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Background: Myocardial feature tracking (FT) provides a comprehensive analysis of myocardial deformation from cine balanced steady‐state free‐precession images (bSSFP). However, FT remains time‐consuming, precluding its clinical adoption. Purpose: To compare left‐ventricular global radial strain (GRS) and global circumferential strain (GCS) values measured using automated DeepStrain analysis of short‐axis cine images to those calculated using manual commercially available FT analysis. Study Type: Retrospective, single‐center. Population: A total of 30 healthy subjects and 120 patients with cardiac disease for DeepStrain development. For evaluation, 47 healthy subjects (36 male, 53 ± 5 years) and 533 patients who had undergone a clinical cardiac MRI (373 male, 59 ± 14 years). Field Strength/Sequence: bSSFP sequence at 1.5 T (Phillips) and 3 T (Siemens). Assessment: Automated DeepStrain measurements of GRS and GCS were compared to commercially available FT (Circle, cvi42) measures obtained by readers with 1 year and 3 years of experience. Comparisons were performed overall and stratified by scanner manufacturer. Statistical Tests: Paired t‐test, linear regression slope, Pearson correlation coefficient (r). Results: Overall, FT and DeepStrain measurements of GCS were not significantly different (P = 0.207), but measures of GRS were significantly different. Measurements of GRS from Philips (slope = 1.06 [1.03 1.08], r = 0.85) and Siemens (slope = 1.04 [0.99 1.09], r = 0.83) data showed a very strong correlation and agreement between techniques. Measurements of GCS from Philips (slope = 0.98 [0.98 1.01], r = 0.91) and Siemens (slope = 1.0 [0.96 1.03], r = 0.88) data similarly showed a very strong correlation. The average analysis time per subject was 4.1 ± 1.2 minutes for FT and 34.7 ± 3.3 seconds for DeepStrain, representing a 7‐fold reduction in analysis time. Data Conclusion: This study demonstrated high correlation of myocardial GCS and GRS measurements between freely available fully automated DeepStrain and commercially available manual FT software, with substantial time‐saving in the analysis. Evidence Level: 3 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Purpose: To develop and evaluate a free breathing non‐electrocardiograph (ECG) myocardial T1* mapping sequence using radial imaging to quantify the changes in myocardial T1* between rest and exercise (T1*reactivity) in exercise cardiac MRI (Ex‐CMR). Methods: A free‐running T1* sequence was developed using a saturation pulse followed by three Look‐Locker inversion‐recovery experiments. Each Look‐Locker continuously acquired data as radial trajectory using a low flip‐angle spoiled gradient‐echo readout. Self‐navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid‐diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free‐breathing acquisition. Finally, data acquired at both mid‐diastole and end‐expiration are picked and reconstructed by a low‐rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise. Results: Numerical simulation demonstrated that changes in T1* are related to the changes in T1; however, other factors such as breathing motion could influence T1* measurements. Phantom T1* values measured using free‐running T1* mapping sequence had good correlation with spin‐echo T1 values and was insensitive to heart rate. In the Ex‐CMR study, the measured T1* reactivity was 10% immediately after exercise and declined over time. Conclusion: The free‐running T1* mapping sequence allows free‐breathing non‐ECG quantification of changes in myocardial T1* with physiological exercise. Although, absolute myocardial T1* value is sensitive to various confounders such as B1 and B0 inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise. [ABSTRACT FROM AUTHOR]

