Search Results (42)

Background: Patients with diabetes mellitus and nonobstructive coronary artery disease (NOCAD) may remain at increased cardiovascular risk despite the absence of flow-limiting stenosis. Quantitative coronary CT angiography (CCTA) enables comprehensive assessment of anatomical, functional, and inflammatory imaging biomarkers beyond luminal stenosis. This study aimed to evaluate the prognostic value of an automated multiparametric CCTA-derived imaging framework for risk stratification in patients with NOCAD, with exploratory assessment in those with diabetes mellitus. Methods: This retrospective single-center study included 485 patients with NOCAD who underwent CCTA between January 2020 and December 2021. Automated CCTA analysis was performed to quantify plaque burden, high-risk plaque features, CT-derived fractional flow reserve (CT-FFR), and perivascular fat attenuation index. The primary endpoint was major adverse cardiovascular events (MACE) during follow-up. Prognostic associations were assessed using Kaplan–Meier analysis, Cox regression, and hierarchical models. Results: During a median follow-up of approximately three years, MACE occurred in 56 patients. Patients with diabetes had a higher event rate than those without diabetes. Increased plaque burden, high-risk plaque features, elevated perivascular fat attenuation index, and reduced CT-FFR were associated with adverse outcomes. The fully integrated model combining anatomical, functional, and inflammatory CCTA-derived biomarkers improved risk stratification compared with plaque-based assessment alone. Conclusions: Automated multiparametric CCTA phenotyping may provide complementary prognostic information for risk stratification in patients with NOCAD. The diabetes-specific findings should be considered exploratory and require validation in larger prospective cohorts. Full article

Background/Objectives: Photon-counting computed tomography (PCCT) combined with radiomics enables advanced myocardial tissue characterization beyond conventional imaging. This study investigated whether myocardial radiomic features derived from PCCT are associated with nicotine status in patients without coronary artery disease. Methods: In this retrospective, single-center study, 104 patients (38 men, 66 women; median age 54 years) without coronary calcification (Agatston score = 0) underwent cardiac PCCT. Myocardial septal thickness was measured at three points during the 65–70% cardiac phase. Myocardial tissue was manually segmented, and 105 radiomic features were extracted. After correlation-based feature reduction, 45 independent features were used for analysis. Patients were categorized based on nicotine status. Machine learning models, including logistic regression, random forest, and gradient boosting, were trained and evaluated using stratified five-fold cross-validation. Model performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC) and additional classification metrics. Results: No significant differences in myocardial septal thickness were observed between smokers and non-smokers (p > 0.05). However, radiomic features enabled moderate discrimination between smokers and non-smokers. Logistic regression with L2 regularization achieved the best performance (ROC-AUC 0.66, balanced accuracy 0.67), outperforming random forest and gradient boosting models. The most relevant radiomic features primarily comprised higher-order texture and shape-based parameters associated with spatial gray-level heterogeneity and subtle variations in myocardial tissue architecture. Conclusions: PCCT-based radiomics may capture subtle myocardial imaging signatures associated with smoking status, even in the absence of structural changes detectable by conventional metrics. These findings highlight the potential of cardiac radiomics as a non-invasive imaging biomarker for early cardiovascular risk assessment and support its integration into advanced cardiac imaging workflows. Future multicenter studies with larger cohorts, external validation, and multimodal correlation are warranted to improve robustness and facilitate clinical translation. Full article

