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Abstract Background Fractional Flow Reserve (FFR) is the gold standard for the functional evaluation of coronary arteries, which is effective in selecting patients for revascularization, avoiding unnecessary procedures, and reducing treatment costs. However, its use is limited due to invasiveness, high cost, and complexity. Therefore, the non-invasive estimation of FFR using artificial intelligence (AI) methods is crucial. Objective This study aimed to identify the AI techniques used for FFR estimation and to explore the features of the studies that applied AI techniques in FFR estimation. Methods The present systematic review was conducted by searching five databases, PubMed, Scopus, Web of Science, IEEE, and Science Direct, based on the search strategy of each database. Results Five hundred seventy-three articles were extracted, and by applying the inclusion and exclusion criteria, twenty-five were finally selected for review. The findings revealed that AI methods, including Machine Learning (ML) and Deep Learning (DL), have been used to estimate the FFR. Conclusion This study shows that AI methods can be used non-invasively to estimate FFR, which can help physicians diagnose and treat coronary artery occlusion and provide significant clinical performance for patients.

"n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Coronary artery anomalies may be seen in 1-5% of coronary angiographies. Origin of the left coronary artery from right aortic cusp is a very rare anomaly and its incidence is about 0.15%. This anomaly could be presented by myocardial ischemia and even sudden cardiac death during exercise in young patients. For the diagnosis of coronary anomalies different diagnostic modalities such as, echocardiography, angiography and CT angiography can be helpful."n"nCases: We report 3 cases with this anomaly and two of them did not have any lesion in their coronary arteries One of these patients had severe coronary artery disease and underwent coronary artery bypass graft surgery."n"nConclusion: Although abnormal origin of left coronary artery from right aortic valsalva sinus is a rare anomaly, due to causing ischemic cardiac symptoms and the possibility of sudden cardiac death it is considered an important anomaly. For definite diagnosis of this anomaly coronary angiography and/or CT angiography is useful.

Abstract This study aimed to design an end-to-end deep learning model for estimating the value of fractional flow reserve (FFR) using angiography images to classify left anterior descending (LAD) branch angiography images with average stenosis between 50 and 70% into two categories: FFR > 80 and FFR ≤ 80. In this study 3625 images were extracted from 41 patients’ angiography films. Nine pre-trained convolutional neural networks (CNN), including DenseNet121, InceptionResNetV2, VGG16, VGG19, ResNet50V2, Xception, MobileNetV3Large, DenseNet201, and DenseNet169, were used to extract the features of images. DenseNet169 indicated higher performance compared to other networks. AUC, Accuracy, Sensitivity, Specificity, Precision, and F1-score of the proposed DenseNet169 network were 0.81, 0.81, 0.86, 0.75, 0.82, and 0.84, respectively. The deep learning-based method proposed in this study can non-invasively and consistently estimate FFR from angiographic images, offering significant clinical potential for diagnosing and treating coronary artery disease by combining anatomical and physiological parameters.

Due to the increase in the average age and metabolic diseases in the Iranian population, an increase in the prevalence of atherosclerotic aortic valve stenosis is expected. In severe and symptomatic cases of this disease, if the valve is not replaced, the death rate increases by 50% with every two years of age. Non-invasive intervention of aortic valve implantation through catheter (TAVI) is suitable for patients in whom open heart surgery is impossible or associated with high risk. Despite the widespread use of the TAVI method around the world and in some medical centers of the country, until now this method has not been started and performed in the Mazandaran Heart Center, a specialized and sub-specialized referral center for cardiovascular patients in Mazandaran province and other parts of the north of the country; Also, provision of a 3D esophageal echocardiography device is necessary as a basic prerequisite. In this policy brief, evidence-based solutions in this field and the challenges ahead have been proposed and presented to policymakers and managers in the field of cardiovascular health by the researchers of the Cardiovascular Research Center of Mazandaran University of Medical Sciences. Therefore, the officials pay sufficient attention to the necessity of equipping the Mazandaran heart center with a 3D transesophageal echocardiography device and funding it, providing physical facilities including a dedicated operating room and training facilities to form a specialized team skilled in TAVI procedure and insurance coverage for this Service is emphasized.

Background and Aim: Core needle biopsy (CNB) is less invasive and has fewer side effects compared to surgical procedures, and provides accurate information about the nature of the tumor. The aim of this study was to evaluate the efficacy of CNB in the diagnosis of the cause of lymphadenopathy. Materials and Methods: In this study, 153 patients with lymphadenopathy underwent CNB from 2014 to 2018. Immunohistochemistry staining with appropriate markers was performed. Excisional biopsy, clinical and radiological data were evaluated using spss-21 softwere, data were analyzed by one way ANOVA and tukey test (p

This paper proposes a precise and general multiple linear regression (MLR) model to predict the unconfined compressive strength (UCS) of various soil types. The study used a wide range of data sets, including 952 data points considering 39 soil types with varying grain sizes. The model inputs were soil physical properties, grain size, age, mixture proportion, and chemical composition of binder materials. An innovative and novel approach was developed to enhance the accuracy of the MLR model, a randomized exploratory algorithm. The model demonstrated significant accuracy with a 0.921 R2 in the testing data set. The Bayesian model averaging (BMA) method was employed for feature reduction, focusing on important variables. Alternative models were also developed based on the significant variables highlighted by the BMA approach, all showing high accuracy in predicting the UCS. The proposed models demonstrated superiority over traditional approaches based on the data set size and statistical metrics. The paper provides instances of predicting soil UCS and determining the mix design corresponding to the target UCS. [ABSTRACT FROM AUTHOR]

