Reply

We are grateful to the authors for their interest in our recently published case report and for their thoughtful commentary on the intravascular ultrasound (IVUS) methodology used in our evaluation of a 17-year-old patient with an anomalous aortic origin of the right coronary artery.¹ Their detailed discussion highlights important considerations in IVUS imaging for this unique cardiovascular anomaly. We were able to understand that, as pointed out by the authors, stationary IVUS imaging at the ostium or intramural segment may be subject to artifacts because of catheter-induced anatomic shifts during the cardiac cycle, potentially creating a misleading appearance of pulsatile lumen deformation. This represents a noteworthy technical consideration that clinicians and researchers should keep in mind when interpreting systolic and diastolic changes in the coronary lumen of anomalous aortic origin of a coronary artery (AAOCA). In our case, we focused on the use of IVUS combined with invasive pressure measurements under rest and stress conditions to better understand the functional relevance of the intramural course.

We also appreciate the authors' introduction of automated intravascular ultrasound of coronary artery anomalies, an open-source tool that enables automated segmentation and alignment of IVUS frames. These techniques may offer valuable opportunities to improve the accuracy of dynamic imaging in AAOCA and other coronary conditions. We expect that automated intravascular ultrasound of coronary artery anomalies has the potential to assist in identifying the true culprit lesions in AAOCA, accurately evaluating the length of the intramural segment, and determining whether the ostium is compressed. One technical concern with the pullback-based approach is the difficulty in ensuring that exactly the same cross-sectional plane is evaluated across different cardiac cycles, even when the pullback is performed at a very slow and constant speed. Nonetheless, this concern could potentially be addressed by incorporating electrocardiogram synchronization or leveraging advanced technologies such as artificial intelligence to improve temporal and spatial consistency. Although this is a relatively niche field, we fully support the advancement of standardized and automated approaches in this area, because the assessment of disease severity in AAOCA is often challenging, and many cases present difficulties in determining an appropriate treatment strategy. Once again, we thank the authors for their expert insights. Their comments contribute meaningfully to the evolving discussion on optimal imaging strategies in the diagnosis and management of AAOCA, and we hope that this exchange will help promote best practices in the field.