumulation, and effective atomic number maps improved lesion visualization. The patient’s headache resolved within 5 h; follow-up non-contrast CT at 24 h showed complete disappearance of the lesion. She resumed clopidogrel, discharged day 3 without sequelae. This case underscores DECT’s role in distinguishing CIE (transient CM, normal neuro exam) from ICH (persistent hemorrhage), guiding safe post-PCI antiplatelet therapy. Full article

Background and Objectives: The extracellular volume fraction (fECV) of the liver, as measured by contrast-enhanced computed tomography (CT), has been shown to correlate closely with the histological stages of hepatic fibrosis. This study aimed to investigate the diagnostic performance of a liver extracellular volume fraction derived from dual-energy CT (DECT) for evaluating liver functional reserve based on the Child–Pugh class in cirrhotic patients, compared with other noninvasive markers. Materials and Methods: This retrospective study included 258 patients with liver cirrhosis who underwent contrast-enhanced DECT. The fECV was measured using iodine maps derived from equilibrium phase images obtained 3 min after contrast injection at 100/140 Sn kVp. Statistical analyses included Welch’s ANOVA with post hoc tests, Spearman’s correlation, and ROC analysis. The area under the curve (AUC) was compared among fECV and other noninvasive markers (aspartate transaminase to platelet ratio index [APRI], Fibrosis-4 [FIB-4], and model for end-stage liver disease [MELD]) using DeLong’s test. Intra- and interobserver reliability of fECV was assessed with the intraclass correlation coefficient (ICC). The area under the receiver operating characteristic curve (AUC) for differentiating Child–Pugh classes was compared among the fECV and other noninvasive markers (aspartate transaminase to platelet ratio index [APRI], Fibrosis-4 [FIB-4], and model for end-stage liver disease [MELD]). Results: The fECV increased significantly with advancing Child–Pugh classes (p < 0.001), showing a moderate correlation with Child–Pugh class (r = 0.53). The mean differences in fECV among the Child–Pugh classes were 8.88 between A and B (95% confidence interval [CI], 5.85–11.92; p < 0.001) and 7.42 between B and C (95% CI, 1.92–12.91: p < 0.001). The AUC for differentiating Child–Pugh classes A and B demonstrated no significant differences among the fECV (0.84), APRI (0.83, p > 0.99) and FIB-4 (0.83, p > 0.99), except for MELD, which had a significantly higher AUC (0.94, p = 0.047). For differentiating Child-Pugh classes B and C, the fECV demonstrated a significantly higher AUC (0.78), compared with FIB-4 (0.50, p = 0.038) and APRI (0.49, p = 0.037), whereas no significant difference was observed between fECV and MELD (0.92, p = 0.12). The intra- and interobserver reliabilities of the fECV measurements were excellent (ICC, 0.93; 95% CI, 0.91–0.95 and 0.91; 95% CI, 0.88–0.92, respectively). Conclusions: DECT derived fECV is a useful noninvasive marker for assessing liver functional reserve based on the Child–Pugh classification. Full article

Acute pulmonary embolism (APE) represents a significant cause of morbidity and mortality worldwide, requiring rapid and precise diagnosis and effective therapy strategies. Computed Tomography Pulmonary Angiography (CTPA) is currently the gold standard technique for diagnosing PE; however, it presents some disadvantages, including limited sensitivity in detecting sub-segmental emboli and contrast-related risks. Recent advancements in imaging technologies, including Dual-Energy Computed Tomography (DECT) and Photon Counting (PC), offer improved sensitivity and specificity for APE and perfusion abnormalities detection. Digital Dynamic Radiography (DDR) perfusion imaging represents a novel imaging that allows pulmonary perfusion assessment without contrast medium administration, able to detect anomalies at the patient’s bedside, representing a promising advancement, particularly for critically ill or contrast-allergic patients. In parallel, interventional radiology has become integral to APE management, particularly for high-risk and intermediate–high-risk patients, with evolving intravascular treatment techniques such as catheter-directed thrombolysis, mechanical thrombectomy, and thrombus aspiration. This narrative review provides an overview of the latest developments in APE diagnostic imaging and interventional radiology, contextualizing them within current guideline recommendations for endovascular treatment. Full article

Gout is a chronic inflammatory disease characterized by the deposition of monosodium urate (MSU) crystals within joints, leading to recurrent acute flares and long-term tissue damage. While various hypotheses have been proposed to explain the self-limiting nature of acute gout attacks, we posit that aggregated neutrophil extracellular traps (aggNETs) play a central role in this process. This review focuses on the mechanisms underlying MSU crystal-induced formation of neutrophil extracellular traps (NETs) and explores their dual role in the clinical progression of gout. During the initial phase of acute flares, massive NET formation is accompanied by the release of preformed inflammatory mediators, which is a condition that amplifies inflammatory cascades. As neutrophil recruitment reaches a critical threshold, the NETs tend to form high-order aggregates (aggNETs). The latter encapsulate MSU crystals and further pro-inflammatory mediators within their three-dimensional scaffold. High concentrations of neutrophil serine proteases (NSPs) within the aggNETs facilitate the degradation of soluble inflammatory mediators and eventually promote the resolution of inflammation in a kind of negative inflammatory feedback loop. In advanced stages of gout, MSU crystal deposits are often visible via dual-energy computed tomography (DECT), and the formation of palpable tophi is frequently observed. Based on the mechanisms of resolution of inflammation and the clinical course of the disease, building on the traditional static model of “central crystal–peripheral fibrous encapsulation,” we have expanded the NETs component and refined the overall concept, proposing a more dynamic, multilayered, multicentric, and heterogeneous model of tophus maturation. Notably, in patients with late-stage gout, tophi exist in a stable state, referred to as “silent” tophi. However, during clinical tophus removal, the disruption of the structural or functional stability of “silent” tophi often leads to the explosive reactivation of inflammation. Considering these findings, we propose that future therapeutic strategies should focus on the precise modulation of NET dynamics, aiming to maintain immune equilibrium and prevent the recurrence of gout flares. Full article