Purpose: Myocardial iron overload has been demonstrated to have a heterogeneous distribution. A segmental T2* CMR approach, with correction factors applied to account for artifacts, has been demonstrated to be feasible and has permitted a reduction in cardiac morbidity and mortality, by better capturing the heterogeneous distribution of myocardial iron overload. To the best of our knowledge, commercially available software does not provide a segmental T2* technique. Our aims were to prospectively examine a large population of healthy volunteers, stratified by sex and age, using the Black Blood MEGE T2* mapping technique, to obtain normative values of the myocardium, to assess their relationship with physiological variables, and to fix correction factors for a segmental approach by using a commercially available software. Methods: Fifty healthy subjects (M:F = 1:1, 20–69 years) underwent CMR without a contrast agent. Segmental T2* values were obtained using cvi42 software; global values were the mean. Inter-study, and intra- and inter-operator reproducibility were assessed to confirm the stability of the acquired data. The association of T2* values with physiological characteristics, and myocardial wall thickness were assessed. The fluctuation of all segments versus the mid-septum was calculated to obtain a correction factor for each segment for the software used. Regional T2* differences were examined. A p-value <0.05 was considered statistically significant. Results: Twenty-five males and females, five for each decade (mean age 43 ± 13.8 years), were included. The native T2* values in all subjects averaged at 34.03 ± 6.65 ms (range 29.9–37.9 ms). Reproducibility analyses showed good correlations between the various datasets (ICC > 0.80). A weakly negative correlation was observed between age and T2* (p = 0.04). Segmental correction factors were developed and found to be significantly different from correction factors developed by non-commercially available software on non-state-of-the-art technology for sequences and scanners. Conclusions: Age-specific normative values and higher normal cut-off values than the conservative 20 ms are recommended to avoid systematic biases in the identification of pathological findings. Moreover, the correction factors developed by using the most reproducible Black Blood MEGE sequences and a commercially available software on a scanner of the current era could be a significant step toward spreading a more sensitive T2* segmental approach in the clinical arena worldwide. Full article

Background/Objectives: Magnetic resonance imaging (MRI) provides a non-invasive means for a comprehensive assessment of the effect of radiation therapy (RT) on heart function. This study aims to determine RT induced cardiotoxicity in thoracic cancer patients using cardiac MRI. Methods: Cardiac MRI was performed at baseline and at six months post-treatment in patients undergoing standard-of-care RT for lung or esophageal cancers at a single institution. Parameters included regional myocardial strain in the longitudinal, circumferential, and radial directions as well as myocardium T1, T2, and extracellular-volume (ECV) maps. Cardiac segmental doses were extracted from the RT planning scans. The relationship between changes in segmental MRI parameters at six months and segmental heart RT dose were investigated. Results: Twelve patients underwent baseline MRI and four completed the follow-up MRI. Five of the segmental strain parameters showed notable changes between baseline and six-month follow-up. Increased doses in the heart base and apex were associated with moderate-to-large and mild deteriorations, respectively, in strain for all regions. Increased doses in the mid-ventricular regions were associated with improved strain in all regions. The segmental analysis revealed that myocardial regions nurtured by the left coronary artery are more negatively affected by radiation compared to those nurtured by the right coronary artery. Conclusions: Alterations in regional tissue and strain parameters on MRI vary according to local myocardial RT dose, suggesting there may be heterogeneity of radiation sensitivity for the heart substructures and regions. Changes in segmental strain parameters may reflect post-RT cardiac remodeling, but larger confirmatory studies are required. Full article

Background: The fat attenuation index (FAI) derived from coronary computed tomography angiography (CTA) is an emerging imaging biomarker of perivascular inflammation. Coronary flow reserve (CFR), assessed by phase-contrast (PC) cine cardiac magnetic resonance (CMR) of the coronary sinus, reflects coronary microvascular function. Although FAI has been linked to adverse outcomes in coronary artery disease (CAD), its relationship with CFR across different CAD stages is not well defined. Methods: We retrospectively evaluated 241 patients (mean age 73.4 ± 10.8 years; 149 men [61.8%]) who underwent both coronary CTA and CMR (122 with known CAD and 119 with suspected CAD). FAI was measured in the proximal left anterior descending (LAD), left circumflex (LCX), and right coronary (RCA) arteries. Impaired CFR was defined as <2.0. Univariable and multivariable logistic regression analyses were performed to identify factors associated with impaired CFR. Results: Impaired CFR was observed in 38 of 122 patients (31.1%) with known CAD and 26 of 119 (21.8%) with suspected CAD. Higher LAD-FAI was associated with impaired CFR in both groups: OR 1.06 (95% CI 1.01–1.11; p = 0.018) in known CAD and OR 1.08 (95% CI 1.02–1.15; p = 0.017) in suspected CAD. Correlation analysis also demonstrated an inverse relationship between LAD-FAI and CFR (p < 0.001), and the strength of association was comparable between the two groups. Conclusions: LAD-FAI was associated with impaired CFR in both suspected and known CAD, with comparable strength of association across the two groups. These findings indicate that perivascular inflammation, reflected by FAI, may relate to coronary microvascular dysfunction in different stages of CAD. Full article

