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RESUMEN La angioplastia transluminal coronaria (ATC) es una de las principales estrategias de revascularización en pacientes con enfermedad coronaria aterosclerótica (ECA). Numerosos estudios respaldan la optimización de la ATC mediante métodos de imagen endovascular; sin embargo, estos métodos son subutilizados en la práctica clínica contemporánea y enfrentan desafíos en la interpretación de los datos obtenidos, por lo que la integración de la inteligencia artificial (IA) se vislumbra como una solución atractiva para promover y simplificar su uso. La IA se define como un programa computarizado que imita la capacidad del cerebro humano para recopilar y procesar datos. El aprendizaje de máquinas es una subdisciplina de la IA que implica la creación de algoritmos capaces de analizar grandes conjuntos de datos sin suposiciones previas, mientras que el aprendizaje profundo se centra en la construcción y entrenamiento de redes neuronales artificiales profundas y complejas. Así, se ha demostrado que la incorporación de sistemas de IA a los métodos de imagen endovascular incrementa la precisión de la ATC, disminuye el tiempo del procedimiento y la variabilidad interobservador en la interpretación de los datos obtenidos, promueve así una mayor adopción y facilita su utilización. El propósito de la presente revisión es destacar cómo los sistemas actuales basados en IA pueden desempeñar un papel fundamental en la interpretación de los datos generados por los métodos de imagen endovascular, lo que conduce a una mejora en la optimización de la ATC en pacientes con ECA.

ABSTRACT Percutaneous coronary intervention (PCI) is one of the primary revascularization strategies in patients with coronary artery disease (CAD). Several studies support the use of intravascular imaging methods to optimize PCI. However, these methods are underutilized in contemporary clinical practice and face challenges in data interpretation. Therefore, the incorporation of artificial intelligence (AI) is seen as an attractive solution to promote and simplify their use. AI can be defined as a computer program that mimics the human brain in its ability to collect and process data. Machine learning is a sub-discipline of AI that involves the creation of algorithms capable of analyzing large datasets without making prior assumptions, while deep learning focuses on the construction and training of deep and complex artificial neural networks. The incorporation of AI systems to intravascular imaging methods improves the accuracy of PCI, reduces procedure duration, and minimizes interobserver variability in data interpretation. This promotes their wider adoption and facilitates their use. The aim of this review is to highlight how current AI-based systems can play a key role in the interpretation of data generated by intravascular imaging methods and optimize PCI in patients with CAD.

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Coronary artery disease is defined by the existence of atherosclerotic plaque on the arterial wall, which can cause blood flow impairment, or plaque rupture, and ultimately lead to myocardial ischemia. Intravascular ultrasound (IVUS) imaging can provide a detailed characterization of lumen and vessel features, and so plaque burden, in coronary vessels. Prediction of the regions in a vascular segment where plaque burden can either increase (progression) or decrease (regression) following a certain therapy, has remained an elusive major milestone in cardiology. Studies like IBIS-4 showed an association between plaque burden regression and high-intensity rosuvastatin therapy over 13 months. Nevertheless, it has not been possible to predict if a patient would respond in a favorable/adverse fashion to such a treatment. This work aims to (i) Develop a framework that processes lumen and vessel cross-sectional contours and extracts geometric descriptors from baseline and follow-up IVUS pullbacks; and to (ii) Develop, train, and validate a machine learning model based on baseline/follow-up IVUS datasets that predicts future percent of atheroma volume changes in coronary vascular segments using only baseline information, i.e. geometric features and clinical data. This is a post hoc analysis, revisiting the IBIS-4 study. We employed 140 arteries, from 81 patients, for which expert delineation of lumen and vessel contours were available at baseline and 13-month follow-up. Contour data from baseline and follow-up pullbacks were co-registered and then processed to extract several frame-wise features, e.g. areas, plaque burden, eccentricity, etc. Each pullback was divided into regions of interest (ROIs), following different criteria. Frame-wise features were condensed into region-wise markers using tools from statistics, signal processing, and information theory. Finally, a stratified 5-fold cross-validation strategy (20 repetitions) was used to train/validate an XGBoost regression models. A feature selection method before the model training was also applied. When the models were trained/validated on ROI defined by the difference between follow-up and baseline plaque burden, the average accuracy and Mathews correlation coefficient were 0.70 and 0.41 respectively. Using a ROI partition criterion based only on the baseline's plaque burden resulted in averages of 0.60 accuracy and 0.23 Mathews correlation coefficient. An XGBoost model was capable of predicting plaque progression/regression changes in coronary vascular segments of patients treated with rosuvastatin therapy in 13 months. The proposed method, first of its kind, successfully managed to address the problem of stratification of patients at risk of coronary plaque progression, using IVUS images and standard patient clinical data.

