Adaptation of contrast injection protocol to tube potential for cardiovascular CT

More sustainable use of iodinated contrast media - Why?

OBJECTIVES

Based on a narrative review of the literature to 1) assess the need for and 2) report methods to help deliver a sustainable approach to iodinated contrast media (ICM) administration.

KEY FINDINGS

Acute ICM shortages have been noted in the literature. As demand for contrast-enhanced imaging continues to increase and access to raw materials becomes more limited, such events may increase. Evidence from the literature has documented a range of iodinated contrast reduction strategies. These include individualised contrast-media dosing, multi-dose bulk ICM vials, switching to alternative modalities or the increased use of non-contrast examinations. The optimisation of imaging parameters, the use of saline chasers, and alternative contrast agents should be further considered. Given the rising concerns regarding the presence and effects of ICMs in waste and drinking water, further consideration of strategies for managing waste and excreted ICMs are starting to emerge.

CONCLUSIONS

Sustainable ICM practices are needed to help avoid supply shortages and to help protect our environment. Such practices must be led and supported locally, nationally, and internationally. Sustainable ICM practices must be reflected within professional Standards of Proficiencies and be adopted by all members of the multidisciplinary team.

IMPLICATIONS FOR PRACTICE

Changes to working practices surrounding the sustainable use of ICMs will likely become commonplace. New methods to ensure optimised ICM dosage with minimal wastage will be more heavily featured in departmental practices. Correct disposal of waste and excreted ICMs will also form part of future changes to practice.

Effect of Body Mass Index in Coronary CT Angiography Performed on a 256-Slice Multi-Detector CT Scanner

We aimed to investigate the effect of a patient’s body mass index (BMI) on radiation dose and image quality in prospectively ECG-triggered coronary CT angiography (CCTA) performed on a 256-slice multi-detector CT scanner. In total, 87 consecutive patients receiving CCTA examinations acquired with tube current modulation (TCM) and iterative reconstruction (IR) were enrolled in this study. The dose report recorded from the CT scanner console was used to derive the effective dose for patients. Subjective image quality scoring and objective noise measurements were conducted to quantify the impact of BMI on the image quality of CCTA. Because of the TCM technique, we expected tube current and radiation dose to increase as BMI increased. However, using TCM did not always guarantee sufficient radiation exposure to achieve consistent image quality for overweight or obese patients since the maximum X-ray tube output in milliamperes and kilovoltage peak was reached. The impact of photon starvation noise on image quality was not significant until BMI ≥ 27 kg/m2; this result could be due to IR’s noise reduction capability. Our results also suggest that using TCM with a noise index of 25 HU can reduce radiation dose without compromising image quality compared to images obtained based on the manufacturer’s default settings.

A Metric for Quantification of Iodine Contrast Enhancement (Q-ICE) in Computed Tomography

BACKGROUND

Poor contrast enhancement is related to issues with examination execution, contrast prescription, computed tomography (CT) protocols, and patient conditions. Currently, our community has no metric to monitor true enhancement on routine single-phase examinations because this requires knowledge of both pre- and postcontrast CT number.

PURPOSE

We propose an automatable solution to quantifying contrast enhancement without requiring a dedicated noncontrast series.

METHODS

The difference in CT number between a target region in an enhanced and unenhanced image defines the metric "quantification of iodine contrast enhancement" (Q-ICE). Quantification of iodine contrast enhancement uses the noncontrast bolus tracking baseline image from routine abdominal examinations, which mitigates the need for a dedicated noncontrast series. We applied this method retrospectively to 312 patient livers from 2 sites between 2017 and 2020. Each site used a weight-based contrast injection protocol for weights 60 to 113 kg and a constant volume less than 60 kg and greater than 113 kg. Hypothesis testing was performed to compare Q-ICE between sites and detect Q-ICE dependence on weight and kilovoltage (kV).

RESULTS

Mean Q-ICE differed between sites (P = 0.004) by 4.96 Hounsfield unit with 95% confidence interval (1.63-8.28), albeit this difference was roughly 2 times smaller than the SD in Q-ICE across patients at a single site. For patients between 60 and 113 kg, we did not observe evidence of Q-ICE varying with patient weight (P = 0.920 and 0.064 for 120 and 140 kV, respectively). The Q-ICE did vary with patient weight for patients less than 60 kg (P = 0.003) and greater than 113 kg (P = 0.04). We observed a roughly 10 Hounsfield unit reduction in Q-ICE liver for patients scanned with 140 versus 120 kV. We observed several underenhancing examinations with an arterial phase appearance motivating our CT protocol optimization team to consider increasing the delay for slowly enhancing patients.

CONCLUSIONS

A quality metric for quantifying CT contrast enhancement was developed and suggested tangible opportunities for quality improvement and potential financial savings.