Background: Heart failure patients with preserved ejection fraction (HFpEF) are at increased risk of future hospitalization. Contrast agents are often contra‐indicated in HFpEF patients due to the high prevalence of concomitant kidney disease. Therefore, the prognostic value of a noncontrast cardiac magnetic resonance imaging (MRI) for HF‐hospitalization is important. Purpose: To develop and test an explainable machine learning (ML) model to investigate incremental value of noncontrast cardiac MRI for predicting HF‐hospitalization. Study Type: Retrospective. Population: A total of 203 HFpEF patients (mean, 64 ± 12 years, 48% women) referred for cardiac MRI were randomly split into training validation (143 patients, ~70%) and test sets (60 patients, ~30%). Field strength: A 1.5 T, balanced steady‐state free precession (bSSFP) sequence. Assessment: Two ML models were built based on the tree boosting technique and the eXtreme Gradient Boosting model (XGBoost): 1) basic clinical ML model using clinical and echocardiographic data and 2) cardiac MRI‐based ML model that included noncontrast cardiac MRI markers in addition to the basic model. The primary end point was defined as HF‐hospitalization. Statistical Tests: ML tool was used for advanced statistics, and the Elastic Net method for feature selection. Area under the receiver operating characteristic (ROC) curve (AUC) was compared between models using DeLong's test. To gain insight into the ML model, the SHapley Additive exPlanations (SHAP) method was leveraged. A P‐value <0.05 was considered statistically significant. Results: During follow‐up (mean, 50 ± 39 months), 85 patients (42%) reached the end point. The cardiac MRI‐based ML model using the XGBoost algorithm provided a significantly superior prediction of HF‐hospitalization (AUC: 0.81) compared to the basic model (AUC: 0.64). The SHAP analysis revealed left atrium (LA) and right atrium (RV) strains as top imaging markers contributing to its performance with cutoff values of 17.5% and −15%, respectively. Data Conclusions: Using an ML model, RV and LA strains measured in noncontrast cardiac MRI provide incremental value in predicting future hospitalization in HFpEF. Evidence Level: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Purpose: To reduce inflow and motion artifacts in free‐breathing, free‐running, steady‐state spoiled gradient echo T1‐weighted (SPGR) myocardial perfusion imaging. Method: Unsaturated spins from inflowing blood or out‐of‐plane motion cause flashing artifacts in free‐running SPGR myocardial perfusion. During free‐running SPGR, 1 non‐selective RF excitation was added after every 3 slice‐selective RF excitations to suppress inflow artifacts by forcing magnetization in neighboring regions to steady‐state. Bloch simulations and phantom experiments were performed to evaluate the impact of the flip angle and non‐selective RF frequency on inflowing spins and tissue contrast. Free‐running perfusion with (n = 11) interleaved non‐selective RF or without (n = 11) were studied in 22 subjects (age = 60.2 ± 14.3 years, 11 male). Perfusion images were graded on a 5‐point Likert scale for conspicuity of wall enhancement, inflow/motion artifact, and streaking artifact and compared using Wilcoxon sum‐rank testing. Result: Numeric simulation showed that 1 non‐selective RF excitation applied after every 3 slice‐selective RF excitations produced superior out‐of‐plane signal suppression compared to 1 non‐selective RF excitation applied after every 6 or 9 slice‐selective RF excitations. In vitro experiments showed that a 30° flip angle produced near‐optimal myocardial contrast. In vivo experiments demonstrated that the addition of interleaved non‐selective RF significantly (P <.01) improved conspicuity of wall enhancement (mean score = 4.4 vs. 3.2) and reduced inflow/motion (mean score = 4.5 vs. 2.5) and streaking (mean score = 3.9 vs. 2.4) artifacts. Conclusion: Non‐selective RF excitations interleaved between slice‐selective excitations can reduce image artifacts in free‐breathing, ungated perfusion images. Further studies are warranted to assess the diagnostic accuracy of the proposed solution for evaluating myocardial ischemia. [ABSTRACT FROM AUTHOR]

