Prospectively ECG-triggered high-pitch 80 kVp coronary computed tomography angiography with 30 mL of 270 mg I/mL contrast material and iterative reconstruction

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction

PURPOSE

To investigate the use of an 80-kVp tube voltage combined with a deep learning image reconstruction (DLIR) algorithm in coronary CT angiography (CCTA) for overweight patients to reduce radiation and contrast doses in comparison with the 120-kVp protocol and adaptive statistical iterative reconstruction (ASIR-V).

METHODS

One hundred consecutive CCTA patients were prospectively enrolled and randomly divided into a low-dose group (n = 50) with 80-kVp, smart mA for noise index (NI) of 36 HU, contrast dose rate of 18 mgI/kg/s and DLIR and 60 % ASIR-V and a standard-dose group (n = 50) with 120-kVp, smart mA for NI of 25 HU, contrast dose rate of 32 mgI/kg/s and 60 % ASIR-V. The radiation and contrast dose, subjective image quality score, attenuation values, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared.

RESULTS

The low-dose group achieved a significant reduction in the effective radiation dose (1.01 ± 0.45 mSv vs 1.85 ± 0.40 mSv, P < 0.001) and contrast dose (33.69 ± 3.87 mL vs 59.11 ± 5.60 mL, P < 0.001) compared to the standard-dose group. The low-dose group with DLIR presented similar enhancement but lower noise, higher SNR and CNR and higher subjective quality scores than the standard-dose group. Moreover, the same patient comparison in the low-dose group between different reconstructions showed that DLIR images had slightly and consistently higher CT values in small vessels, indicating better defined vessels, much lower image noise, higher SNR and CNR and higher subjective quality scores than ASIR-V images (all P < 0.001).

CONCLUSIONS

The application of 80-kVp and DLIR allows for significant radiation and dose reduction while further improving image quality in CCTA for overweight patients.

The influence of image quality on diagnostic performance of a machine learning-based fractional flow reserve derived from coronary CT angiography

OBJECTIVE

To investigate the effect of image quality of coronary CT angiography (CCTA) on the diagnostic performance of a machine learning-based CT-derived fractional flow reserve (FFR_CT).

METHODS

This nationwide retrospective study enrolled participants from 10 individual centers across China. FFR_CT analysis was performed in 570 vessels in 437 patients. Invasive FFR and FFR_CT values ≤ 0.80 were considered ischemia-specific. Four-score subjective assessment based on image quality and objective measurement of vessel enhancement was performed on a per-vessel basis. The effects of body mass index (BMI), sex, heart rate, and coronary calcium score on the diagnostic performance of FFR_CT were studied.

RESULTS

Among 570 vessels, 216 were considered ischemia-specific by invasive FFR and 198 by FFR_CT. Sensitivity and specificity of FFR_CT for detecting lesion-specific ischemia were 0.82 and 0.93, respectively. Area under the curve (AUC) of high-quality images (0.93, n = 159) was found to be superior to low-quality images (0.80, n = 92, p = 0.02). Objective image quality and heart rate were also associated with diagnostic performance of FFR_CT, whereas there was no statistical difference in diagnostic performance among different BMI, sex, and calcium score groups (all p > 0.05, Bonferroni correction).

CONCLUSIONS

This retrospective multicenter study supported the FFR_CT as a noninvasive test in evaluating lesion-specific ischemia. Subjective image quality, vessel enhancement, and heart rate affect the diagnostic performance of FFR_CT.

KEY POINTS

• FFR_CTcan be used to evaluate lesion-specific ischemia. • Poor image quality negatively affects the diagnostic performance of FFR_CT. • CCTA with ≥ score 3, intracoronary enhancement degree of 300-400 HU, and heart rate below 70 bpm at scanning could be of great benefit to more accurate FFR_CTanalysis.

Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry

OBJECTIVE. Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR_ML). However, attenuation values vary according to the tube voltage used, and it has not been shown whether this significantly affects the diagnostic performance of cFFR and cFFR_ML. Therefore, the purpose of this study is to retrospectively evaluate the effect of tube voltage on the diagnostic performance of cFFR_ML. MATERIALS AND METHODS. A total of 525 coronary vessels in 351 patients identified in the MACHINE consortium registry were evaluated in terms of invasively measured FFR and cFFR_ML. CCTA examinations were performed with a tube voltage of 80, 100, or 120 kVp. For each tube voltage value, correlation (assessed by Spearman rank correlation coefficient), agreement (evaluated by intraclass correlation coefficient and Bland-Altman plot analysis), and diagnostic performance (based on ROC AUC value, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) of the cFFR_ML in terms of detection of significant stenosis were calculated. RESULTS. For tube voltages of 80, 100, and 120 kVp, the Spearman correlation coefficient for cFFR_ML in relation to the invasively measured FFR value was ρ = 0.684, ρ = 0.622, and ρ = 0.669, respectively (p < 0.001 for all). The corresponding intraclass correlation coefficient was 0.78, 0.76, and 0.77, respectively (p < 0.001 for all). Sensitivity was 100.0%, 73.5%, and 85.0%, and specificity was 76.2%, 79.0%, and 72.8% for tube voltages of 80, 100, and 120 kVp, respectively. The ROC AUC value was 0.90, 0.82, and 0.80 for 80, 100, and 120 kVp, respectively (p < 0.001 for all). CONCLUSION. CCTA-derived cFFR_ML is a robust method, and its performance does not vary significantly between examinations performed using tube voltages of 100 kVp and 120 kVp. However, because of rapid advancements in CT and postprocessing technology, further research is needed.

Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography

Aims

Iterative reconstruction (IR) algorithms allow for a significant reduction in radiation dose of coronary computed tomography angiography (CCTA). We performed a head-to-head comparison of adaptive statistical IR (ASiR) and model-based IR (MBIR) algorithms to assess their impact on quantitative image parameters and diagnostic accuracy for submillisievert CCTA.

Methods and results

CCTA datasets of 91 patients were reconstructed using filtered back projection (FBP), increasing contributions of ASiR (20, 40, 60, 80, and 100%), and MBIR. Signal and noise were measured in the aortic root to calculate signal-to-noise ratio (SNR). In a subgroup of 36 patients, diagnostic accuracy of ASiR 40%, ASiR 100%, and MBIR for diagnosis of coronary artery disease (CAD) was compared with invasive coronary angiography. Median radiation dose was 0.21 mSv for CCTA. While increasing levels of ASiR gradually reduced image noise compared with FBP (up to - 48%, P < 0.001), MBIR provided largest noise reduction (-79% compared with FBP) outperforming ASiR (-59% compared with ASiR 100%; P < 0.001). Increased noise and lower SNR with ASiR 40% and ASiR 100% resulted in substantially lower diagnostic accuracy to detect CAD as diagnosed by invasive coronary angiography compared with MBIR: sensitivity and specificity were 100 and 37%, 100 and 57%, and 100 and 74% for ASiR 40%, ASiR 100%, and MBIR, respectively.

Conclusion

MBIR offers substantial noise reduction with increased SNR, paving the way for implementation of submillisievert CCTA protocols in clinical routine. In contrast, inferior noise reduction by ASiR negatively affects diagnostic accuracy of submillisievert CCTA for CAD detection.

Low kV and Low Concentration Contrast Agent with Iterative Reconstruction of Computed Tomography (CT) Coronary Angiography: A Preliminary Study

Background

The aim of this study was to evaluate the image quality and radiation dose of CT coronary angiography (CTCA) with low kV, low concentration contrast agent, and iterative reconstruction.

Material/Methods

Ninety cases were randomly divided into 3 groups according to contrast agent concentration: group A 270 mg/ml (100 kV), group B 350 mg/ml (120 kV), and group C 370 mg/ml (120 kV), with 30 cases per group. Tube current was 200–250 mAs. Collimator width was 128×0.6 mm. Rotation speed was 0.27 s. The CT value of the left and right coronary arteries and the ascending aortic root was measured. The SNR and CNR of the images were calculated to evaluate the image quality objectively. The CTDI, DLP, and contrast injection were recorded.

Results

There were no significant differences in sex, age, weight, height, and BMI among the 3 groups. There was no statistically significant difference between left and right coronary artery and ascending aortic root CT value, background noise, SNR, and CNR. Compared to B and C, the ED in group A decreased by about 27.58% and 28.21%, respectively. The total amount of iodine in group A was decreased by about 21.27% and 24.83%, respectively compared with groups B and C.

Conclusions

Low kV and low concentration contrast agent combined with iterative reconstruction for CTCA imaging produced image quality consistent with that of conventional CTCA and significantly reduced the dosage of the radiation and injected iodine.

Minimized Radiation and Contrast Agent Exposure for Coronary Computed Tomography Angiography: First Clinical Experience on a Latest Generation 256-slice Scanner

RATIONALE AND OBJECTIVES

The aim of the study was to evaluate the impact of the latest coronary computed tomography angiography (CCTA) techniques allowing a radiation- and contrast-sparing protocol on image quality in unselected patients referred for exclusion of suspected coronary artery disease (CAD).

MATERIALS AND METHODS

This prospective study was approved by the local ethics committee, and all patients provided written informed consent. Between March and June 2015, 89 consecutive patients (61% male; mean age 55 ± 11 years) referred for exclusion of CAD by 256-slice CCTA using prospective electrocardiogram triggering were included. Tube voltage (80-120 kVp), tube current (180-310 mA) as well contrast agent volume (25-45 mL) and flow rate (3.5-5 mL/s) were adapted to body mass index. Signal intensity was measured by placing a region of interest in the aortic root, the left main artery, and the proximal right coronary artery. Image noise was measured in the aortic root. Two independent blinded readers semi-quantitatively assessed the image quality regarding motion, noise, and contrast on a 4-point scale.

RESULTS

Median contrast agent volume and median effective radiation dose were 35 mL (interquartile range, 30-40 mL) and 0.5 mSv (interquartile range, 0.4-0.6 mSv), respectively. Mean attenuation in the aortic root was 412 ± 89 Hounsfield units. Diagnostic image quality was obtained in 1050 of 1067 (98.4%) coronary segments and, on an intention-to-diagnosis basis, in 85 of 89 (95.5%) patients. Below a cut-off heart rate of 67 beats/min, only 1 of 974 (0.1%) coronary segments was nondiagnostic.

CONCLUSION

A radiation- and contrast-sparing protocol for CCTA on a latest generation 256-slice computed tomography scanner yields diagnostic image quality in patients referred for CAD exclusion in daily clinical routine.