Patient-tailored Contrast Delivery Protocols for Computed Tomography Coronary Angiography: Lower Contrast Dose and Better Image Quality

CTCA in children with severe heterozygous familial hypercholesterolaemia: Screening for subclinical atherosclerosis

Familial hypercholesterolemia (FH) is one of the most common genetically inherited disorders in the world. Children with severe heterozygous FH (HeFH), i.e. untreated low-density lipoprotein cholesterol (LDL-C) levels above the 90th percentile for age and sex among FH mutation carriers, can have LDL-C levels that overlap levels of children with homozygous FH (HoFH), but treatment regimen and cardiovascular follow-up to prevent cardiovascular disease are less intensive in children with severe HeFH. In children with HoFH, subclinical atherosclerosis can already be present using computed tomography coronary angiography (CTCA). The question remains whether this is also the case in children with severe HeFH who have a high exposure to elevated LDL-C levels from birth onwards as well. We calculated the cumulative LDL-C exposure (CEtotal [mmol]) in four children with severe HeFH and performed computed tomography coronary angiography (CTCA). These children, aged 13, 14, 15 and 18 years, had CEtotal of 71.3, 97.8, 103.6 and 136.1 mmol, respectively. None of them showed abnormalities on cardiovascular imaging, despite high LDL-C exposure. The results of this study, do not give us an indication to recommend performing CTCA routinely in children with severe HeFH.

Thoughts on sustainability in the use of iodinated contrast media in CT: a practice-oriented review based on the example of a hospital and a private practice

Iodinated contrast media (CM) have become indispensable in computed tomography (CT), angiography, and cardiac cathlab as well as in other X-ray-based procedures, for example in urology. In this context, iodinated CM are released into the environment in particular via patient excretions along with other trace substances. At the same time, the use of iodinated CM also involves CM leftovers as well as packaging and consumables.In order to reduce the discharge of iodinated CM into the environment and to promote efficient use of resources, awareness of the sustainable and responsible use of iodinated CM and associated consumables is essential. A number of effective measures can contribute to this in the short, medium, and long term. Based on the literature and quantitative data from our own routine, aspects of sustainability when dealing with CM in computed tomography are discussed in this review using the example of a hospital and a private practice.When planning and performing contrast-enhanced CT examinations, personalized CM protocols can make CM use more efficient. Some CM manufacturers offer recycling programs for CM leftovers. The collection of CM excretions after CM injections using urine bags might have a major impact on reducing the discharge of iodinated CM into the environment. In addition, responsible use of consumables and packaging material, in particular the use of multi-patient systems, can make a valuable contribution to waste avoidance and resource conservation. All of these measures can ultimately be fully effective in terms of protecting the environment and resources if they can be implemented on a broad basis. For this purpose, an even greater focus on the topic of sustainability among all parties involved is desirable. · Sustainable and responsible use of iodinated contrast media is desirable.. · Various measures can be taken today to reduce the environmental impact and conserve resources.. · CM use can be made more efficient by optimizing contrast-enhanced CT examinations.. · Recycling programs for CM leftovers enable their further use.. · Urine bags might have a major impact on reducing the environmental impact..

Optimization of uniformity in coronary artery enhancement using a bolus tracking technique with a dual region of interest in coronary computed tomographic angiography

BACKGROUND

Consistent coronary artery enhancement is essential to achieve accurate and reproducible quantification of coronary plaque composition.

PURPOSE

To optimize coronary artery uniformity of enhancement using a bolus tracking technique with a dual region of interest (ROI) in coronary computed tomography angiography (CCTA) on a 320-detector CT scanner.

MATERIAL AND METHODS

This prospective study recruited 100 consecutive patients who underwent CCTA and were randomly divided into two groups, namely, a manual trigger group (n = 50), in which a manual fast start technique was used to start the diagnostic scan with the visual evaluation of attenuation in the left atrium and left ventricle, and an automatic trigger group (n = 50), in which a bolus tracking technique was used to automatically start the breath-holding command and diagnostic scan with two ROIs placed in the right and left ventricles. Coronary artery image quality was assessed using quantitative and qualitative scores. The enhancement uniformity was characterized by attenuation variability of the ascending aorta (AAO) and coronary arteries.