Purpose: To develop and evaluate a real‐time phase contrast (PC) MRI protocol via complex‐difference deep learning (DL) framework. Methods: DL used two 3D U‐nets to separately filter aliasing artifact from radial real‐time velocity‐compensated and complex‐difference images. U‐nets were trained with synthetic real‐time PC generated from electrocardiograph (ECG) ‐gated, breath‐hold, segmented PC (ECG‐gated segmented PC) acquired at the ascending aorta of 510 patients. In 21 patients, free‐breathing, ungated real‐time (acceleration rate = 28.8) and ECG‐gated segmented (acceleration rate = 2) PC were prospectively acquired at the ascending aorta. Hemodynamic parameters (cardiac output [CO], stroke volume [SV], and mean velocity at peak systole [peak mean velocity]) were measured for ECG‐gated segmented and DL‐filtered synthetic real‐time PC and compared using Bland‐Altman and linear regression analyses. Additionally, hemodynamic parameters were quantified from DL‐filtered, compressed‐sensing (CS) ‐reconstructed, and gridding reconstructed prospective real‐time PC and compared to ECG‐gated segmented PC. Results: Synthetic real‐time PC with DL showed strong correlation (R > 0.98) and good agreement with ECG‐gated segmented PC for quantified hemodynamic parameters (mean‐difference: CO = −0.3 L/min, SV = −4.3 mL, peak mean velocity = −2.3 cm/s). On average, DL required 0.39 s/frame to filter prospective real‐time PC, which was 4.6‐fold faster than CS. Compared to CS, DL showed superior correlation, tighter limits of agreement (LOAs), better bias for peak mean velocity, and worse bias for CO and SV. Compared to gridding, DL showed similar correlation, tighter LOAs for CO and SV, similar bias for CO, and worse bias for SV and peak mean velocity. Conclusion: The complex‐difference DL framework accelerated real‐time PC‐MRI by nearly 28‐fold, enabling rapid free‐running real‐time assessment of flow hemodynamics. [ABSTRACT FROM AUTHOR]

Purpose: To develop a free‐breathing sequence, that is, Multislice Joint T1‐T2, for simultaneous measurement of myocardial T1 and T2 for multiple slices to achieve whole left‐ventricular coverage. Methods: Multislice Joint T1‐T2 adopts slice‐interleaved acquisition to collect 10 single‐shot electrocardiogram‐triggered images for each slice prepared by saturation and T2 preparation to simultaneously estimate myocardial T1 and T2 and achieve whole left‐ventricular coverage. Prospective slice‐tracking using a respiratory navigator and retrospective image registration are used to reduce through‐plane and in‐plane motion, respectively. Multislice Joint T1‐T2 was validated through numerical simulations and phantom and in vivo experiments, and compared with saturation‐recovery single‐shot acquisition and T2‐prepared balanced Steady‐State Free Precession (T2‐prep SSFP) sequences. Results: Phantom T1 and T2 from Multislice Joint T1‐T2 had good accuracy and precision, and were insensitive to heart rate. Multislice Joint T1‐T2 yielded T1 and T2 maps of nine left‐ventricular slices in 1.4 minutes. The mean left‐ventricular T1 difference between saturation‐recovery single‐shot acquisition and Multislice Joint T1‐T2 across healthy subjects and patients was 191 ms (1564 ± 60 ms versus 1373 ± 50 ms; P <.05) and 111 ms (1535 ± 49 ms vs 1423 ± 49 ms; P <.05), respectively. The mean difference in left‐ventricular T2 between T2‐prep SSFP and Multislice Joint T1‐T2 across healthy subjects and patients was −6.3 ms (42.4 ± 1.4 ms vs 48.7 ± 2.5; P <.05) and −5.7 ms (41.6 ± 2.5 ms vs 47.3 ± 2.7; P <.05), respectively. Conclusion: Multislice Joint T1‐T2 enables quantification of whole left‐ventricular T1 and T2 during free breathing within a clinically feasible scan time of less than 2 minutes. [ABSTRACT FROM AUTHOR]

