ArticleScientific reports2018
Defining Coronary Flow Patterns: Comprehensive Automation of Transthoracic Doppler Coronary Blood Flow.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 13 citations in OpenAlex.
- Velocimetry based on multiphase CCTA images for reliable coronary flow velocity quantification across stenosis severities and ischemia detection.Medical physics · 2026Article
- Artificial Intelligence in Cardiovascular Medicine: A Giant Step in Personalized Medicine?Journal of personalized medicine · 2026Review
- Systolic-dominant coronary flow in rats and mice: Challenging the diastolic paradigm across conscious and anaesthetized states.Experimental physiology · 2026Article
- Impaired Coronary Microcirculation and Myocardial Systolic Function: A Narrative Review on Non-Invasive Assessment in Cardiovascular Diseases.Life (Basel, Switzerland) · 2025Review
- Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion.Biomechanics and modeling in mechanobiology · 2024Article
- Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins.NPJ digital medicine · 2024Article
- Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research.American journal of physiology. Heart and circulatory physiology · 2024Review
- Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps.International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) · 2023Article
- Development of artificial intelligence tools for invasive Doppler-based coronary microvascular assessment.European heart journal. Digital health · 2023Article
- Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data.SN computer science · 2023Article
- Prospective Assessment of Coronary Artery Flows Before and After Cardiopulmonary Bypass in Children With a Spectrum of Congenital Heart Disease.CJC pediatric and congenital heart disease · 2022Article
- Improvement of automated analysis of coronary Doppler echocardiograms.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The coronary microcirculation (CM) plays a critical role in the regulation of blood flow and nutrient exchange to support the viability of the heart. In many disease states, the CM becomes structurally and functionally impaired, and transthoracic Doppler echocardiography can be used as a non-invasive surrogate to assess CM disease. Analysis of Doppler echocardiography is prone to user bias and can be laborious, especially if additional parameters are collected. We hypothesized that we could develop a MATLAB algorithm to automatically analyze clinically-relevant and non-traditional parameters from murine PW Doppler coronary flow patterns that would reduce intra- and inter-operator bias, and analysis time. Our results show a significant reduction in intra- and inter-observer variability as well as a 30 fold decrease in analysis time with the automated program vs. manual analysis. Finally, we demonstrated good agreement between automated and manual analysis for clinically-relevant parameters under baseline and hyperemic conditions. Resulting coronary flow velocity reserve calculations were also found to be in good agreement. We present a MATLAB algorithm that is user friendly and robust in defining and measuring Doppler coronary flow pattern parameters for more efficient and potentially more insightful analysis assessed via Doppler echocardiography.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.