AIMC Topic: Fractional Flow Reserve, Myocardial

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Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging Apr 1, 2020
AIMS: Although deep-learning algorithms have been used to compute fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA), no study has achieved 'fully automated' (i.e. free from human input) FFR calculation using deep-lear...
Sensitivity and Specificity Deep Learning Retrospective Studies Tomography, X-Ray Computed Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Predictive Value of Tests Coronary Angiography Humans
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Virtual fractional flow reserve and virtual coronary stent guided percutaneous coronary intervention.

Cardiology journal Jan 1, 2020
Aged Male Treatment Outcome Humans Machine Learning Stents Coronary Stenosis Cineangiography Fractional Flow Reserve, Myocardial Radiographic Image Interpretation, Computer-Assisted Percutaneous Coronary Intervention Predictive Value of Tests Coronary Angiography
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Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Journal of the American Heart Association Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Angiography Coronary Vessels Middle Aged Severity of Illness Index ROC Curve Imaging, Three-Dimensional Female Male Algorithms Retrospective Studies Humans Machine Learning
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CT morphological index provides incremental value to machine learning based CT-FFR for predicting hemodynamically significant coronary stenosis.

International journal of cardiology Aug 15, 2018
AIMS: To study the diagnostic performance of the ratio of Duke jeopardy score (DJS) to the minimal lumen diameter (MLD) at coronary computed tomographic angiography (CCTA) and machine learning based CT-FFR for differentiating functionally significant...
Humans Machine Learning Retrospective Studies Female Computed Tomography Angiography Male Single-Blind Method Coronary Stenosis Predictive Value of Tests Fractional Flow Reserve, Myocardial Multidetector Computed Tomography
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Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Circulation. Cardiovascular imaging Jun 1, 2018
BACKGROUND: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necess...
United States Coronary Stenosis Europe Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Fractional Flow Reserve, Myocardial Asia Aged Severity of Illness Index Predictive Value of Tests Computed Tomography Angiography Coronary Artery Disease Male Coronary Angiography Deep Learning Coronary Vessels Retrospective Studies Humans Middle Aged Prospective Studies Female
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