Purpose: To develop and validate a saturation‐delay‐inversion recovery preparation, slice tracking and multi‐slice based sequence for measuring whole‐heart native T1. Method: The proposed free‐breathing sequence performs T1 mapping of multiple left‐ventricular slices by slice‐interleaved acquisition to collect 10 electrocardiogram‐triggered single‐shot slice‐selective images for each slice. A saturation‐delay‐inversion recovery pulse is used for T1 preparation. Prospective slice tracking by the diaphragm navigator and retrospective registration are used to reduce through‐plane and in‐plane motion, respectively. The proposed sequence was validated in both phantom and human subjects (12 healthy subjects and 15 patients who were referred for a clinical cardiac MR exam) and compared with saturation recovery single‐shot acquisition (SASHA) and modified Look‐Locker inversion recovery (MOLLI). Results: Phantom T1 measured by the proposed sequence had excellent agreement (R2 = 0.99) with the ground‐truth T1 and was insensitive to heart rate. In both healthy subjects and patients, the proposed sequence yielded nine left‐ventricular T1 maps per volume in less than 2 minutes (healthy volunteers: 1.8 ± 0.4 minutes; patients: 1.9 ± 0.2 minutes). The average T1 of whole left ventricle for all healthy subjects and patients were 1560 ± 61 and 1535 ± 49 ms by SASHA, 1208 ± 42 and 1233 ± 56 ms by MOLLI5(3)3, and 1397 ± 34 and 1433 ± 56 ms by the proposed sequence, respectively. The corresponding coefficient of variation of T1 were 6.2 ± 1.4% and 5.8 ± 1.6%, 5.3 ± 1.1% and 5.1 ± 0.8%, and 4.9 ± 0.8% and 4.5 ± 0.8%, respectively. Conclusion: The proposed sequence enables quantification of whole heart T1 with good accuracy and precision in less than 2 minutes during free breathing. [ABSTRACT FROM AUTHOR]

We developed a deep convolutional neural network (CNN) based method to remove streaking artefact from accelerated radial acquisitions of myocardial T1-mapping images. A deep CNN based on a modified U-Net architecture was developed and trained to remove the streaking artefacts from under-sampled T1 mapping images. A total of 2090 T1-weighted images for 33 patients (55 ± 15 years, 19 males) and five healthy subjects (30 ± 14 years, 2 males) were used for training and testing the network. The images were acquired using radial slice interleaved T1 mapping sequence (STONE) and retrospectively under-sampled to achieve acceleration rate of 4 (corresponding to 48 spokes). The dataset was split into training and testing subsets with 23 subjects (60%) and 15 subjects (40%), respectively. For generating voxel-wise T1 maps, a two-parameter fitting model was used. Network performance was evaluated using normalized mean square error (NMSE), structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) metrics. The proposed network allowed fast (<0.3 s/image) removal of the artefact from all T1-weighted testing images and the corresponding T1 maps with PSNR = 64.3 ± 1.02, NMSE = 0.2 ± 0.09 and SSIM = 0.9 ± 0.3 × 10−4. There was no statistically significant difference between the measured T1 maps for both per-subject (reference: 1085 ± 37 ms, CNN: 1088 ± 37 ms, p = 0.4) and per-segment (reference: 1084 ± 48 ms, CNN: 1083 ± 58 ms, p = 0.9) analyses. In summary, deep CNN allows fast and reliable removal of streaking artefact from under-sampled radial T1 mapping images. Our results show that the highly non-linear operations of deep CNN processing of T1 mapping images do not impact accurate reconstruction of myocardial T1 maps. [ABSTRACT FROM AUTHOR]

