UC Irvine

Objectives

The objective was to retrospectively develop a protocol in swine for optimal contrast media timing in coronary CT angiography (CCTA).

Methods

Several dynamic acquisitions were performed in 28 swine (55 ± 24 kg) with cardiac outputs between 1.5 and 5.5 L/min, for 80 total acquisitions. The contrast was injected (1mL/kg, 5mL/s, Isovue 370), followed by dynamic scanning of the entire aortic enhancement curve, from which the true peak time and aortic and coronary enhancements were recorded as the reference standard. Each dataset was then used to simulate two different CCTA protocols-a new optimal protocol and a standard clinical protocol. For the optimal protocol, the CCTA was acquired after bolus tracking-based trigging using a variable time delay of one-half the contrast injection time interval plus 1.5 s. For the standard protocol, the CCTA was acquired after bolus tracking-based triggering using a fixed time delay of 5 s. For both protocols, the CCTA time, aortic enhancement, coronary enhancement, and coronary contrast-to-noise ratio (CNR) were quantitatively compared to the reference standard measurements.

Results

For the optimal protocol, the angiogram was acquired within -0.15 ± 0.75 s of the true peak time, for a mean coronary CNR within 7% of the peak coronary CNR. Conversely, for the standard CCTA protocol, the angiogram was acquired within -1.82 ± 1.71 s of the true peak time, for a mean coronary CNR that was 23% lower than the peak coronary CNR.

Conclusions

The optimal CCTA protocol improves contrast media timing and coronary CNR by acquiring the angiogram at the true aortic root peak time.

Key points

• This study in swine retrospectively developed the mathematical basis of an improved approach for optimal contrast media timing in CCTA. • By combining dynamic bolus tracking with a simple contrast injection timing relation, CCTA can be acquired at the peak of the aortic root enhancement. • CCTA acquisition at the peak of the aortic root enhancement should maximize the coronary enhancement and CNR, potentially improving the accuracy of CT-based assessment of coronary artery disease.