Four-dimensional quantitative coronary artery motion analysis : a novel method for culprit lesion prediction

Background: This study aimed to determine if measuring four-dimensional (4D) quantitative coronary artery motion (4D-QCAM) and change in tortuosity (ΔT) on invasive biplane coronary angiogram is predictive of the location of culprit lesions responsible for myocardial infarctions. Invasive coronary angiograms have no current clinical application for the prediction of future coronary events. Previous studies have shown promise in demonstrating the effects of coronary artery motion on plaque formation and location, but this has yet to fully translate into a directed diagnostic method. Methods: Both 4D-QCAM and ΔT were calculated with CAAS QCA4D prototype software (Pie Medical Imaging, the Netherlands) for sections of the culprit coronary artery using biplane coronary angiograms of 14 patients who underwent percutaneous coronary intervention for myocardial infarction. Prediction of the artery section containing the culprit lesion was performed using one sample t-testing, generalised linear latent and mixed statistical modelling with grouping by patient, and logistic regression modelling. Results: The 4D-QCAM was a significant predictor of the location of culprit lesions (p = 0.047), and ΔT was not (p = 0.49). Conclusion: The 4D-QCAM may have a role in predicting the location of culprit lesions, and may allow for targeted local therapy to prevent future events.