Dynamic analysis of problems with complex geometries requires utilization of numerical methods. To completely capture the effects of seismic wave propagation in a system, one must consider the structure or irregularity within its encompassing half-space. Correct consideration of half-space in a numerical model is important specially when it comes to cases where the half-space contains semi-infinite irregularities. In this study, a generalized numerical methodology is presented for dynamic analysis of a half-space with semi-infinite irregularities. The methodology is first verified through comparison with analytical solution of known problems. Then the method is employed to solve the dynamic analysis of an arbitrary-shaped existing valley within a half-space under propagating plane harmonic SH wave with different angles of incidence. Results indicate complete capability of the methodology in solving wave propagation problems for complex systems without the usual restrictions of common existing methods. [ABSTRACT FROM AUTHOR]

Background: We aimed to compare the diagnostic accuracy of mammography and ultrasonography and their breast imaging-reporting and data system (BI-RADS) classification versus breast core needle biopsy (CNB) findings in distinguishing the breast masses. Methods: This cross-sectional study was conducted during 2016-2018 on female patients who were referred to a radiology center in Babol, northern Iran, for routine screening and/or for CNB. Patients underwent sonography and mammography by a senior radiologist. The breast lesions were also evaluated according to BI-RADS classification. CNB was performed on the breast masses by the same radiologist and pathological procedures were performed by an expert pathologist. Descriptive statistics were used to analyze the data. Results: In total, 213 breast masses were finally assessed, of which 107 (50.2 %) masses were benign and 106 (49.8 %) masses were malignant. The sensitivity for mammography and ultrasound alone was 72.6% and 68.9%, respectively. This rate for combined mammography and ultrasound was 84.9%. About BI-RADS classification, 28 masses were classified as BI-RADS 3, 99 as BI-RADS 4A, 4 as BI-RADS 4B, 18 as BI-RADS 4C, and 64 as BI-RADS 5. BI-RADS 4A had the highest sensitivity (70.1%) among BI-RADS categories. The highest specificity pertained to BI-RADS 3 and 5 (100%) among BI-RADS categories. Also, the highest accuracy was related to BI-RADS 5 (80.3%). Conclusion: The results of the present study showed that combined mammography and ultrasound had a higher rate of accuracy than mammography or ultrasound alone. Furthermore, the imaging methods BI-RADS classification had an acceptable positive predictive value.

Increasing heat transfer in straight pipes, particularly in applications like heat exchangers, can be achieved by incorporating fins into the pipe wall. However, in curved pipes, the presence of more intricate flows resulting from centrifugal forces can alter this effect. The current study investigates how both the height and angular position of radial fins simultaneously influence the flow patterns within curved pipes. Adjusting the placement of radial fins is identified as a cost-effective and strategic approach to improve both the hydrodynamic and thermal efficiency in curved pipe systems. The numerical analysis focuses on studying laminar, incompressible flow in curved tubes with radial fins. The mass, momentum, and energy conservation equations in toroidal coordinates were discretized with the second-order finite difference method on a staggered grid, followed by their solution through the projection algorithm. The results indicate that adapting the angular position of the fins improves the thermal-hydraulic performance by 51.8%, 48.4%, 36.3%, and 20.6% for one to four fins, respectively. These changes are closely related to the behavior of the secondary flows. Furthermore, altering the height of the fins reveals that for three fins within the tube, the most optimal fin height is half of the tube radius. In other cases, a fin height equal to 0.7 multiplied by the tube radius provides the highest performance. From the numerical results, it is found that the primary factor affecting the heat transfer rate in curved pipes is the strength of secondary motions, while the generation of friction is influenced only by the axial velocity. [ABSTRACT FROM AUTHOR]

Abstract Background Prevalence of coronary heart disease (CHD) risk factors are increasing in developing countries. The present study aimed to assess the prevalence of self-reported CHD and evaluate the role of various risk factors on its prevalence in the Tabari cohort study (TCS) population. Methods The enrollment phase of TCS was performed between June 2015 and November 2017. In the current study, data were derived from information collecting from the enrollment phase of TCS. In the enrollment phase, 10,255 individuals aged 35–70 living in urban and mountainous areas of Sari (northern part of Iran) were entered into the study. Educational level, socioeconomic and marital status, history of smoking, opium and alcohol abuse/addiction, level of daily physical activity, indices of obesity, and traditional risk factors of the participants were determined. Results The prevalence of CHD was measured at 9.2%. Older individuals (P

Purpose: In all types of ischemic stroke, especially in the acute phase, excessive oxidative stress causes structural and functional damage to the brain. This may play a major role in the pathophysiology of the brain damage. Higher serum levels of bilirubin have therapeutic effects in oxidative stress-induced stroke. Nevertheless, role of increased serum levels of bilirubin in the acute phase of ischemic stroke is controversial. Methods: This study was a cross-sectional prospective descriptive study conducted in the Emergency Department (ED) of Imam Reza hospital, Tabriz University of Medical Sciences, Tabriz, Iran, throughout six months. 275 ischemic stroke patients were evaluated based on their brain CT scan infarct size, NIHSS, MRS, and serum levels of bilirubin. Later, data were analyzed using SPSS software. Results: Total, direct and indirect bilirubin levels were significantly higher in expired patients (p< 0.0001). Total (p< 0.0001), direct (p< 0.0001) and indirect (p< 0.0001) bilirubin levels, NIHSS score (p< 0.0001), and ischemic area (p< 0.0001) significantly predicted the outcome in these patients. Conclusion: Total, direct and indirect bilirubin levels was significantly associated with mortality in the acute phase of ischemic stroke patients.