An Optimized Test Bolus Contrast Injection Protocol for Consistent Coronary Artery Luminal Enhancement for Coronary CT Angiography

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.

Comparison of ultrahigh and standard resolution photon-counting CT angiography of the femoral arteries in a continuously perfused in vitro model

BACKGROUND

With the emergence of photon-counting CT, ultrahigh-resolution (UHR) imaging can be performed without dose penalty. This study aims to directly compare the image quality of UHR and standard resolution (SR) scan mode in femoral artery angiographies.

METHODS

After establishing continuous extracorporeal perfusion in four fresh-frozen cadaveric specimens, photon-counting CT angiographies were performed with a radiation dose of 5 mGy and tube voltage of 120 kV in both SR and UHR mode. Images were reconstructed with dedicated convolution kernels (soft: Body-vascular (Bv)48; sharp: Bv60; ultrasharp: Bv76). Six radiologists evaluated the image quality by means of a pairwise forced-choice comparison tool. Kendall's concordance coefficient (W) was calculated to quantify interrater agreement. Image quality was further assessed by measuring intraluminal attenuation and image noise as well as by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR).

RESULTS

UHR yielded lower noise than SR for identical reconstructions with kernels ≥ Bv60 (p < 0.001). UHR scans exhibited lower intraluminal attenuation compared to SR (Bv60: 406.4 ± 25.1 versus 418.1 ± 30.1 HU; p < 0.001). Irrespective of scan mode, SNR and CNR decreased while noise increased with sharper kernels but UHR scans were objectively superior to SR nonetheless (Bv60: SNR 25.9 ± 6.4 versus 20.9 ± 5.3; CNR 22.7 ± 5.8 versus 18.4 ± 4.8; p < 0.001). Notably, UHR scans were preferred in subjective assessment when images were reconstructed with the ultrasharp Bv76 kernel, whereas SR was rated superior for Bv60. Interrater agreement was high (W = 0.935).

CONCLUSIONS

Combinations of UHR scan mode and ultrasharp convolution kernel are able to exploit the full image quality potential in photon-counting CT angiography of the femoral arteries.

RELEVANCE STATEMENT

The UHR scan mode offers improved image quality and may increase diagnostic accuracy in CT angiography of the peripheral arterial runoff when optimized reconstruction parameters are chosen.

KEY POINTS

• UHR photon-counting CT improves image quality in combination with ultrasharp convolution kernels. • UHR datasets display lower image noise compared with identically reconstructed standard resolution scans. • Scans in UHR mode show decreased intraluminal attenuation compared with standard resolution imaging.

Contrast media timing optimization for coronary CT angiography: a retrospective validation study in swine

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.

A patient- and acquisition-tailored injection approach for improving consistency of CT enhancement towards a target CT value in coronary CT angiography

BACKGROUND

Unoptimized coronary CT angiography (CTA) exams typically result in a highly variable arterial enhancement (HU_a ) across patients. This study aimed at harmonizing arterial enhancement by implementing a patient-, contrast- and kV-tailored injection protocol.

METHODS

First, the optimal body size metric to predict HU_a was identified by retrospectively analysing images of 76 patients, acquired with 70 ml contrast media (G1). Second, using phantom experiments, correction factors for the effect of kV and contrast concentration on HU_a were determined. Third, a model was developed, prescribing the optimal contrast dose to be injected to obtain a diagnostically appropriate arterial target enhancement HU_target . The model was then validated on 278 prospectively collected patients, in two groups with two different HU_target : 525 HU (207 patients, G2A) and 425 HU (71 patients, G2B). The HU_a histograms were compared among groups and to the target enhancement through their mean and standard deviation (SD) at 100 kVp reference level. Also, signal-to-noise ratio was obtained and compared among the groups.

RESULTS

Fat free mass (FFM) showed the highest correlation with HU_a (r = 0.69). KVp correction factors ranged from 0.65 at 70 kVp to 1.22 at 140 kVp. The obtained model reduced the group heterogeneity (SD) from 101HU for reference G1 to 75HU (p < 0.001) for G2A and 68HU (p < 0.001) for G2B. The mean HU_a of 506HU in G2A was slightly below HU_target  = 525HU (p = 0.01) whereas in G2B, the mean HU_a of 414HU was not significantly different from HU_target  = 425HU (p = 0.54). The total iodine dose was lowered from 19.5 g-I to 17.6 g-I and 14.2 g-I from G1 to G2A and G2B, on average.

CONCLUSION

A contrast injection model, based on patient's fat free mass and accounting for the contrast agent concentration and the planned CT-scan tube voltage, harmonized arterial enhancement among patients towards a predefined target enhancement in coronary CTA scanning, without affecting the bolus timing.

Optimization of contrast material administration for coronary CT angiography using a software-based test-bolus evaluation algorithm

OBJECTIVES

To evaluate the benefit of a prototype circulation time-based test bolus evaluation algorithm for the individualized optimal timing of contrast media (CM) delivery in patients undergoing coronary CT angiography (CCTA).

METHODS

Thirty-two patients (62 ± 16 years) underwent CCTA using a prototype bolus evaluation tool to determine the optimal time-delay for CM administration. Contrast attenuation, signal-to-noise ratio (SNR), objective, and subjective image quality were evaluated by two independent radiologists. Results were compared to a control cohort (matched for age, sex, body mass index, and tube voltage) of patients who underwent CCTA using the generic test bolus peak attenuation +4 s protocol as scan delay.

