Search Results (30)

Background: While epicardial adipose tissue (EAT) is a known predictor of adverse cardiovascular outcomes, lipomatous hypertrophy of the interatrial septum (LHIS) is composed of metabolically active fat such as brown adipose tissue, which may exert a different effect. This study investigates the coronary atherosclerosis profile in patients with LHIS using CTA, compared with a propensity score-matched control group. Methods: A total of 142 patients were included (n = 71 with LHIS and n = 71 controls) and propensity score-matched for age, gender, BMI, and the major CV risk factors (matching level, <0.05). CTA imaging parameters included HRP, coronary stenosis severity (CADRADS), and CAC score. Results: The mean age was 60.9 years +/− 10.6, there were nine (6.3%) women, and the mean BMI is 28.04 kg/m² +/− 4.99. HRP prevalence was significantly lower in LHIS patients vs. controls (21.1% vs. 40.8%; p < 0.011), while CAC (p = 0.827) and CADRADS (p = 0.329) were not different, and there was no difference in the obstructive disease rate. There was no difference in lipid panels (cholesterol, LDL, HDL, TG) and statin intake rate. Conclusions: HRP prevalence is lower in patients with LHIS than controls, while coronary stenosis severity and CAC score are not different. Clinical relevance: LHIS may serve as imaging biomarker for reversed CV risk. Full article

In recent years, there has been a surge in the extrusion-based 3D printing of materials for various biomedical applications. This work presents a novel methodology for optimizing extrusion-based 3D bioprinting of a gelatin/siloxane hybrid material for biomedical applications. A systematic approach integrating rheological characterization, computational fluid dynamics simulation (CFD), and machine-learning-based image analysis, was employed. Rheological tests revealed a shear stress of 50 Pa, a maximum viscosity of 3 × 10⁵ Pa·s, a minimum viscosity of 0.089 Pa·s, and a shear rate of 15 rad/s (27G nozzle, 180 kPa pressure, 32 °C temperature, 30 mm/s velocity) for a BIO X bioprinter. While these parameters yielded constructs with 54.5% similarity to the CAD design, a multi-faceted optimization strategy was implemented to enhance fidelity, computational fluid dynamics simulations in SolidWorks, coupled with a custom-develop a binary classifier convolutional neuronal network for post-printing image analysis, facilitated targeted parameter refinement. Subsequent printing optimized parameters (25G nozzle, 170 kPa, 32 °C, 20 mm/s) achieved a significantly improved similarity of 92.35% CAD, demonstrating efficacy. The synergistic combination of simulation and machine learning ultimately enabled the fabrication of complex 3D constructs with a high fidelity of 94.13% CAD similarity, demonstrating the efficacy and potential of this integrated approach for advanced biofabrication. Full article

Background: Optimization of pulmonary nodule detection across varied imaging protocols remains challenging. We evaluated four DL-CAD systems and manual reading with volume rendering (VR) for performance under varying radiation doses and reconstruction methods. VR refers to a post-processing technique that generates 3D images by assigning opacity and color to CT voxels based on Hounsfield units. Methods: An anthropomorphic phantom with 169 artificial nodules was scanned at three dose levels using two kernels and three reconstruction algorithms (1080 image sets). Performance metrics included sensitivity, specificity, volume error (AVE), and Lung-RADS classification accuracy. Results: DL-CAD systems demonstrated high sensitivity across dose levels and reconstruction settings, with three fully automatic DL-CAD systems (0.92–0.95) outperforming manual CT readings (0.72), particularly for sub-centimeter nodules. However, DL-CAD systems exhibited limitations in volume measurement and Lung-RADS classification accuracy, especially for part-solid nodules. VR-enhanced manual reading outperformed original CT interpretation in nodule detection, particularly benefiting less-experienced radiologists under suboptimal imaging conditions. Conclusions: These findings underscore the potential of DL-CAD for lung cancer screening and the clinical value of VR in low-dose settings, but they highlight the need for improved classification algorithms. Full article

