Publications by authors named "Kranthi K Kolli"

Article Synopsis
  • The study examined the use of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) during percutaneous coronary interventions (PCI) using Medicare claims data from 2015 to 2020.
  • Results indicated that IVUS and OCT were infrequently used in PCIs—92% used angiography alone, while IVUS and OCT were used in 7.5% and 0.3% of cases, respectively.
  • Compared to angiography alone, both IVUS and OCT were associated with lower rates of major adverse cardiovascular events over three years, with OCT showing a more significant reduction in risks.
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Objective: To develop a novel method for evaluating coronary artery ischemia using a combination of non-invasive coronary CT angiograms (CCTA) and 3D printing (FFR).

Methods: Twenty eight patients with varying degrees of coronary artery disease who underwent non-invasive CCTA scans and invasive fractional flow reserve (FFR) of their epicardial coronary arteries were included in this study. Coronary arteries were segmented and reconstructed from CCTA scans using Mimics (Materialize).

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Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP.

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Background: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to examine the prognostic ability of a ML-based prediction algorithm utilizing routine health checkup data to predict all-cause mortality (ACM) compared to established risk prediction approaches.

Methods: A total 86155 patients with seventy available parameters (35 clinical, 32 laboratory, and 3 coronary artery calcium score [CACS] parameters) were analyzed.

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Background The ability to accurately predict the occurrence of in-hospital death after percutaneous coronary intervention is important for clinical decision-making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System in order to elucidate the determinants of in-hospital mortality in patients undergoing percutaneous coronary intervention across New York State. Methods and Results We examined 479 804 patients undergoing percutaneous coronary intervention between 2004 and 2012, utilizing traditional and advanced machine learning algorithms to determine the most significant predictors of in-hospital mortality.

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Coronary bypass grafting (CABG) is a surgical procedure for anastomosing small grafts to the coronary vessels. The bypass graft bridges the occluded or diseased coronary artery, allowing sufficient blood flow to deliver oxygen and nutrients to the heart muscles. Patient-specific (PS) anatomy obtained from coronary computed tomography angiography (CCTA) was used to generate a 3D aorto-coronary model (pre-surgery).

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Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models.

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Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular medicine. Owing to the growing body of literature validating both the diagnostic performance as well as the prognostic implications of anatomic and physiologic findings, coronary computed tomography angiography (CCTA) is now a well-established non-invasive modality for the assessment of cardiovascular disease. ML has been increasingly utilized to optimize performance as well as extract data from CCTA as well as non-contrast enhanced cardiac CT scans.

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Introduction: Machine learning (ML) is a field in computer science that demonstrated to effectively integrate clinical and imaging data for the creation of prognostic scores. The current study investigated whether a ML score, incorporating only the 16 segment coronary tree information derived from coronary computed tomography angiography (CCTA), provides enhanced risk stratification compared with current CCTA based risk scores.

Methods: From the multi-center CONFIRM registry, patients were included with complete CCTA risk score information and ≥3 year follow-up for myocardial infarction and death (primary endpoint).

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Background: In this study, lesion flow coefficient (LFC: ratio of % area stenosis [%AS] to the square root of the ratio of the pressure drop across the stenosis to the dynamic pressure in the throat region), that combines both the anatomical (%AS) and functional measurements (pressure and flow), was assessed for application in a clinical setting.

Methods And Results: Pressure, flow, and anatomical values were obtained from patients in 251 vessels from two different centers. Fractional flow reserve (FFR), Coronary flow reserve (CFR), hyperemic stenosis resistance index (HSR) and hyperemic microvascular index (HMR) were calculated.

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Background: Wall shear stress (WSS) is an established predictor of coronary atherosclerosis progression. Prior studies have reported that high WSS has been associated with high-risk atherosclerotic plaque characteristics (APCs). WSS and APCs are quantifiable by coronary computed tomography angiography, but the relationship of coronary lesion ischemia-evaluated by fractional flow reserve-to WSS and APCs has not been examined.

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Background: The aim of this study was to investigate the impact of varying hemodynamic conditions on fractional flow reserve (ratio of pressure distal [Pd] and proximal [Pa] to stenosis under hyperemia) in an in vitro setting. Failure to achieve maximal hyperemia and the choice of hyperemic agents may have differential effects on coronary hemodynamics and, consequently, on the determination of fractional flow reserve.

Methods And Results: An in vitro flow system was developed to experimentally model the physiological coronary circulation as flow-dependent stenosis resistance in series with variable downstream resistance.

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Objectives And Background: Functional assessment of intermediate coronary stenosis during cardiac catheterization is conducted using diagnostic parameters like fractional flow reserve (FFR), coronary flow reserve (CFR), hyperemic stenosis resistance index (HSR), and hyperemic microvascular resistance (HMR). CDP (ratio of pressure drop across a stenosis to distal dynamic pressure), a nondimensional index derived from fundamental fluid dynamic principles, based on a combination of intracoronary pressure, and flow measurements may improve the functional assessment of coronary lesion severity.

Methods: Patient-level data pertaining to 350 intracoronary pressure and flow measurements across coronary stenoses was assessed to evaluate CFR, FFR, HSR, HMR, and CDP.

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Background: ECG-gated rest-stress cardiac PET can lead to simultaneous quantification of both left ventricular ejection fraction and flow impairment. In this study, our aim was to assess the benefit of rest and stress PET ejection fraction (EF) (EFp) in relation to single-photon emission computed tomography (SPECT) EF (EFs) and echocardiography EF (EFe). To this effect, the EFp was compared with EFs and EFe.

