[Coronary CT Angiography-Based Mechanomics Predicts Atherosclerotic Plaque Formation in Regions Proximal to Myocardial Bridging].
Year: 2024
Type: other
Abstract: Objective: To assess with machine learning the predictive value of mechanomics derived from coronary CT angiography (CCTA) for atherosclerotic plaque formation in regions proximal to myocardial bridging (MB) in the left anterior descending coronary artery (LAD). Methods: This retrospective study included a cohort of patients with MB in LAD and no atherosclerotic plaque formation in LAD as confirmed by two CCTA conducted between January 2007 and April 2021 at our hospital. The interval between the two CCTA examinations was more than 3 months. The primary endpoint was the formation of atherosclerotic plaques in regions proximal to the myocardial bridging. Patient demographic characteristics and clinical risk factors were documented. Then, the patients were matched by age and sex in a 1-to-1 ratio and divided into two groups, those with plaque formation and those without plaque formation. Computational fluid dynamics analysis was performed based on CCTA. Key anatomical parameters of MB, including location, length, depth, and systolic compression index, were meticulously measured on the CCTA images. Mechanomic data were extracted from the region proximal to the MB. A multivariate Cox regression analysis was performed to identify significant features. A random forest algorithm was used to select mechanomic features for subsequent modeling and to assign scores for each patient's mechanomic features. The log-rank test and Kaplan-Meier curves were used to investigate the mechanomic model's predictive performance concerning plaque formation. Additionally, the operator characteristic curves were applied to evaluate how well the model could predict plaque formation across various myocardial bridge subgroups. Results: <0.001). The area under the curve (AUC) for plaque formation, as predicted by the model, was 0.88 (95% CI: 0.82-0.95) for the entire population, 0.89 (95% CI: 0.82-0.96) for the training set, 0.86 (95% CI: 0.74-0.99) for the validation set, 0.92 (95% CI: 0.86-0.97) for the superficial MB group, 0.86 (95% CI: 0.74-0.98) for the long MB group, and 0.91 (95% CI: 0.83-0.98) for the short MB group. Conclusion: The mechanomic assessment holds substantial potential as a predictive tool for atherosclerotic plaque formation in regions proximal to MB in LAD.
Source: PubMed
DOI: 10.12182/20241160502
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4407908334