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BACKGROUND: Isolate features of the coronary anatomy have been associated with the pathophysiology of atherosclerotic disease. Computational methods have been described to allow precise quantification of the complex three-dimensional (3D) coronary geometry. The present study tested whether quantitative parameters that describe the spatial 3D coronary geometry is associated with the extension and composition of the underlying coronary artery disease (CAD). METHODS: Patients with CAD scheduled for percutaneous intervention were investigated with coronary computed tomography angiography (CCTA), and invasive coronary angiography, and virtual histology intravascular ultrasound (IVUS-VH). For all target vessels, 3D centerlines were extracted from CCTA images and processed to quantify 23 geometric indexes, grouped into 3 main categories as follows: (i) length-based; (ii) curvature-based, torsion-based, and curvature/torsion-combined; (iii) vessel path-based. The geometric variables were compared with IVUS-VH parameters assessing the extent and composition of coronary atherosclerosis. RESULTS: A total of 36 coronary patients (99 vessels) comprised the study population. From the 23 geometric indexes, 18 parameters were significantly (p < 0.05) associated with at least 1 IVUS-VH parameter at a univariate analysis. All three main geometric categories provided parameters significantly related with atherosclerosis variables. The 3D geometric indexes were associated with the degree of atherosclerotic extension, as well as with plaque composition. Geometric features remained significantly associated with all IVUS-VH parameters even after multivariate adjustment for clinical characteristics. CONCLUSIONS: Quantitative 3D vessel morphology emerges as a relevant factor associated with atherosclerosis in patients with established CAD.

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BACKGROUND: There is little information on the performance of the new generation of stents with bioabsorbable polymers in the Latin American population. This registry aimed to further validate the safety and efficacy of the Orsiro bioresorbable-polymer sirolimus-eluting stent (BPSES) in unselected patients undergoing percutaneous coronary intervention (PCI) in Chilean centers. METHODS: We prospectively enrolled patients undergoing PCI with BPSES in 6 Chilean centers. The primary endpoint was defined as the composite of cardiac death, target vessel-related myocardial infarction (MI), and clinically driven target lesion revascularization at 1-year follow-up. RESULTS: From April 2017 to February 2019, 520 patients were enrolled in the registry, more frequently male (74.6%), with a mean age of 62.7 ± 10.8 years and a high prevalence of diabetes (40.2%). The clinical presentation was stable angina in 41.1% (n = 214), acute MI in 52.5% (n = 167 [32.1%] ST-elevation MI and n = 106 [20.4%] non-ST-elevation MI), and unstable angina in 6.3% (n = 33). Of 610 treated lesions, 425 (69.7%) were American College of Cardiology/American Heart Association type B or C lesions. Device and procedural success were achieved in 99.4% and 98.7% of the patients, respectively. The primary endpoint of the study occurred in 4%, primarily driven by cardiac death. CONCLUSIONS: The results of the ROSES multicenter registry indicated good clinical outcomes of BPSES Orsiro in all-comers Latin Americann patients undergoing PCI, despite the high-risk patients and treated lesions.