Background: This study aims to evaluate the prevalence, spectrum, and coexistence of anatomical variations in the major branches of the abdominal aorta using Multidetector Computed Tomography (MDCT) angiography, with a specific emphasis on analyzing sex-related differences in a large-scale cohort. Methods: A retrospective analysis was conducted on 1174 patients (63.8% male, 36.2% female; mean age 60.54) who underwent abdominal CT angiography between January 2023 and June 2024. Images were acquired using a 128-slice MDCT scanner and reconstructed for detailed vascular assessment. Statistical comparisons between genders were performed using Chi-square and Fisher–Freeman–Halton tests, with p < 0.05 considered significant. Results: The celiac trunk (93.3%), superior mesenteric artery (SMA) (97.1%), and inferior mesenteric artery (IMA) (98.5%) predominantly showed classical patterns. However, significant sex-related differences were identified. Females exhibited significantly higher rates of classical patterns for the celiac trunk (96.2% vs. 91.7%), IMA (99.1% vs. 98.1%), right hepatic artery (RHA) (91.5% vs. 82.6%), and left hepatic artery (LHA) (95.8% vs. 85.4%). Conversely, males showed a higher prevalence of complex variations, including replaced/accessory hepatic arteries and the absence of the common hepatic artery. The number of right and left renal arteries was similar between sexes and did not show a significant difference, while horseshoe kidney was detected only in males. Conclusions: Abdominal vascular structures adhere to classical anatomy more frequently in females, while males exhibit greater morphological variability. These findings emphasize the necessity of gender-specific preoperative vascular mapping to optimize surgical outcomes and reduce morbidity. Full article

Background: Visceral artery aneurysms (VAAs) are rare but potentially life-threatening vascular lesions often clinically silent until rupture. The widespread use of advanced imaging has increased incidental detection, highlighting the need for accurate, noninvasive diagnostic strategies. Dual-Energy Computed Tomography Angiography (DECTA) offers potential advantages over conventional CT across diagnostic and post-treatment settings; however, its role in VAAs remains incompletely defined. This narrative review summarizes current evidence on DECTA applications in VAAs, focusing on diagnosis, emergency evaluation, and post-treatment follow-up. Methods: A non-systematic literature search of PubMed and Embase focusing on English-language articles up to June 2025 was performed. The search included peer-reviewed original research articles, systematic reviews, and meta-analyses addressing dual-energy CT and spectral CT in vascular and aneurysmal imaging. Case reports without technical data and non-English articles were excluded. Results: In the diagnostic phase, DECTA enhances tissue differentiation through virtual monoenergetic images, iodine maps, and material decomposition reconstructions. In the post-treatment setting, DECTA supports assessment after endovascular procedures, including coil embolization or stent graft placement. In VAAs, these techniques may improve aneurysm delineation, reduce metal artifacts after endovascular treatment, enable accurate detection of endoleaks or residual perfusion, and support volumetric follow-up. Virtual Non-Contrast images may reduce radiation exposure without compromising diagnostic confidence. Conclusions: DECTA represents a versatile imaging modality with potential benefits across the diagnostic, emergency, and post-treatment phases of VAA management. Although many applications are extrapolated from aortic and peripheral vascular disease, emerging evidence supports its growing clinical relevance. Further dedicated studies are needed to define its role in VAA-specific decision-making and follow-up. Full article