RESULTS

In the study group, the mean time delay to CCTA acquisition was significantly longer (26.0 ± 2.9 s) compared to the control group (23.1 ± 3.5 s; p < 0.01). In the study group, SNR improvement was seen in the right coronary artery (17.5 vs 13; p = 0.028), the left main (15.3 vs 12.3; p = 0.027), and the left anterior descending artery (18.5 vs 14.1; p = 0.048). Subjective image quality was rated higher in the study group (4.75 ± 0.7 vs 3.64 ± 0.5; p < 0.001).

CONCLUSIONS

The prototype test bolus evaluation algorithm provided a reliable patient-specific scan delay for CCTA that ensured homogenous vascular attenuation, improvement in objective and subjective image quality, and avoidance of beam hardening artifacts.

ADVANCES IN KNOWLEDGE

The prototype contrast bolus evaluation and optimization tool estimated circulation time-based time-delay improves the overall quality of CCTA.

The auto segmentation for cardiac structures using a dual-input deep learning network based on vision saliency and transformer

Purpose

Accurate segmentation of cardiac structures on coronary CT angiography (CCTA) images is crucial for the morphological analysis, measurement, and functional evaluation. In this study, we achieve accurate automatic segmentation of cardiac structures on CCTA image by adopting an innovative deep learning method based on visual attention mechanism and transformer network, and its practical application value is discussed.

Methods

We developed a dual‐input deep learning network based on visual saliency and transformer (VST), which consists of self‐attention mechanism for cardiac structures segmentation. Sixty patients’ CCTA subjects were randomly selected as a development set, which were manual marked by an experienced technician. The proposed vision attention and transformer mode was trained on the patients CCTA images, with a manual contour‐derived binary mask used as the learning‐based target. We also used the deep supervision strategy by adding auxiliary losses. The loss function of our model was the sum of the Dice loss and cross‐entropy loss. To quantitatively evaluate the segmentation results, we calculated the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Meanwhile, we compare the volume of automatic segmentation and manual segmentation to analyze whether there is statistical difference.

Results

Fivefold cross‐validation was used to benchmark the segmentation method. The results showed the left ventricular myocardium (LVM, DSC = 0.87), the left ventricular (LV, DSC = 0.94), the left atrial (LA, DSC = 0.90), the right ventricular (RV, DSC = 0.92), the right atrial (RA, DSC = 0.91), and the aortic (AO, DSC = 0.96). The average DSC was 0.92, and HD was 7.2 ± 2.1 mm. In volume comparison, except LVM and LA (p < 0.05), there was no significant statistical difference in other structures. Proposed method for structural segmentation fit well with the true profile of the cardiac substructure, and the model prediction results closed to the manual annotation.

Conclusions

The adoption of the dual‐input and transformer architecture based on visual saliency has high sensitivity and specificity to cardiac structures segmentation, which can obviously improve the accuracy of automatic substructure segmentation. This is of gr

Big Data Framework Using Spark Architecture for Dose Optimization Based on Deep Learning in Medical Imaging

Deep learning and machine learning provide more consistent tools and powerful functions for recognition, classification, reconstruction, noise reduction, quantification and segmentation in biomedical image analysis. Some breakthroughs. Recently, some applications of deep learning and machine learning for low-dose optimization in computed tomography have been developed. Due to reconstruction and processing technology, it has become crucial to develop architectures and/or methods based on deep learning algorithms to minimize radiation during computed tomography scan inspections. This chapter is an extension work done by Alla et al. in 2020 and explain that work very well. This chapter introduces the deep learning for computed tomography scan low-dose optimization, shows examples described in the literature, briefly discusses new methods for computed tomography scan image processing, and provides conclusions. We propose a pipeline for low-dose computed tomography scan image reconstruction based on the literature. Our proposed pipeline relies on deep learning and big data technology using Spark Framework. We will discuss with the pipeline proposed in the literature to finally derive the efficiency and importance of our pipeline. A big data architecture using computed tomography images for low-dose optimization is proposed. The proposed architecture relies on deep learning and allows us to develop effective and appropriate methods to process dose optimization with computed tomography scan images. The real realization of the image denoising pipeline shows us that we can reduce the radiation dose and use the pipeline we recommend to improve the quality of the captured image.

Image quality and radiation dose of different scanning protocols in DSCT cardiothoracic angiography for children with tetralogy of fallot

The aim of this study was to investigate the image quality and radiation dose of different scanning protocols in dual-source CT cardiothoracic angiography for children with tetralogy of Fallot (TOF). Seventy-five consecutive children with known or suspected TOF were enrolled to undergo prospective ECG-triggering sequential dual-source CT (DSCT) cardiothoracic angiography. According to the scanning protocols, these patients were randomly divided into 3 groups: fixed delay time (FDT, n = 25, group A), automatic bolus-tracking (ABT, n = 25, group B) and manual bolus-tracking (MBT, n = 25, group C). Subjective and objective image quality were evaluated. The radiation doses were recorded. The image quality scores of group C were significantly higher than those of group A and B. The absolute value of difference (D-value) on CT attenuation between left (CT_LV) and right ventricle (CT_RV) in group C was significantly lower than that in group A and B. The total effective dose of groups A, B and C were 0.39 ± 0.06 mSv, 0.40 ± 0.07 mSv and 0.40 ± 0.08 mSv, respectively. There was no significant difference among 3 groups (P = 0.722). Scanning protocol has significantly impacts on the image quality of cardiovascular structures for TOF patients. Compared with the conventional scanning protocols FDT and ABT, the MBT technique provides high image quality and achieves more homogenous attenuation among different patients with TOF.