RESULTS

No statistically significant differences in the image quality of the coronary arteries were observed between the two groups (all P > 0.05). The coefficients of variation (COVs) of arterial attenuation in the automatic trigger group were significantly smaller than in the manual trigger group (AAO: 9.89% vs. 17.93%; LMA: 10.35% vs. 18.98%; LAD proximal: 12.09% vs. 20.84%; LCX proximal: 11.85% vs. 20.95%; RCA proximal: 12.13% vs. 20.84%; all P < 0.05).

CONCLUSION

The automatic trigger technique accompanied with dual ROI provides consistent coronary artery enhancement and optimizes coronary artery enhancement uniformity in CCTA on a 320-detector CT scanner.

Image quality improvement in head and neck CT angiography: Individualized post-trigger delay versus fixed delay

PURPOSE

To compare the contrast media opacification of head and neck CT angiography (CTA) between conventional fixed trigger delay and individualized post-trigger delay (PTD).

METHODS

In this prospective study (April-October 2022), 196 consecutive participants were randomly divided into two groups to perform head and neck CTA in bolus tracking with either an individualized PTD (Group A) or a fixed 4-second PTD (Group B). All CT and contrast media protocol parameters were consistent between the two groups. One reader evaluated objective image quality, while two readers rated subjective image quality. Objective image quality was compared between groups via two-sample t-test, while the subjective ratings were compared with chi-square analysis.

RESULTS

Participants' clinical information including sex, age, weight, body weight index (BMI), and heart rate were not statistically different between two groups (all p > 0.05). Individualized PTD ranging from 3.5 to 7.9 s (average 5.6 s), which is shorter than fixed delays (p < 0.05). Both readers rated better subjective image quality for the Group A (p < 0.05). The mean vessel enhancement was significantly higher in Group A in all vessels (all p < 0.05).

CONCLUSIONS

Compared to the fixed post-trigger delay in bolus tracking technique, individualized post-trigger delay could achieve reliable scan timing, optimize vessel opacification and obtain better image quality for head and neck CT angiography.

Patient-specific post-trigger delay in coronary CT angiography: A prospective study comparing with fixed delay

OBJECTIVES

To validate the peak enhancement timing of a patient-specific post-trigger delay (PTD) in Coronary CT angiography (CCTA) and compare its image quality against a fixed PTD.

METHODS

In this prospective study, 204 consecutive participants were randomly divided into two groups to perform CCTA in bolus tracking with either a fixed 5-second PTD (Group A) or a patient-specific PTD (Group B). Test bolus was also performed in Group B to determine the reference peak enhancement timing. One reader evaluated objective image quality, while two readers rated subjective image quality. The predicted PTD was validated through correlation and agreement analysis with the reference measurement. Objective image quality was compared between groups via two-sample t-test and linear regression, while the subjective ratings were compared with chi-square analysis.

RESULTS

The two groups each had 102 participants with comparable characteristics (52.9 ± 11.3 versus 52.1 ± 11.3 years of age, and 53 versus 52 males). The scan timing from patient-specific PTD demonstrated strong correlation (R = 0.77) and consistency (ICC = 0.618) with the reference peak timing. Both readers rated better subjective image quality for the Group B (p < 0.001). The mean vessel enhancement was significantly higher in Group B in all coronary vessels (all p < 0.05). After adjusting for the participant variation, the patient-specific PTD strategy was associated with an average of 33.5 HU higher enhancement compared to the fixed PTD.

CONCLUSIONS

Patient-specific delay could achieve reliable scan timing, optimize vessel opacification and obtain better image quality in CCTA.

Intravenous Contrast Material for Cardiac Computed Tomography: Results From the Open-label Multicenter, Multivendor Italian Registry of Contrast Material Use in Cardiac Computed Tomography

PURPOSE

The Italian Registry of Contrast Material use in Cardiac Computed Tomography (iRCM-CCT) is a multicenter, multivendor, observational study on the use of contrast media (CM) in patients undergoing cardiac computed tomography (CCT). The aim of iRCM-CCT is to assess image quality and safety profile of intravenous CM compounds.

MATERIALS AND METHODS

iRCM-CCT enrolled 1842 consecutive patients undergoing CCT (≥50 per site) at 20 cluster sites with the indication of suspected coronary artery disease. Demographic characteristics, CCT, and CM protocols, clinical indications, safety markers, radiation dose reports, qualitative (ie, poor vascular enhancement) and quantitative (ie, HU attenuation values) image parameters were recorded. A centralized coordinating center collected and assessed all image parameters.