Background/Objectives: Super-resolution deep-learning reconstruction (SR-DLR) is an advanced image reconstruction technique, but its effect on dynamic myocardial computed tomography perfusion (CTP) imaging has not been evaluated. This study aimed to examine the impact of SR-DLR on image quality and perfusion parameters in dynamic myocardial CTP. Methods: Thirty-five patients who underwent dynamic myocardial CTP for coronary artery disease assessment were retrospectively analyzed. Two CTP datasets were reconstructed using hybrid iterative reconstruction (HIR) and SR-DLR. Image quality was compared qualitatively and quantitatively, including image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge rise slope (ERS). Equivalence of CT-derived myocardial blood flow (CT-MBF) between two reconstructions was tested using a previously reported 15% equivalence margin. Intra-patient variability of CT-MBF was evaluated using the robust coefficient of variation (rCV). Results: In the qualitative assessment, SR-DLR had significantly higher scores in contrast (4.0 vs. 2.0) and sharpness (4.5 vs. 2.5) compared with HIR (p < 0.001), while contrast scores were similar. In the quantitative assessment, SR-DLR demonstrated significantly lower image noise (19.4 vs. 29.4 HU), and improved SNR (6.1 vs. 4.1), CNR (13.7 vs. 10.9), and ERS (171.0 vs. 135.1 HU/mm) (all p < 0.001). Mean global CT-MBF was comparable (3.15 ± 0.91 mL/g/min for HIR vs. 3.18 ± 0.97 mL/g/min for SR-DLR) and equivalence was confirmed (p = 0.022). SR-DLR significantly reduced rCV compared with HIR (36.0% vs. 41.0%, p < 0.001). Conclusions: SR-DLR enhances image quality in dynamic myocardial CTP while maintaining mean global CT-MBF and reducing intra-patient variability. Full article

Background/Objectives: Aortic valve calcification is commonly evaluated using 3.0 mm true non-contrast (TNC) computed tomography (CT) images. This study evaluates the reproducibility of virtual non-contrast (VNC) reconstructions at different slice intervals using photon-counting detector CT (PCD-CT). Methods: In this retrospective study, we included 279 consecutive patients, who underwent PCD-CT for evaluation of native aortic valve between February 2023 and December 2023 with both TNC and VNC images at 3.0 and 1.5 mm slice intervals. Aortic valve calcium score (AVCS) and aortic valve calcium volume (AVCV) were compared between the two methods using paired t-tests. Agreement for continuous variables was assessed using inter-class coefficients (ICCs). Cohen’s Kappa (κ) was calculated to evaluate the agreement between different modalities in diagnosing severe AV calcification. Results: Compared to the standard, TNC images at 1.5 mm intervals showed higher AVCS (mean difference: −290 ± 418, p < 0.001), with high reproducibility between techniques (CS: ICC 0.969, [IQR 0.962, 0.975]). Compared with reference, VNC showed no significant differences in AVCS at either slice intervals, with excellent reproducibility (3.0 mm, ICC 0.970 [0.963, 0.976]; 1.5 mm, ICC 0.971 [0.964, 0.977]). Compared to TNC 3.0 mm, strong concordance was observed using other reconstruction techniques in assessing severe AV calcification (κ = 0.81 [95% CI: 0.74–0.88], 0.83 [95% CI: 0.76–0.90], and 0.83 [95% CI: 0.76–0.90] for TNC at 1.5 mm, VNC at 3.0 mm, and 1.5 mm, respectively), with low misclassification rates. Conclusions: Our study highlights high reproducibility in the evaluation of AVCS by VNC reconstruction at 3.0 and 1.5 mm intervals compared with reference offering a reliable alternative with an excellent diagnostic accuracy. Full article

This review focuses on the diverse etiologies of secondary spontaneous pneumothorax (SSP) and the crucial role of imaging in their diagnosis. Unlike primary spontaneous pneumothorax (PSP), which is typically due to ruptured blebs, SSP results from a wide array of underlying pulmonary conditions that can pose significant diagnostic challenges. These include infections like tuberculosis, airway diseases such as chronic obstructive pulmonary disease, malignancies (primary and metastatic), interstitial lung diseases like sarcoidosis, cystic lung diseases such as lymphangioleiomyomatosis, and connective tissue disorders. In women, catamenial pneumothorax secondary to endometriosis should be considered. The role of radiologists is crucial in uncovering these underlying conditions. While chest radiography is the initial imaging modality, computed tomography (CT) provides superior sensitivity for detecting subtle parenchymal abnormalities. Advanced techniques like photon-counting detector CT offer further benefits, including enhanced spatial resolution, reduced noise, and lower radiation dose, potentially revealing underlying causes that might be missed with conventional CT. This enhanced visualization of subtle parenchymal changes, small airways, and vascular structures can be the key to diagnosing the underlying cause of pneumothorax. Recognizing the diverse etiologies of SSP and utilizing advanced imaging techniques is paramount for accurate diagnosis, appropriate management, and improved patient outcomes. Full article