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BACKGROUND/PURPOSE: Local hemodynamic forces such as endothelial shear stress (ESS) may have an influence on appropriate neointimal healing, vessel remodeling, and struts absorption process following second-generation drug-eluting resorbable magnesium scaffold (RMS, Magmaris, Biotronik AG, Buelach, Switzerland) placement. The aim of this study was to investigate the impact of ESS assessed by optical coherence tomography (OCT)- based computational fluid dynamic (CFD) simulations on absorption process and coronary lumen dimension after Magmaris implantation. METHODS AND RESULTS: A total of 22 patients who were enrolled in the BIOSOLVE-II trial and underwent serial OCT assessment immediately after Magmaris implantation and at 6- and 12-month follow-up were included. We evaluated qualitative OCT findings frame by frame, and CFD simulations were performed to calculate the ESS at 3-dimensional (3D) reconstructed arteries. For quantitative calculation, the average ESS within each 1-mm section was classified into three groups: low (2.5 Pa). A significant difference of percentage remnants of scaffold was observed among the 3 groups at 12-month follow-up (P = 0.001) but not at 6-month follow-up. Low-ESS segment at baseline resulted in a greater lumen change of −1.857 ± 1.902 mm2 at 1 year compared to −1.277 ± 1.562 mm2 in the intermediate-ESS segment (P = 0.017) and − 0.709 ± 1.213 mm2 in the high-ESS segment (P = 0.001). CONCLUSION: After Magmaris implantation, the presence of higher ESS might be associated with slower strut absorption process but less luminal loss. SUMMARY FOR TABLE OF CONTENTS: The authors analyzed 22 patients from the BIOSOLVE-II trial who underwent optical coherence tomography assessment immediately after receiving a Magmaris second-generation drug-eluting resorbable magnesium scaffold. The analysis found that after Magmaris implantation, the presence of higher endothelial shear stress (ESS) might be associated with slower strut absorption process but less luminal loss. This study is the first demonstrating the impact of ESS assessed by OCT on absorption process and coronary lumen dimension after Magmaris implantation.

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The patient reported angina measurement with the Seattle Angina Questionnaire (SAQ) has shown to have prognostic implications and became an endpoint in clinical trials. Our objective was to study physician-reported and SAQ severity with the total coronary atherosclerotic burden as assessed by 4 angiographic scores. We prospectively analyzed data of consecutive patients scheduled for coronary angiography or percutaneous coronary intervention. The Canadian Cardiovascular Society (CCS) angina categories was used as physician-reported angina. SAQ domains were categorized as severe (0 to 24), moderate 25 to 75 and mild angina (>75). All angina assessments were done before coronary angiography. Gensini, Syntax, Friesinger, and Sullivan angiographic scores were used for total atherosclerotic burden quantification: 261 patients were included in the present analysis. The median age was 66.0 (59.0 to 71.8) years, 53.6% were male and 43.7% had diabetes. The median SYNTAX score was 6.0 (0 to 18.0). The worse the symptoms of CCS categories, the more severe was the atherosclerotic burden in all angiographic scores: SYNTAX (p = 0.01); Gensini (p <0.01); Friesinger (p = 0.02) and Sullivan (p = 0.03). Conversely, SAQ domains were not able to discriminate the severity of CAD in any of the scores. The only exception was the severe SAQ quality of life that had worse Gensini score than the mild SAQ quality of life (p = 0.04). In conclusion, CCS angina categories are related to the total atherosclerotic burden in coronary angiography, by all angiographic scores. SAQ domains should be used as a measure of patient functionality and quality of life but not as a measure of CAD severity.

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The characterization of vascular geometry is a fundamental step towards the correct interpretation of coronary artery disease. In this work, we report a comprehensive comparison of the geometry featured by coronary vessels as obtained from coronary computed tomography angiography (CCTA) and the combination of intravascular ultrasound (IVUS) with bi-plane angiography (AX) modalities. We analyzed 34 vessels from 28 patients with coronary disease, which were deferred to CCTA and IVUS procedures. We discuss agreement and discrepancies between several geometric indexes extracted from vascular geometries. Such an analysis allows us to understand to which extent the coronary vascular geometry can be reliable in the interpretation of geometric risk factors, and as a surrogate to characterize coronary artery disease.

