Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine.
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ABSTRACT:
SUBMITTER: Ganzer PD
PROVIDER: S-EPMC8730601 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionThe electrocardiogram (ECG) is a valuable tool for the diagnosis of myocardial ischemia as it presents distinctive ischemic patterns. Deep learning methods such as convolutional neural networks (CNN) are employed to extract data-derived features and to recognize natural patterns. Hence, CNN enable an unbiased view on well-known clinical phenomenon, e.g., myocardial ischemia. This study tested a novel, hypothesis-generating approach using pre-trained CNN to determine the optimal ischemic parameter as obtained from the highly susceptible intracoronary ECG (icECG).MethodThis was a retrospective observational study in 228 patients with chronic coronary syndrome. Each patient had participated in clinical trials with icECG recording and ST-segment shift measurement at the beginning (i.e., non-ischemic) and the end (i.e., ischemic) of a one-minute proximal coronary artery balloon occlusion establishing the reference. Using these data (893 icECGs in total), two pre-trained, open-access CNN (GoogLeNet/ResNet101) were trained to recognize ischemia. The best performing CNN during training were compared with the icECG ST-segment shift for diagnostic accuracy in the detection of artificially induced myocardial ischemia.ResultsUsing coronary patency or occlusion as reference for absent or present myocardial ischemia, receiver-operating-characteristics (ROC)-analysis of manually obtained icECG ST-segment shift (mV) showed an area under the ROC-curve (AUC) of 0.903±0.043 (p<0.0001, sensitivity 80%, specificity 92% at a cut-off of 0.279mV). The best performing CNN showed an AUC of 0.924 (sensitivity 93%, specificity 92%). DeLong-Test of the ROC-curves showed no significant difference between the AUCs. The underlying morphology responsible for the network prediction differed between the trained networks but was focused on the ST-segment and the T-wave for myocardial ischemia detection.ConclusionsWhen tested in an experimental setting with artificially induced coronary artery occlusion, quantitative icECG ST-segment shift and CNN using pathophysiologic prediction criteria detect myocardial ischemia with similarly high accuracy.
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Project description:UnlabelledAbsolute quantitation of myocardial blood flow (MBF) by PET is an established method of analyzing coronary artery disease (CAD) but subject to the various shortcomings of available radiotracers. Flurpiridaz F 18 is a novel PET radiotracer that exhibits properties of an ideal tracer.MethodsA new absolute perfusion quantitation method with flurpiridaz was developed, taking advantage of the early kinetics and high first-pass extraction by the myocardium of this radiotracer, and the first-in-human measurements of MBF performed in 7 healthy subjects and 8 patients with documented CAD. PET images with time-activity curves were acquired at rest and during adenosine stress.ResultsIn healthy subjects, regional MBF between coronary artery territories did not differ significantly, leading to a mean global MBF of 0.73 mL/min/g at rest and 2.53 mL/min/g during stress, with a mean global myocardial flow reserve (MFR) of 3.70. CAD vascular territories with <50% stenosis demonstrated a mean MBF of 0.73 at rest and 2.02 during stress, leading to a mean MFR of 2.97. CAD vascular territories with ≥50% stenosis exhibited a mean MBF of 0.86 at rest and 1.43 during stress, leading to a mean MFR of 1.86. Differences in stress MBF and MFR between normal and CAD territories, as well as between <50% and ≥50% stenosis vascular territories, were significant (P < 0.01).ConclusionAbsolute quantitation of MBF in humans with the novel PET radiotracer flurpiridaz is feasible over a wide range of cardiac flow in the presence or absence of stress-inducible myocardial ischemia. The significant decrease in stress MBF and ensuing MFR in CAD territories allows a clear distinction between vascular territories exhibiting stress-inducible myocardial ischemia and those with normal perfusion.
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