Background/Objectives: To develop and validate deep learning-based models for detecting significant steno-occlusion (SSO)—defined as luminal narrowing greater than 50%—of the femoropopliteal arteries using maximum intensity projection (MIP) images from lower extremity CT angiography (CTA). Methods: This retrospective study utilized MIP images of lower extremity CTA performed between January 2021 and December 2023 for internal model development. Deep learning-based models were developed sequentially to diagnose SSO: screening with single anteroposterior image, followed by four-segment rotational analysis that divided each femoropopliteal artery into four segments and incorporated multi-angle images. Given the cropped images and the shape of stenosis, models were trained to classify the presence of SSO. A temporal validation dataset comprised MIP images from lower extremity CTA performed between January and June 2024. Results: In total, 56,496 segment images from 642 patients (mean age: 68.2 ± 13.5 years; 472 men) were included in the internal dataset. In the single-image analysis, RDNet achieved the highest mean AUC of 0.886 for SSO detection. In the four-segment rotational analysis, RDNet also demonstrated the highest mean AUC, reaching 0.964 in both half-set and full-set approaches. While RDNet recorded the highest mean AUC, all other models showed improved AUCs as the number of input images increased (p < 0.05). In the temporal validation dataset, RDNet again achieved the highest mean AUC (0.959) in the half-set analysis. Conclusions: The deep learning-based model, particularly RDNet, demonstrated excellent performance in detecting SSO of peripheral arteries on MIP images from lower extremity CTA. Full article

Aortic valve stenosis (AS) is a valvular heart disease that imposes a high afterload on the left ventricle (LV) due to restricted opening of the aortic valve, resulting in LV hypertrophy. Severe AS can lead to syncope, angina pectoris, and heart failure. The number of patients with AS has been increasing due to aging populations, the growing prevalence of lifestyle-related diseases, and advances in diagnostic technologies. Therefore, accurate diagnosis and appropriate treatment of AS are essential. In recent years, transcatheter aortic valve implantation (TAVI) has become feasible, and the number of procedures has rapidly increased, particularly among elderly patients. As treatment options for AS expand and diversify, detailed pre-procedural evaluation has become increasingly important. In particular, diagnostic imaging modalities such as computed tomography (CT) have advanced significantly, with notable improvements in image quality. With recent advancements in CT technology—such as increased detector rows, faster gantry rotation speeds, new image reconstruction methods, and the introduction of dual-energy imaging—the scope of cardiac assessment has expanded beyond the coronary arteries to include valves, myocardium, and the entire heart. This includes evaluating restricted AV opening and cardiac function using four-dimensional imaging, assessing AV annulus diameter and AS severity via calcium scoring with a novel motion correction algorithm, and detecting myocardial damage through late-phase contrast imaging using new reconstruction techniques. In cases of pre-TAVI evaluation or congenital bicuspid valves, CT is also valuable for assessing extracardiac structures, such as access routes and associated congenital heart anomalies. In addition, recent advancements in CT technology have made it possible to significantly reduce radiation exposure during cardiac imaging. CT has become an extremely useful tool for comprehensive cardiac evaluation in patients with aortic stenosis, especially those being considered for surgical treatment. Full article