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Introduction: Depression and anxiety affect students on an academic and personal level. Compared to the population, college stu-dents seem to show a higher prevalence of both disorders. Objectives: To estimate the prevalence of anxiety and depression, and associated risk factors in a sample of medical students. Methods: Cross-sectional, observational, descriptive and analytical study, through closed surveys; from 04/02/19 to 04/10/19. Sociodemographic variables were collected, GAD-7 and PHQ-9 tests were performed, and probable anxiety and depression were defined with cut-off points ≥10 for each test. Data was analyzed using SPSS V21. Results: 1165 surveys were included. 56% had probable anxiety and 57.8% probable depression. The risk factors for probable anxiety were female sex (p=0.002; OR:1.09;95%CI=1.03-1.16), first year (p=0.002;OR:1.2; 95%CI=1.08-1.35), being a foreigner (p=0.005; OR:1.22; 95%CI=1.08-1.39), living alone (p=0.026; OR:1.14;95%CI=1.02-1.27) and working (p=0.045; OR:1.17;95%-CI=1.02-1.34). There is a probable anxiety and depression comorbidity of 80.7% (p<0.001; OR:3.07;95%CI=2.62-3.59). The risk factors for probable depression were female sex (p<0.001; OR:1.12;95%CI=1.1-1.2), freshmen (p=0.014; OR:1.15;95%CI=1.04-1.29) and being a foreigner (p<0.001; OR:1.27;95%CI=1.13-1.43). Conclusion: Half of the population studied could present anxiety and/or depression. Women, freshmen, foreigners and those who live alone have a higher risk of both diseases.

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Aims: Assessment of minimum lumen areas in intravascular ultrasound (IVUS) pullbacks is time-consuming and demands adequately trained personnel. In this work, we introduce a novel and fully automated pipeline to segment the lumen boundary in IVUS datasets. Methods and results: First, an automated gating is applied to select end-diastolic frames and bypass saw-tooth artefacts. Second, within a machine learning (ML) environment, we automatically segment the lumen boundary using a multi-frame (MF) convolutional neural network (MFCNN). Finally, we use the theory of Gaussian processes (GPs) to regress the final lumen boundary. The dataset consisted of 85 IVUS pullbacks (52 patients). The dataset was partitioned at the pullback-level using 73 pullbacks for training (20 586 frames), 6 pullbacks for validation (1692 frames), and 6 for testing (1692 frames). The degree of overlapping, between the ground truth and ML contours, median (interquartile range, IQR) systematically increased from 0.896 (0.874-0.933) for MF1 to 0.925 (0.911-0.948) for MF11. The median (IQR) of the distance error was also reduced from 3.83 (2.94-4.98)% for MF1 to 3.02 (2.25-3.95)% for MF11-GP. The corresponding median (IQR) in the lumen area error remained between 5.49 (2.50-10.50)% for MF1 and 5.12 (2.15-9.00)% for MF11-GP. The dispersion in the relative distance and area errors consistently decreased as we increased the number of frames, and also when the GP regressor was coupled to the MFCNN output. Conclusion: These results demonstrate that the proposed ML approach is suitable to effectively segment the lumen boundary in IVUS scans, reducing the burden of costly and time-consuming manual delineation.

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AIMS : Second-generation drug-eluting absorbable metal scaffold (DREAMS 2G) is an alternative novel device for treating coronary lesions. However, the relationship between in-scaffold dimensions after implantation of DREAMS 2G and vessel healing and luminal results at follow-up is unknown. The aim of this study is, therefore, to investigate whether the expansion index after implantation of DREAMS 2G as assessed by optical coherence tomography (OCT) impacts late luminal status and healing of the vessel wall. METHODS AND RESULTS : This study comprises of a total 65 out of 123 patients who were enrolled in the BIOSOLVE-II trial. We assessed both qualitative and quantitative OCT findings and the expansion index of DREAMS 2G after implantation frame by frame using OCT. Expansion index was defined as minimum scaffold area/mean reference lumen area. The over-expansion group was also defined with expansion index >1.0. The total number of analyzed frames at post-procedure and 6-month follow-up was 8243 and 8263 frames, respectively. At 6-month follow-up, in-scaffold healing was documented by the reduction of 82% in dissections, 93% in attached intra-luminal mass (ILM), 65% in non-attached ILM, and 76% in jailed side branch. The over-expansion group had significantly greater in-scaffold luminal volume loss (LVL) compared with the non-over-expansion group [over-expansion: 35.0 (18.5-52.1) mm3 vs. non-over-expansion: 21.0 (11.6-37.9) mm3, P = 0.039]. CONCLUSION : Excellent in vivo healing process after implantation of DREAMS 2G was observed at 6 months. We found that higher expansion indices were associated with higher in-scaffold LVL at 6 months assessed by OCT. (AU)

