Time-aligned segmental strain as a diagnostic marker for obstructive coronary artery disease in patients with chronic chest pain

Background Myocardial strain curves provide valuable insights into coronary artery disease (CAD) beyond conventional peak strain measurements. This study aimed to evaluate the diagnostic utility of time-aligned segmental strain and strain rate (S/SR) curves to identify obstructive CAD in chest pain patients undergoing coronary computed tomography angiography (CCTA). Methods A total of 510 chest pain patients referred for CCTA and 88 post-revascularized MI patients were included. Transthoracic echocardiography (TTE) was performed, and segmental strain curves were time-aligned using aortic valve closure (AVC) and cardiac cycle length as reference points. Average S/SR curves were generated for 18 myocardial segments, establishing reference curves from a group of 314 chronic chest-pain patients without CAD. Deviations were defined based on thresholds of peak S/SR or average S/SR curve deviation over systole and the first half of diastole. Results Significant differences were observed between groups, particularly between the revascularized MI, CABG, or 3-vessel CAD groups compared to the No-CAD group (p<0.05). ROC curve analysis demonstrated excellent diagnostic performance for CABG patients (AUC = 0.933), while the detection rate for PCI was limited (AUC < 0.7). Global longitudinal strain rate in early diastole (GLSR E) and segmental peak SR E showed the highest diagnostic accuracy. These findings confirm that time-aligned strain analysis improves the detection of significant CAD but remains limited for identifying patients with mild disease. Conclusion Time-aligned segmental strain analysis improved detection of regional dysfunction but could not distinguish single-vessel from non-obstructive CAD, while strain rate in early diastole demonstrated excellent accuracy for identifying high-grade disease requiring CABG. Pathological strain patterns became significant only in advanced CAD, indicating that resting strain analysis has clinical utility primarily for identifying advanced coronary disease.