Background: CT image guidance and navigation, although routinely used in complex endovascular procedures, is an unexplored territory in evolving vascular robotic procedures. In robotic surgery, it promises the better localization of vasculature, the optimization of port placement, less inadvertent tissue damage, and increased patient safety during the dissection of retroperitoneal structures. However, unknown tissue displacement resulting from induced pneumoperitoneum and positional changes compared to the preoperative CT scan can pose significant limitations to the reliability of image guidance. We aimed to study the displacement of retroperitoneal organs and vasculature due to factors such as increased intra-abdominal pressure (IAP) due to CO₂ insufflation and patient positioning (PP) using intraoperative CT imaging in a cadaveric model. Methods: A thawed, fresh-frozen human cadaveric model was positioned according to simulated procedural workflows. Intra-arterial, contrast-enhanced CT scans were performed after the insertion of four laparoscopic ports in the abdomen. CT scans were performed with 0–5–15–25 mmHg IAPs in supine, left lateral decubitus, right lateral decubitus, Trendelenburg, and reverse Trendelenburg positions. Euclidean distances between fixed anatomical bony and retroperitoneal vascular landmarks were measured and compared across different CT scans. Results: Comparing the effects of various IAPs to the baseline (zero IAP) in the same PP, an average displacement for retroperitoneal vascular landmarks ranged from 0.6 to 3.0 mm (SD 1.0–2.8 mm). When changing the PPs while maintaining the same IAP, the average displacement of the retroperitoneal vasculature ranged from 2.0 to 15.0 mm (SD 1.7–7.2 mm). Conclusions: Our preliminary imaging findings from a single cadaveric model suggest minimal (~3 mm maximum) target vasculature displacement in the retroperitoneum due to elevated IAP in supine position and higher displacement due to changes in patient positioning. Similar imaging studies are needed to quantify procedural workflow-specific and anatomy-specific deformation, which would be invaluable in developing and validating advanced tissue deformation models, facilitating the routine applicability and usefulness of CT image guidance for target delineation during robotic vascular procedures. Full article

Introduction and objective: The pre-transplant protocol for lung transplant candidates includes a chest CT scan to assess disease progression and often coronary angiography (CA) to rule out coronary artery disease (CAD). Coronary artery calcium is commonly observed in these pre-transplant CT scans. This study aims to evaluate the relationship between coronary calcium detected on CT and findings from CA to determine whether calcium presence could serve as an additional criterion for selecting patients for CA. Material and Methods: We included 252 consecutive lung transplant patients who had both a CT scan and CA within 365 days of each other. Coronary calcium quantification was performed using artery-based, segment artery-based, and visual assessment methods. CA findings were classified by stenosis severity: ≤20%, 21–70%, and >70%. Results: This study showed very high concordance (kappa = 0.896; 95% CI: 0.843–0.948) between the three methods, especially in distinguishing patients without and with coronary calcium (kappa = 1.000; 95% CI: 0.929–1.071). ROC analysis identified the absence of coronary calcium as the best cutoff to differentiate patients with ≤20% stenosis from those with >21%, with a sensitivity of 73.5%, specificity of 55.7%, PPV of 28.5%, and NPV of 90%. Only 11 patients (8.7%) without coronary calcium had stenosis of 21–70%, and only 2 (1.6%) had stenosis > 70%. Conclusions: The visual assessment method yielded results similar to the other two quantification methods. The absence of coronary calcium in pre-transplant CT may be a useful criterion for selecting patients for CA. Full article

Objective: The purpose of this study was to explore the impact of pericardial T1 mapping as a potential supportive non-contrast cardiovascular magnetic resonance (CMR) parameter in the diagnosis of acute pericarditis. Additionally, we investigated the relationship between T1 mapping values in acute pericarditis patients and their demographic data, cardiovascular risk factors, clinical parameters, cardiac biomarkers, and cardiac function. Method: This retrospective study included CMR scans in 35 consecutive patients with acute pericarditis (26 males, 45.54 ± 23.38 years). Moreover, we included 17 sex- and age-matched healthy controls (12 males, mean age 47.78 ±19.38 years). CMR-derived pericardial T1 mapping values, which included all pericardial structures within the pericardial layers—encompassing both pericardial effusion and pericardial layer thickness—were analyzed and compared between acute pericarditis patients and controls. Results: Compared to the matched control group, acute pericarditis patients demonstrated significantly lower pericardial T1 mapping values (2137 ms ± 519 vs. 3268 ms ± 362, p = 0.001). In the multivariable analysis, the pericardial T1 mapping value was independently associated with the severity of pericardial late gadolinium enhancement (LGE) (β coefficient = −3.271, p = 0.003). The receiver operating characteristic curve analysis showed that the diagnostic performance of pericardial T1 mapping in discriminating acute pericarditis patients was excellent, with an area under the curve of 0.97 (95% CI = 0.94–0.98), using a threshold of 2862.5 ms. Conclusions: Pericardial T1 mapping values could serve as an additional non-contrast CMR parameter for identifying patients with acute pericarditis, demonstrating an independent association with the severity of pericardial LGE. Full article