RESULTS

The cohort included 891 men and 951 women (age: 63±14 y, body mass index: 26±4 kg/m2) studied with ≥64 detector rows computed tomography scanners and different iodinated intravenous CM protocols and compounds (iodixanol, iopamidol, iohexol, iobitridol, iopromide, and iomeprol). The following vascular attenuation was reported: 504±147 HU in the aorta, 451±146 HU in the right coronary artery, 474±146 HU in the left main, 451±146 HU in the left anterior descending artery, and 441±149 HU in the circumflex artery. In 4% of cases the image quality was not satisfactory due to poor enhancement. The following adverse reactions to CM were recorded: 6 (0.3%) extravasations and 17 (0.9%) reactions (11 mild, 4 moderate, 2 severe).

CONCLUSIONS

In a multicenter registry on CM use during CCT the prevalence of CM-related adverse reactions was very low. The appropriate use of CM is a major determinant of image quality.

Deep learning-based detection of functionally significant stenosis in coronary CT angiography

Patients with intermediate anatomical degree of coronary artery stenosis require determination of its functional significance. Currently, the reference standard for determining the functional significance of a stenosis is invasive measurement of the fractional flow reserve (FFR), which is associated with high cost and patient burden. To address these drawbacks, FFR can be predicted non-invasively from a coronary CT angiography (CCTA) scan. Hence, we propose a deep learning method for predicting the invasively measured FFR of an artery using a CCTA scan. The study includes CCTA scans of 569 patients from three hospitals. As reference for the functional significance of stenosis, FFR was measured in 514 arteries in 369 patients, and in the remaining 200 patients, obstructive coronary artery disease was ruled out by Coronary Artery Disease-Reporting and Data System (CAD-RADS) category 0 or 1. For prediction, the coronary tree is first extracted and used to reconstruct an MPR for the artery at hand. Thereafter, the coronary artery is characterized by its lumen, its attenuation and the area of the coronary artery calcium in each artery cross-section extracted from the MPR using a CNN. Additionally, characteristics indicating the presence of bifurcations and information indicating whether the artery is a main branch or a side-branch of a main artery are derived from the coronary artery tree. All characteristics are fed to a second network that predicts the FFR value and classifies the presence of functionally significant stenosis. The final result is obtained by merging the two predictions. Performance of our method is evaluated on held out test sets from multiple centers and vendors. The method achieves an area under the receiver operating characteristics curve (AUC) of 0.78, outperforming other works that do not require manual correction of the segmentation of the artery. This demonstrates that our method may reduce the number of patients that unnecessarily undergo invasive measurements.

Machine learning-based prediction of insufficient contrast enhancement in coronary computed tomography angiography

OBJECTIVES

Patient-tailored contrast delivery protocols strongly reduce the total iodine load and in general improve image quality in CT coronary angiography (CTCA). We aim to use machine learning to predict cases with insufficient contrast enhancement and to identify parameters with the highest predictive value.

METHODS

Machine learning models were developed using data from 1,447 CTs. We included patient features, imaging settings, and test bolus features. The models were trained to predict CTCA images with a mean attenuation value in the ascending aorta below 400 HU. The accuracy was assessed by the area under the receiver operating characteristic (AUROC) and precision-recall curves (AUPRC). Shapley Additive exPlanations was used to assess the impact of features on the prediction of insufficient contrast enhancement.

RESULTS

A total of 399 out of 1,447 scans revealed attenuation values in the ascending aorta below 400 HU. The best model trained using only patient features and CT settings achieved an AUROC of 0.78 (95% CI: 0.73-0.83) and AUPRC of 0.65 (95% CI: 0.58-0.71). With the inclusion of the test bolus features, it achieved an AUROC of 0.84 (95% CI: 0.81-0.87), an AUPRC of 0.71 (95% CI: 0.66-0.76), and a sensitivity of 0.66 and specificity of 0.88. The test bolus' peak height was the feature that impacted low attenuation prediction most.

CONCLUSION

Prediction of insufficient contrast enhancement in CT coronary angiography scans can be achieved using machine learning models. Our experiments suggest that test bolus features are strongly predictive of low attenuation values and can be used to further improve patient-specific contrast delivery protocols.

KEY POINTS

• Prediction of insufficient contrast enhancement in CT coronary angiography scans can be achieved using machine learning models. • The peak height of the test bolus curve is the most impacting feature for the best performing model.