Background: There is a large overlap in the risk profiles and pathophysiologies of coronary artery disease (CAD) and cerebrovascular macroangiopathy. Therefore, this study aimed to analyse whether findings in CAD examination by coronary angiography or cardio-computer tomography (cardio-CT) are predictive of cerebrovascular macroangiopathy. Methods: Our study was a prospective, bicentric, cross-sectional cohort study. A total of 191 patients without earlier CAD diagnosis who underwent a cardio-CT scan or coronary angiography for the screening of CAD during clinical routine were serially included. Two groups were formed based on the criterion of CAD (yes/no), and both were subsequently examined using sonography of the carotids. The CAD scores Syntax score I, Agatston equivalent score, and CAD-RADS score as well as AHA classification were determined. In cerebrovascular examinations, plaques and stenoses of the internal carotid artery (ICA) and the intima-media thickness (IMT) of the common carotid artery were analysed. Demographic and medical data such as the presence of arterial hypertension, diabetes mellitus, obesity, nicotine abuse, and dyslipidaemia were documented. The primary endpoint was the nominal association between CAD and ICA stenosis controlled for age and gender; secondary endpoints were correlations between ICA stenoses and CAD scores. Results: Of the 191 serially recruited patients (58% male, 65 ± 11 yrs.), 101 fulfilled CAD criteria; 90 did not. Of all patients, 137 had ICA plaques, and 11 thereof had an ICA stenosis ≥ 50%. No association was found between CAD and ICA stenosis (Wald = 0.24; p = 0.624). Accordingly, there was no association between IMT and Syntax score I (Wald = 0.38; p = 0.706), Agatston equivalent score (Wald = 0.89; p = 0.380), CAD-RADS score (Wald = 0.90; p = 0.377), or AHA classification (Wald = 0.21; p = 0.837). Common cardiovascular risk factors, i.e., arterial hypertension (Wald = 4.47; p = 0.034), diabetes mellitus (Wald = 7.61; p = 0.006), and nicotine abuse (Wald = 0.83; p = 0.028), were associated with newly diagnosed CAD but not with ICA plaques, stenosis, or increased IMT. Conclusions: In our cohort, newly diagnosed CAD was associated with typical risk factors. However, neither CAD nor these risk factors were associated with cerebrovascular disease. This suggests that in patients without prior CAD diagnosis, findings from CAD examinations might not be reliably predictive of cerebrovascular disease. Full article

Background: The diagnostic performance of preprocedural CT angiography in detecting coronary artery disease (CAD) in patients scheduled for transcatheter aortic valve implantation (TAVI) has been reported. However, data on predictors of diagnostic inaccuracy are sparse. We sought to investigate clinical characteristics and imaging criteria that predict the inaccurate assessment of coronary artery stenosis based on pre-TAVI-CT. Methods: The patient- and vessel-level analysis of all CT datasets from 192 patients (mean age 82.1 ± 4.8 years; 63.5% female) without known CAD or severe renal dysfunction was performed retrospectively in a blinded fashion. Significant CAD was defined as a CAD-RADS™ 2.0 category ≥ 4 by CT. Invasive coronary angiography (ICA) served as the reference standard for relevant CAD (≥70% luminal diameter stenosis or fractional flow reserve ≤ 0.80). Pertinent clinical characteristics and imaging criteria of all true-positive (n = 71), false-positive (n = 30), false-negative (n = 4), and true-negative patient-level CT diagnoses (n = 87) for relevant stenosis according to ICA were assessed. Results: In the univariate per-patient analysis, the following parameters yielded discriminative power (p < 0.10) regarding inaccurate CAD assessment by pre-TAVI-CT: age, atrial fibrillation, scanner generation, and image quality. Factors independently associated with CT diagnostic inaccuracy were determined using multivariable logistic regression analysis: a younger age (odds ratio [OR] 0.87; 95% confidence interval [CI] 0.80 to 0.94; p < 0.01) and insufficient CT image quality (OR 0.6; CI 0.41 to 0.89; p < 0.01). Conclusions: Our results demonstrate younger age and poor CT image quality to predict less accurate CAD assessments by pre-TAVI-CT in comparison with ICA. Knowledge of these predictors may aid in more efficient coronary artery interpretations based on pre-TAVI-CT. Full article

Objectives: Our study aims to investigate the correlation between epicardial adipose tissue (EAT) volume assessed with non-contrast cardiac CT (NCCCT) and sex, age, coronary artery disease reporting and data system (CAD-RADS 2.0) categories, and coronary artery calcification (CAC) extent. The secondary aim is to establish the average values of EAT in a population considered healthy for coronary artery disease (CAD). Materials and Methods: We retrospectively analyzed patients who underwent coronary computed tomography angiography (CCTA) at our institution from January 2023 to August 2024. The CAD-RADS 2.0 scoring system was applied to assess the extent of CAD; CAC extent was quantified according to the Agatston score. EAT was segmented semi-automatically in NCCCT images, and its volume was subsequently measured. Correlation analyses between EAT volume, sex, patient age, CAC, and CAD-RADS categories were conducted. Results: A total of 489 consecutive patients met the inclusion criteria (63.96 ± 12.18 years; 214 females). The mean EAT volume ± SD in those categorized as CAD-RADS 0 (57.25 ± 15.45 years, 120 patients) was 117.43 ± 50.30 cm³: values were higher in men (121.07 ± 53.31 cm³) than in women (114.54 ± 47.98 cm³). EAT volumes positively correlated with age, male sex, CAD severity, and CAC scores. Conclusions: According to our results, males in all CAD-RADS categories have a greater amount of EAT than females. A positive correlation between the volume of EAT and factors such as age (p = 0.003), CAD-RADS categories (p: 0.004), and coronary calcium score (p = 0.0001) with a strong influence exerted by sex was demonstrated. Our results reinforce the observation that higher EAT volumes are associated with a more severe coronary artery disease. Full article