Background: In patients with suspected or known hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) provides diagnostic and prognostic value. However, contraindications and long-term retention of gadolinium have raised concern about repeated gadolinium administration in this population. Alternatively, native T1 -mapping enables identification of focal fibrosis, the substrate of LGE. However HCM-specific heterogeneous fibrosis distribution leads to subtle T1 -maps changes that are difficult to identify.Purpose: To apply radiomic texture analysis on native T1 -maps to identify patients with a low likelihood of LGE(+), thereby reducing the number of patients exposed to gadolinium administration.Study Type: Retrospective interpretation of prospectively acquired data.Subjects: In all, 188 (54.7 ± 14.4 years, 71% men) with suspected or known HCM.Field Strength/sequence: A 1.5T scanner; slice-interleaved native T1 -mapping (STONE) sequence and 3D LGE after administration of 0.1 mmol/kg of gadobenate dimeglumine.Assessment: Left ventricular LGE images were location-matched with native T1 -maps using anatomical landmarks. Using a split-sample validation approach, patients were randomly divided 3:1 (training/internal validation vs. test cohorts). To balance the data during training, 50% of LGE(-) slices were discarded.Statistical Tests: Four sets of texture descriptors were applied to the training dataset for capture of spatially dependent and independent pixel statistics. Five texture features were sequentially selected with the best discriminatory capacity between LGE(+) and LGE(-) T1 -maps and tested using a decision tree ensemble (DTE) classifier.Results: The selected texture features discriminated between LGE(+) and LGE(-) T1 -maps with a c-statistic of 0.75 (95% confidence interval [CI]: 0.70-0.80) using 10-fold cross-validation during internal validation in the training dataset and 0.74 (95% CI: 0.65-0.83) in the independent test dataset. The DTE classifier provided adequate labeling of all (100%) LGE(+) patients and 37% of LGE(-) patients during testing.Data Conclusion: Radiomic analysis of native T1 -images can identify ~1/3 of LGE(-) patients for whom gadolinium administration can be safely avoided.Level Of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020. J. Magn. Reson. Imaging 2020;52:906-919. [ABSTRACT FROM AUTHOR]

Several deep‐learning models have been proposed to shorten MRI scan time. Prior deep‐learning models that utilize real‐valued kernels have limited capability to learn rich representations of complex MRI data. In this work, we utilize a complex‐valued convolutional network (ℂNet) for fast reconstruction of highly under‐sampled MRI data and evaluate its ability to rapidly reconstruct 3D late gadolinium enhancement (LGE) data. ℂNet preserves the complex nature and optimal combination of real and imaginary components of MRI data throughout the reconstruction process by utilizing complex‐valued convolution, novel radial batch normalization, and complex activation function layers in a U‐Net architecture. A prospectively under‐sampled 3D LGE cardiac MRI dataset of 219 patients (17 003 images) at acceleration rates R = 3 through R = 5 was used to evaluate ℂNet. The dataset was further retrospectively under‐sampled to a maximum of R = 8 to simulate higher acceleration rates. We created three reconstructions of the 3D LGE dataset using (1) ℂNet, (2) a compressed‐sensing‐based low‐dimensional‐structure self‐learning and thresholding algorithm (LOST), and (3) a real‐valued U‐Net (realNet) with the same number of parameters as ℂNet. LOST‐reconstructed data were considered the reference for training and evaluation of all models. The reconstructed images were quantitatively evaluated using mean‐squared error (MSE) and the structural similarity index measure (SSIM), and subjectively evaluated by three independent readers. Quantitatively, ℂNet‐reconstructed images had significantly improved MSE and SSIM values compared with realNet (MSE, 0.077 versus 0.091; SSIM, 0.876 versus 0.733, respectively; p < 0.01). Subjective quality assessment showed that ℂNet‐reconstructed image quality was similar to that of compressed sensing and significantly better than that of realNet. ℂNet reconstruction was also more than 300 times faster than compressed sensing. Retrospective under‐sampled images demonstrate the potential of ℂNet at higher acceleration rates. ℂNet enables fast reconstruction of highly accelerated 3D MRI with superior performance to real‐valued networks, and achieves faster reconstruction than compressed sensing. [ABSTRACT FROM AUTHOR]