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Background The aim of this study was to compare the 12-month clinical outcomes of patients treated with Magmaris or Orsiro. Second generation drug-eluting absorbable metal scaffold Magmaris (Dreams 2G) has proved to be safe and effective in the BIOSOLVE-II study. Similarly, biodegradable polymer sirolimus-eluting stent, Orsiro has shown notable clinical results even in all-comer populations. Methods Magmaris group patients were taken from the BIOSOLVE-II and BIOSOLVE-III trials, while the patients from Orsiro group were enrolled in BIOFLOW-II trial. The primary outcome was explored using a time-to-event assessment of the unadjusted clinical outcomes for target lesion failure (TLF) at 12 months, followed by a multivariate analysis adjusting for all the significantly different covariates between the groups. Results The study population consisted of 482 patients (521 lesions), 184 patients (189 lesions) in Magmaris group and 298 patients (332 lesions) in Orsiro group. The mean age was 65.5 ±â€¯10.8 and 62.7 ±â€¯10.4 years in Magmaris and Orsiro groups, respectively ( p = 0.005). Magmaris and Orsiro unadjusted TLF rates were 6.0 and 6.4% with no significant difference between the groups ( p = 0.869). In the multivariate analysis, there were no meaningful differences between Magmaris and Orsiro groups. Finally, none of the groups presented device thrombosis cases at 12 months. Conclusion At 12 months there were no significant differences between Magmaris and Orsiro groups neither in the unadjusted assessment nor in the multivariate analysis for target lesion failure. These results should be taken as hypothesis generating and may warrant a head to head comparison on a randomized fashion.

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Non-adherence has been well recognized for years to be a common issue that significantly impacts clinical outcomes and health care costs. Medication adherence is remarkably low even in the controlled environment of clinical trials where it has potentially complex major implications. Collection of non-adherence data diverge markedly among cardiovascular randomized trials and, even where collected, is rarely incorporated in the statistical analysis to test the consistency of the primary endpoint(s). The imprecision introduced by the inconsistent assessment of non-adherence in clinical trials might confound the estimate of the calculated efficacy of the study drug. Hence, clinical trials may not accurately answer the scientific question posed by regulators, who seek an accurate estimate of the true efficacy and safety of treatment, or the question posed by payers, who want a reliable estimate of the effectiveness of treatment in the marketplace after approval. The Non-adherence Academic Research Consortium is a collaboration among leading academic research organizations, representatives from the U.S. Food and Drug Administration and physician-scientists from the USA and Europe. One in-person meeting was held in Madrid, Spain, culminating in a document describing consensus recommendations for reporting, collecting, and analysing adherence endpoints across clinical trials. The adoption of these recommendations will afford robustness and consistency in the comparative safety and effectiveness evaluation of investigational drugs from early development to post-marketing approval studies. These principles may be useful for regulatory assessment, as well as for monitoring local and regional outcomes to guide quality improvement initiatives.(AU)

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Introduction and objective: The edge vascular response (EVR) remains unknown in second generation drugeluting Resorbable Magnesium Scaffold (RMS), such as Magmaris. The aim of the study was to evaluate tissue modifications in the RMS edges over time, assessed by different invasive imaging modalities. Methods: The patients treated with the device were assessed by optical coherence tomography (OCT), grayscale intravascular ultrasound (IVUS), and virtual histology IVUS at baseline and 12 months. The EVR study performed a segment- and frame-level analysis of the 5 mm segments proximal and distal of the actual RMS. Results: The segment-level grayscale IVUS (n=10), virtual histology IVUS (n=10), and OCT (n=18) analysis did not showany significant changes after 12months, except for a fibrous plaque area (FPA) reduction of 0.5mm2 (p=0.017) in the proximal segment compared to baseline. In the frame-level analysis, IVUS evaluation revealed a vessel area decreased 2.80 ± 1.43 mm2 (p = 0.012) and 2.49 ± 1.53 mm2 (p = 0.022) in 2 proximal frames. This was accompanied by plaque area reduction of 0.88 ± 0.70 mm2 (p = 0.048) and a FPA decreased by 0.63 ± 0.48mm2 (p = 0.004) in one proximal frame. In 1 distal frame, there was a dense calcium area reduction of 0.10 ± 0.12 mm2 (p = 0.045), FPA and fibrous fatty plaque increased 0.54 ± 0.53 mm2 (p = 0.023) and 0.17 ± 0.16 mm2 (p = 0.016), respectively. By OCT, there was a lumen area decrease of 0.76 ± 1.51 mm2 (p = 0.045) in a distal frame. Conclusion: At 12 months, Magmaris EVR assessment does not show overall significant changes, except for a fibrous plaque area reduction in the proximal segment. This could be translated as a benign healing process a the edges of the RMS. Summary: The edge vascular response (EVR) remains unknown in second generation drug-eluting absorbable metal scaffolds (RMS), such as Magmaris. Patients treated with the device were assessed by multi invasive imagingmodalities [i.e. optical coherence tomography (OCT), grayscale intravascular ultrasound (IVUS), and virtual histology IVUS] evaluating the tissue changes over timein the segment- and frame-level analysis of the 5mm segments proximal and distal of the actual RMS. As a result, after 12months, Magmaris EVR assessment does not show overall significant changes, except for a fibrous plaque area reduction in the proximal segment, translating a benign healing process at the edges of the RMS.