Background/objectives: Cardiovascular risk (CVR) stratification in clinical settings remains limited. This study aims to evaluate clinical parameters that could improve the identification of higher-than-expected coronary artery disease (CAD) in CT scan coronarography. Methods: In a cross-sectional study of asymptomatic patients from the Integrated Cardiovascular Assessment Program (ICAP), volunteers aged 40–80 without diagnosed cardiovascular disease were assessed. CVR factors like obesity, lipid and glucose profiles, liver fibrosis risk (FIB-4 ≥ 1.3), C-reactive protein, and family history of CVD were evaluated. Patients were stratified by CVR following ESC guidelines. “CVR excess” was defined as CAD-RADS ≥ 2 in low-to-moderate-risk (LMR), CAD-RADS ≥ 3 in high-risk (HR), and CAD-RADS ≥ 4 in very-high-risk (VHR) groups. Results: Among 219 patients (mean age 57.9 ± 1.15 years, 14% female), 43.4% were classified as LMR, 49.3% as HR, and 7.3% as VHR. “CVR excess” was observed in 18% of LMR, 15% of HR, and 19% of VHR patients. LMR patients with prior statin use and HR patients with obesity were more likely to have “CVR excess” (p < 0.01 and p < 0.05, respectively). FIB-4 modified the effect of statin use and obesity on “CVR excess” prediction (p for interactions < 0.05). Models including age, sex, and both interactions showed a strong discrimination for “CVR excess” in LMR and HR groups (AUROC 0.84 (95% CI 0.73–0.95) and 0.82 (95% CI 0.70–0.93), respectively). Conclusions: Suspected liver fibrosis combined with statin use in LMR patients and obesity in HR patients is associated with CVR excess, providing potential indications for image CAD assessment in asymptomatic patients. Full article

Background/Objectives: Some calculated total blood count readings are investigated as novel additional readings to help with evaluation of personalized CAD patients’ clinical management and prognosis. We aimed to investigate the association between readings such as NLR, MLR, PLR, NMR, LMR, MHR, SII, and SIRI and the severity of CAD in patients with SAP. Methods: This retrospective pilot study included 166 patients. All patients underwent CA or CCTA, or both, to assess severity of CAD. Patients were divided three ways: (1) according to presence (n = 146) or absence (n = 20) of CAD; (2) according to Gensini score; (3) according to the CAD-RADS score. Results: Patients with CAD had lower LMR, higher NLR, SIRI, MLR, and SII compared to patients without CAD (p < 0.001 and p = 0.018, respectively for SII). According to the CAD severity by Gensini score, the NLR, MLR, SII, and SIRI values increase and LMR decreases gradually with severity of CAD (p < 0.001). A moderate correlation was found between SII (r = 0.511, p < 0.001), NLR (r = 0.567, p < 0.001), and SIRI (r = 0.474, p < 0.001) and severity of CAD according to Gensini score. MLR and LMR had a low corelation with severity of CAD according to Gensini score (r = 0.356, p < 0.001; r = −0.355, p < 0.001, respectively). The CAD-RADS score weakly correlated with NLR and MHR (r = 0.365, p < 0.001; r = 0.346, p < 0.001, respectively), and moderately with LMR, MLR, and SIRI (r = −0.454, p < 0.001; r = 0.455, p < 0.001; r = 0.522, p < 0.001, respectively). Conclusions: NLR, LMR, and SIRI appear to be potential predictors of chronic inflammation, and SIRI is the best predictor of the degree of atherosclerosis of all the other assessed blood parameters. Full article