Background: Celiac disease (CD), a serious autoimmune disorder that occurs in people who are genetically predisposed, is induced by dietary gluten intake and affects primarily the small intestine. Many studies have identified an increased risk of cardiovascular problems in patients with CD. Moreover, these patients are susceptible to certain liver diseases, as well as fibrosis. Objective: The aim of this study was to assess the presence of fibrosis using the De Ritis ratio, determining its effect on the electromechanical features of the left atrium and its susceptibility to atrial fibrillation (AF) in patients with CD. Methods: A total of 97 patients diagnosed with CD by antibody test and biopsy were included in this prospective study. Two groups were created from these patients, a fibrosis-prone (FP) group and a non-fibrosis-prone (NFP) group, according to the cut-off value, as defined in previously published reports, for the AST/ALT ratio. Electrocardiographic and echocardiographic examinations were performed as part of the study. Results: There were no differences in the baseline characteristics and conventional echocardiographic parameters of the defined groups. However, the patients in the FP group, as compared to those in the NFP group, had significantly increased PWD (56.68±6.48 ms vs. 37.49±6.22 ms, P<0.001). Additionally, significantly higher interatrial (60.50±13.05 ms vs. 29.40±11.55 ms, P<0.001), intra-left atrial (44.18±14.12 ms vs. 21.02±11.99 ms, P<0.001), and intra-right atrial (15.61±8.91 ms vs. 8.38±4.50 ms, P<0.001) EMD was found among the patients in the FP group compared to that of the NFP group. Conclusion: It is believed that the susceptibility to AF cited in previous studies may be related to fibrosis. Our study is the first to examine the possible effects of fibrosis on AF susceptibility in patients with CD, whereby we propose a new biomarker for prediction of AF susceptibility of these patients. [ABSTRACT FROM AUTHOR]

Introduction: Paraoxonase (PON1) is an enigmatic enzyme with multiple enzymatic properties including arylesterase and lactonase activities besides its ability to hydrolyze the toxic metabolite of parathion, paraoxon. The aim of this study was to determine the phenotype distribution of PON1 in patients with cardiac disease who were classified in coronary artery bypass grafting (CABG), heart valve disease (HVD), heart failure (HF) and ST elevation myocardial infarction (STEMI) groups and healthy subjects as a control group.Material and Methods: A total of 300 people (100 cardiac surgery (70 CABG and 30 HVD), 70 HF, 30 STEMI patients and 100 healthy controls) were admitted to this study. Individual variations in PON1 were determined using the dual substrate (paraoxon and phenylacetate) method.Results: The following phenotype distributions were found in the cardiac disease and control groups: cardiac disease group (n = 200): 48.5% (QQ), 42.5% (QR), 9% (RR) and control group (n = 100): 58% (QQ), 39% (QR), 3% (RR). RR (high activity) phenotypic distribution was more common in the cardiac disease group than in controls (p = 0.04). In particular, the frequency of the RR phenotype was two- to three-fold higher in the STEMI and HF patients compared to the controls as well as CABG and HVD groups.Conclusions: We found a higher percentage of RR phenotype in STEMI and HF patients compared to a large control group as well as compared to two other groups of cardiac disease patients. [ABSTRACT FROM AUTHOR]

Objective In our study, we aimed to evaluate the effect of weight loss on left and right ventricular functions in obese patients. Methods Thirty patients with a BMI greater than 30 kg/m2 and without any exclusion criteria were included in the study. Left ventricular systolic and diastolic functions were assessed with conventional and tissue Doppler echocardiography ( TDE). At the end of 3 months, echocardiographic examination was repeated in patients with weight loss for cardiac function evaluation and it was compared to the baseline echocardiographic parameters. Results At the end of 3 months of weight loss period, conventional Doppler echocardiography revealed an improvement in diastolic functions with an increase in mitral E-wave, a decrease in mitral A-wave and an increase in E/A ratio. Deceleration time and isovolumetric relaxation time were ascertained shortened and Tei index decreased. TDE showed an increase in left ventricular lateral wall systolic wave (Sm) and E-wave velocity (Em). Mitral septal annular isovolumetric acceleration time ( IVA), Sm and Em, were found to be increased, whereas Tei index was ascertained reduced. Right ventricular tissue Doppler examination following weight loss revealed an increase in RV- IVA, RV-Sm, and RV-Em, and a decrease in Tei index. Conclusion We disclosed that left ventricular structural changes and diastolic dysfunction occur in obese patients, and by weight loss, these abnormalities may be reversible which we demonstrated both by conventional and TDE. In addition, obesity might impair RV function as well, and we observed an enhancement in right ventricular functions by weight loss. [ABSTRACT FROM AUTHOR]

