Computed tomography angiography (CTA) of anomalous aortic origin of a coronary artery (AAOCA): Which measurements are accurate and reliable?

BACKGROUND

The variation and accuracy of computed tomography angiography (CTA) features of anomalous aortic origin of a coronary artery (AAOCA) have not been completely characterized. We evaluated anomalous right (AAORCA) and left (AAOLCA) coronary arteries by CTA, with an emphasis on reproducibility, comparison with surgical measurements, and effect of nitroglycerin.

METHODS

CTAs were interpreted for location of coronary origin & exit from the aorta, course, and dominance; minor & major diameters of the proximal & distal coronaries; shape of orifice; and intramural length. Relationships between vessel measurements, body surface area (BSA), and nitroglycerin use were evaluated. Comparisons between CTA and surgical measurements included intramural length, surgical probe size pre-intervention vs. CTA proximal AAOCA diameter, and surgical probe size post-intervention vs. CTA distal AAOCA diameter.

RESULTS

Of 104 patients [81 (78%) AAORCA], all but 1 were intramural. Compared to AAOLCA, AAORCA patients were more likely to have a high origin (91% vs. 31%, p ​< ​0.01), and slit-like orifice (58% vs. 26%, p ​< ​0.01). When CTAs with nitroglycerin were compared to those without, no difference in proximal AAOCA dimensions was identified; however distal AAOCA and normal-origin coronary dimensions were larger in scans with nitroglycerin. Aside from slit-like orifice, reliability of coronary CTA measurements, including proximal AAOCA minor diameter and intramural length, was moderate to good between readers. In a subgroup of 54 patients, proximal AAOCA minor diameter and intramural length had good agreement and correlation with surgery.

CONCLUSION

Proximal AAOCA dimensions and intramural length are reproducible variables. The lack of difference in proximal AAOCA dimensions with nitroglycerin may reflect abnormal vessel mechanics. Multicenter studies are an important next step in understanding the generalizability of our findings.