Objective: To investigate the association between sarcopenia, as appraised with CT-derived muscle metrics, and cardiovascular status, as assessed via coronary CT angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS) and with pericoronary adipose tissue (pCAT) metrics. Methods: A retrospective observational study conducted on patients who underwent CCTA. The cross-sectional area (CSA) and attenuation values of the paravertebral muscles at the T8 level and the pectoralis major muscles at the T6 level were measured. The patient height was employed for the normalization of the skeletal muscle CSA. The pCAT attenuation around the coronary arteries was assessed, and the CAD severity was graded using the CAD-RADS reporting system. Regression analyses were performed to assess the impact of demographics, clinical factors, and CT variables on the CAD-RADS and pCAT. Results: A total of 220 patients were included (132 males, median age 65 years). Regression analyses showed the associations of CAD with age and sex (p < 0.001). Familiarity with CAD was related to the left anterior descending artery pCAT (p = 0.002) and circumflex artery pCAT (p = 0.018), whereas age was related to the left anterior descending artery pCAT (p = 0.032). Weak positive correlations were found between the lower muscle density and lower pCAT attenuation (ρ = 0.144–0.240, p < 0.039). Conclusions: This study demonstrated weak associations between the sarcopenia indicators and the cardiovascular risk, as assessed by the CAD severity and pCAT inflammation. However, these correlations were not strong predictors of CAD severity, as age and traditional cardiovascular risk factors overshadowed the impact of sarcopenia in the cardiovascular risk assessment. Full article

Our study develops a computer-aided diagnosis (CAD) system for breast ultrasound by presenting an innovative frequency domain technique for extracting mass irregularity features, thereby significantly boosting tumor classification accuracy. The experimental data consists of 5252 ultrasound breast tumor images, including 2745 benign tumors and 2507 malignant tumors. A Support Vector Machine was employed to classify the tumor as either benign or malignant, and the effectiveness of the proposed features set in distinguishing malignant masses from benign ones was validated. For the constructed CAD system, the performance indices’ accuracy, sensitivity, specificity, PPV, and NPV were 92.91%, 89.94%, 91.38%, 90.29%, and 91.45%, respectively, and the area index in the ROC analysis (AUC) was 0.924, demonstrating our method’s superiority over traditional spatial gray level dependence (SGLD), the ratio of depth to width, the count of depressions, and orientation features. Therefore, the constructed CAD system with the proposed features will be able to provide a precise and quick distinction between benign and malignant breast tumors with minimal training time in clinical settings. Full article

The aim of this paper is to demonstrate the difference in usefulness of the coronary artery calcium score (CACS) and the full assessment of the severity of coronary artery disease in coronary computed tomography angiography (CCTA) studies. The difference between the population risk of coronary artery disease (CAD) assessed by the CACS and the severity of CAD was demonstrated in images from two CCTA studies. The first image is from a patient with a CACS of 0 and significant coronary artery stenosis. In the native phase of CCTA examination, no calcified changes were detected in the topography of the coronary arteries. In the middle section of the left descending artery (LAD), at the level of the second diagonal branch (Dg2), a large non-calcified atherosclerotic plaque was visible. Mid-LAD stenosis was estimated to be approximately 70%. The second image features a patient with a high CACS but no significant coronary artery stenosis. The calcium score of individual coronary arteries calculated using the Agatston method was as follows: left main (LM) 0, LAD 403, left circumflex (LCx) 207.7, right coronary artery (RCA) 12. CACS was 622.7, representing a significant population risk of significant CAD. In the proximal and middle sections of the LAD, numerous calcified and mixed atherosclerotic plaques with positive remodeling were visible, causing stenosis of 25–50%. Similarly, in the proximal and middle sections of the LCx, numerous calcified and mixed atherosclerotic plaques with positive remodeling were visualized, causing stenoses of 25–50%. Calcified atherosclerotic plaques were found in the RCA, causing stenosis <25%. The entire CCTA image met CAD-RADS 2 (coronary artery disease reporting and data system) criteria. In summary, CACS may be applicable in population-based studies to assess the risk of significant CAD. In the evaluation of individual patients, a comprehensive assessment of CAD severity based on the angiographic phase of the CCTA examination should be used. Full article

The intracavitary coronary arteries (ICCA) course is a rare phenomenon, where the segments of the coronary artery go through the atria or ventricles of the heart. In the past, these changes were incidentally detected during invasive diagnostic procedures for other reasons, as well as during postmortem examinations. As the use of multidetector computed tomography angiography (CTA) becomes more widespread, it has emerged that the incidence of ICCA has been underestimated. We present images from two coronary computed tomography angiography cases, which document the existence of ICCA in patients with non-specific chest pain. In the first case, in a 66-year-old woman, in addition to confirming coronary artery disease without significant stenosis (CAD-RADS 2-category 2 in the coronary-artery-disease-reporting and data system), the course of the middle section of the right coronary artery (RCA) in the lumen of the right atrium was demonstrated. In the second case, in a 47-year-old man in whom the presence of atherosclerotic lesions in the coronary arteries was excluded (CAD-RADS 0), the course of the distal segment of the left anterior descending (LAD) was found in the lumen of the apical layers of the right ventricle. To sum up, it should be stated that coronary CTA is a non-invasive diagnostic method that allows for visualization of the ICCA. In coronary CTA performed for indications consistent with the guidelines of scientific societies, attention should also be paid to the possible intracavitary course of the coronary arteries. The identification of such a course of the coronary arteries may be useful when preparing the patient for potential future invasive procedures involving the cardiac cavities. Full article