Urotensin II (U-II) was thought to be one of the mediators of primary renal sodium retention due to effects on renal sodium excretion. For this purpose, the relationship between U-II and overhydration was investigated. A total of 107 patients were enrolled in the study. According to body compositor monitor analysis, fluid overload up to 1.1 L, was considered normohydration. Patients were divided according to hydration status; overhydrate ( n = 42) and normohydrate ( n = 65) were studied in both groups. Pulse waveform velocity propagation for arterial stiffness and blood pressure analysis and echocardiographic left ventricular and left atrial indices were performed with known fluid overload-related parameters. U-II levels were measured by using Human ELISA kit. In overhydrated group, U-II levels were significantly lower. All parameters (blood pressure, arterial stiffness parameters, echocardiographic data, age, gender, diabetes, U-II, hemoglobin) correlated with overhydration, were determined by linear regression model (method = enter), when considered together, U-II was found to be an independent predictor from other conventional overhydration-related parameters. Male sex, left ventricular mass index, left atrial volume index, hemoglobin value were found to be independent predictors for overhydration. Considering the association of low U-II levels with adverse cardiovascular events and its role in sodium retention, we think that low U-II levels can be accepted as a potential therapeutic target in patients with hypervolemic cardio-renal syndrome. [ABSTRACT FROM AUTHOR]

Introduction: Patients with peripheral arterial disease (PAD) are at increased risk for all-cause mortality and cardiovascular mortality. Aim: To present anatomical and morphological characteristics of patients who underwent endovascular stenting with laboratory and our mid-term results. Material and methods: One hundred fifty-three patients (mean age: 62.8, 86% male) who underwent percutaneous intervention of lower extremity arteries were included in the study. Demographic characteristics, medical history, physical examination and laboratory findings of patients were analyzed. Patients' lesions were classified according to the TransAtlantic Inter-Society Consensus (TASC). Clinical outcomes included complications and mortality, 6-minute walking distance, functional class (NYHA) and patency rates. Results: Seventy percent of patients had hypertension, 42% were smokers, 78% had coronary artery disease, 20% had coronary artery bypass grafting, 55% had diabetes mellitus and 71% had dyslipidemia. Six patients with diabetes mellitus and poor wound healing despite medical therapy were treated with stenting leading to alleviation of pain and avoidance of amputation. The initial technical success rate of revascularization was 95.6% (153/160). Our mid-term results show that percutaneous procedures in lower extremity arterial diseases can be performed with low complication and high success rates. Patients' 6-minute walk distance, ankle/ brachial index values, functional class and the status of foot ulcers were evaluated. Conclusions: Especially in patients with distal vascular disease, poor wound healing and no chance of surgical revascularization, percutaneous endovascular revascularization may provide good blood flow and prevent amputation. [ABSTRACT FROM AUTHOR]

The article describes a case of successful percutaneous coil embolization of a tortuous coronary artery fistula in a 60-year-old man using the anchor technique. Diagnostic coronary angiography revealed a relatively large coronary fistula originating from the proximal portion of the circumflex artery to the pulmonary artery. The occurrence of angina and inferior ischemia in the patient as revealed by myocardial perfusion scintigraphy was associated with the fistula and coronary artery steal.