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Second-generation drug-eluting absorbable metal scaffold (DREAMS 2G) is used for treating coronary lesions. However, the natural history of the jailed side-branch (SB) after DREAMS 2G implantation remains to be elucidated. The aim of this study is to investigate the effect of scaffold struts on jailed SBs as assessed by 3-dimensional (3D) optical coherence tomography (OCT) after implantation of DREAMS 2G. We enrolled the patients who received a DREAMS 2G implantation and where OCT was performed at postprocedure and 12-month follow-up in the BIOSOLVE-II trial. The area of the ostium of jailed SBs and number of compartments divided by scaffold struts were assessed by cut-plane analysis using 3D OCT. A total of 24 patients with 61 jailed SBs were analyzed in this study. The number of compartments was significantly decreased (postprocedure; 1.98 +/- 0.84 vs 12 months; 1.10 +/- 0.30, p <0.001) during the 12 months. Since most of the struts disappeared, the ostium area was increased in 62% of jailed SBs at 12 months, however, not significantly different from postprocedure (postprocedure; 0.74 [0.34 to 1.46] mm(2) vs 12 months; 0.78 [0.41 to 1.68] mm(2), p=0.055). The number of compartments created by scaffold struts and branching angle at postprocedure had no effect on the changes of SB ostium área. DREAMS 2G has a favorable absorption process in the jailed SBs up to 12 months and may be considered as an optional therapy for treating lesions that involve SBs. (AU)

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OBJECTIVES: To evaluate the diagnostic performance of a novel computational algorithm based on three-dimensional intravascular ultrasound (IVUS) imaging in estimating fractional flow reserve (IVUSFR ), compared to gold-standard invasive measurements (FFRINVAS ). BACKGROUND: IVUS provides accurate anatomical evaluation of the lumen and vessel wall and has been validated as a useful tool to guide percutaneous coronary intervention. However, IVUS poorly represents the functional status (i.e., flow-related information) of the imaged vessel. METHODS: Patients with known or suspected stable coronary disease scheduled for elective cardiac catheterization underwent FFRINVAS measurement and IVUS imaging in the same procedure to evaluate intermediate lesions. A processing methodology was applied on IVUS to generate a computational mesh condensing the geometric characteristics of the vessel. Computation of IVUSFR was obtained from patient-level morphological definition of arterial districts and from territory-specific boundary conditions. FFRINVAS measurements were dichotomized at the 0.80 threshold to define hemodynamically significant lesions. RESULTS: A total of 24 patients with 34 vessels were analyzed. IVUSFR significantly correlated (r = 0.79; P < 0.001) and showed good agreement with FFRINVAS , with a mean difference of -0.008 ± 0.067 (P = 0.47). IVUSFR presented an overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 91%, 89%, 92%, 80%, and 96%, respectively, to detect significant stenosis. CONCLUSION: The computational processing of IVUSFR is a new method that allows the evaluation of the functional significance of coronary stenosis in an accurate way, enriching the anatomical information of grayscale IVUS.

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