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Invasive diagnosis of coronary artery disease utilizes either anatomical or functional measurements. In this study, we tested a futuristic parameter, lesion flow coefficient (LFC, defined as the ratio of percent coronary area stenosis (%AS) to the square root of the ratio of the pressure drop across the stenosis to the dynamic pressure in the throat region), that combines both the anatomical (%AS) and functional measurements (pressure and flow) for application in a clinical setting. In 51 vessels, simultaneous pressure and flow readings were obtained using a 0.

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Background: Cardiac positron emission tomography (PET) can lead to flow impairment quantification using PET coronary flow reserve (CFRp: ratio of stress flow to rest flow) and is superior to the current standard, single-photon emission computed tomography. In this study, our first aim was to assess the benefit of CFRp in place of invasive CFR (CFRi) by comparing the correlations of each of the indices with combined pressure and flow index CDP, and combined functional (pressure-flow) and anatomical (%area stenosis, %AS) index, LFC. The second aim was to test the correlation between CFRp and CFRi.

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The assessment of functional coronary lesion severity using intracoronary hemodynamic parameters like the pressure-derived fractional flow reserve and the flow-derived coronary flow reserve are known to rely critically on the establishment of maximal hyperemia. We evaluated a hyperemia-free index, basal pressure drop coefficient (bCDP), that combines pressure and velocity for simultaneous assessment of the status of both epicardial and microvascular circulations. In 23 pigs, simultaneous measurements of distal coronary arterial pressure and flow were performed using a dual-sensor tipped guidewire in the settings of both normal and abnormal microcirculation with the presence of epicardial lesions of area stenosis (AS) < 50% and AS > 50%.

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Objectives And Background: Functional assessment of coronary lesion severity during cardiac catheterization is conducted using diagnostic parameters like fractional flow reserve (FFR; pressure derived) and coronary flow reserve (CFR; flow derived). However, the complex hemodynamics of stenosis might not be sufficiently explained by either pressure or flow alone, particularly in the case of intermediate stenosis. CDP (ratio of pressure drop across a stenosis to distal dynamic pressure), a non-dimensional index derived from fundamental fluid dynamic principles based on a combination of intracoronary pressure and flow, may improve the functional assessment of coronary lesion severity.

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The study of hemodynamics in an animal model simulating coronary stenosis has been limited due to the lack of a safe, accurate and reliable technique for creating an artificial stenosis. Creating artificial stenosis using occluders in an open-chest procedure has often caused myocardial infarction (MI) or severe injury to the vessel resulting in high failure rates. To minimize these issues, closed-chest procedures with internal balloon obstruction are often used to create an artificial stenosis.

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Objectives And Background: Myocardial fractional flow reserve (FFR) in conjunction with coronary flow reserve (CFR) is used to evaluate the hemodynamic severity of coronary lesions. However, discordant results between FFR and CFR have been observed in intermediate coronary lesions. A functional parameter, pressure drop coefficient (CDP; ratio of pressure drop to distal dynamic pressure), was assessed using intracoronary pressure drop (dp) and average peak velocity (APV).

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In this study, coronary diagnostic parameters, pressure drop coefficient (CDP: ratio of trans-stenotic pressure drop to distal dynamic pressure), and lesion flow coefficient (LFC: ratio of % area stenosis (%AS) to the CDP at throat region), were evaluated to distinguish levels of %AS under varying contractility conditions, in the presence of microvascular disease (MVD). In 10 pigs, %AS and MVD were created using angioplasty balloons and 90-μm microspheres, respectively. Simultaneous measurements of pressure drop, left ventricular pressure (p), and velocity were obtained.

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Objectives And Background: Decisions based on invasive functional diagnostic measurements are often made in the setting of fluctuating hemodynamic variables that may alter resting or hyperemic measurements. The purpose of this investigation is to analyze the effect of myocardial contractility (CY) on invasive functional parameters. We hypothesize that the pressure drop coefficient (CDPe; ratio of pressure drop to distal dynamic pressure) and fractional flow reserve (FFR; ratio of average pressures distal and proximal to a stenosis) are not affected by fluctuations in CY and can distinguish between different severities of epicardial stenosis.

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Background: Guidewire (GW) size and stenosis dimensions are the two major factors affecting the translesional pressure drop. Studying the combined effect of these parameters on the mean pressure drop (Δp) across the stenosis is of high practical importance.

Methods: In this study, time averaged mass and momentum conservation equations are solved analytically to obtain pressure drop-flow, Δp-Q, curves for three different percentage area blockages corresponding to moderate (64%), intermediate (80%), and severe (90%) stenoses.

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A limitation in the use of invasive coronary diagnostic indexes is that fluctuations in hemodynamic factors such as heart rate (HR), blood pressure, and contractility may alter resting or hyperemic flow measurements and may introduce uncertainties in the interpretation of these indexes. In this study, we focused on the effect of fluctuations in HR and area stenosis (AS) on diagnostic indexes. We hypothesized that the pressure drop coefficient (CDP(e), ratio of transstenotic pressure drop and distal dynamic pressure), lesion flow coefficient (LFC, square root of ratio of limiting value CDP and CDP at site of stenosis) derived from fluid dynamics principles, and fractional flow reserve (FFR, ratio of average distal and proximal pressures) are independent of HR and can significantly differentiate between the severity of stenosis.

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