Investigating aircraft flight dynamics often requires dynamic wind tunnel testing. This paper proposes a non-contact, off-board instrumentation method using vision-based techniques. The method utilises a sequential process of Harris corner detection, Kanade–Lucas–Tomasi tracking, and quaternions to identify the Euler angles from a pair of cameras, one with a side view and the other with a top view. The method validation involves simulating a 3D CAD model for rotational motion with a single degree-of-freedom. The numerical analysis quantifies the results, while the proposed approach is analysed analytically. This approach results in a 45.41% enhancement in accuracy over an earlier direction cosine matrix method. Specifically, the quaternion-based method achieves root mean square errors of 0.0101 rad/s, 0.0361 rad/s, and 0.0036 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. Notably, the method exhibits a 98.08% accuracy for the pitch rate. These results highlight the performance of quaternion-based attitude estimation in dynamic wind tunnel testing. Furthermore, an extended Kalman filter is applied to integrate the generated on-board instrumentation data (inertial measurement unit, potentiometer gimbal) and the results of the proposed vision-based method. The extended Kalman filter state estimation achieves root mean square errors of 0.0090 rad/s, 0.0262 rad/s, and 0.0034 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. This method exhibits an improved accuracy of 98.61% for the estimation of pitch rate, indicating its higher efficiency over the standalone implementation of the direction cosine method for dynamic wind tunnel testing. Full article

The aim of the study was to assess the relationship between the presence of atherosclerotic lesions in the carotid arteries detected by ultrasound and the occurrence of atherosclerosis in the coronary arteries determined by computed tomography (CT) in patients with arterial hypertension (HTA). A total of 83 patients with HTA were qualified for the study (age: 71.3 ± 8.5 years). All subjects underwent carotid arteries ultrasound and coronary arteries CT. The carotid plaque score was assessed using ultrasound. The studied group was divided into two subgroups: a subgroup with the carotid plaque score ≤ 1 (A) and a subgroup with carotid plaque score ≥2 (B). Coronary arteries CT assessed coronary artery calcium score (CACS) and degree of coronary stenosis based on CAD-RADS. In subgroup B, a significantly higher CACS (411.3 ± 70.1 vs. 93.5 ± 31.8) and significantly higher grade in the CAD-RADS classification were demonstrated than in subgroup A (CAD-RADS ≥ 3: 21.8 vs. 6.0%). The regression analysis showed that carotid plaque score and age are independent risk factors for the severity of atherosclerotic lesions in the coronary arteries. In summary, ultrasound assessment of the carotid plaque score in patients with HTA could be considered as surrogate indicator of the risk and severity of atherosclerotic changes in the coronary arteries, but further studies are necessary to corroborate these results. Full article

As the number of coronary computed tomography angiography (CTA) examinations is expected to increase, technologies to optimize the imaging workflow are of great interest. The aim of this study was to investigate the potential of artificial intelligence (AI) to improve clinical workflow and diagnostic accuracy in high-volume cardiac imaging centers. A total of 120 patients (79 men; 62.4 (55.0–72.7) years; 26.7 (24.9–30.3) kg/m²) undergoing coronary CTA were randomly assigned to a standard or an AI-based (human AI) coronary analysis group. Severity of coronary artery disease was graded according to CAD-RADS. Initial reports were reviewed and changes were classified. Both groups were similar with regard to age, sex, body mass index, heart rate, Agatston score, and CAD-RADS. The time for coronary CTA assessment (142.5 (106.5–215.0) s vs. 195.0 (146.0–265.5) s; p < 0.002) and the total reporting time (274.0 (208.0–377.0) s vs. 350 (264.0–445.5) s; p < 0.02) were lower in the human AI than in the standard group. The number of cases with no, minor, or CAD-RADS relevant changes did not differ significantly between groups (52, 7, 1 vs. 50, 8, 2; p = 0.80). AI-based analysis significantly improves clinical workflow, even in a specialized high-volume setting, by reducing CTA analysis and overall reporting time without compromising diagnostic accuracy. Full article