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Rationale and Objectives: To explore the value of an artificial intelligence (AI)-based application for identifying plaque-specific stenosis and obstructive coronary artery disease from monoenergetic spectral reconstructions on coronary computed tomography angiography (CTA).Materials and Methods: This retrospective study enrolled 71 consecutive patients (52 men, 19 women; 63.3 ± 10.7 years) who underwent coronary CTA and invasive coronary angiography for diagnosing coronary artery disease. The conventional 120 kVp images and eight different virtual monoenergetic images (VMIs) (from 40 keV to 140 keV at increment of 10 keV) were reconstructed. An AI system automatically detected plaques from the conventional 120 kVp images and VMIs and calculated the degree of stenosis, which was further compared to invasive coronary angiography. The assessment was performed at a segment, vessel, and patient level.Results: Vessel and segment-based analyses showed comparable diagnostic performance between conventional CTA images and VMIs from 50 keV to 90 keV. For vessel-based analysis, the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of conventional CTA were 74.3% (95% CI: 64.9%-82.0%), 85.6% (95% CI: 77.0%-91.4%), 84.3% (95% CI: 75.2%-90.7%), 76.1% (95% CI: 67.1%-83.3%) and 79.8% (95% CI: 73.7%-84.9%), respectively; the average sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy values of the VMIs ranging from 50 keV to 90 keV were 71.6%, 90.7%, 87.5%, 64.1% and 81.6%, respectively. For plaque-based assessment, diagnostic performance of the average VMIs ranging from 50 keV to 100 keV showed no significant statistical difference in diagnostic accuracy compared to those of conventional CTA images in detecting calcified (91.4% vs. 93.8%, p > 0.05), noncalcified (92.6% vs. 85.2%, p > 0.05) or mixed (80.2% vs. 81.2%, p > 0.05) stenosis, although the specificity was slightly higher (53.4% vs. 40.0%, p > 0.05) in detecting stenosis caused by mixed plaques. For VMIs above 100 keV, the diagnostic accuracy dropped significantly.Conclusion: Our study showed that the performance of an AI-based application employed to detect significant coronary stenosis in virtual monoenergetic reconstructions ranging from 50 keV to 90 keV was comparable to conventional 120 kVp reconstructions. [ABSTRACT FROM AUTHOR]

Background: Vasodilator stress computed tomography perfusion (sCTP) imaging is complementary to coronary CT angiography (CCTA), used to determine the hemodynamic significance of coronary artery disease. However, it requires a separate image acquisition due to motion artifacts caused by higher heart rates during stress, resulting in increased iodine contrast dose and radiation. We sought to determine whether a novel motion correction algorithm applied to stress images would improve the visualization of the coronary arteries to potentially allow CCTA + sCTP evaluation in a single scan.Methods: 28 patients referred for clinically indicated CCTA (iCT, Philips) underwent sCTP imaging (retrospective-gating with dose modulation; 100 kVp and 250 mA; 5.2 ± 4.3 mSv) after regadenoson (0.4 mg, Astellas). Stress images were reconstructed using standard filtered back-projection (FBP) and also processed to generate interaction-free coronary motion-compensated back-projection reconstructions (MCR). Each coronary artery from standard FBP and MCR images was viewed side-by-side by a reader blinded to the reconstruction technique, who graded severity of motion artifact by segment (scale 0-5, with 3 as the threshold for diagnostic quality) and to measure signal-to-noise and contrast-to-noise ratios (SNR, CNR).Results: Visualization scores were higher with MCR for all coronary segments, including 14/86 (16%) segments deemed as non-diagnostic on FBP images. SNR (7 ± 2) and CNR (15 ± 8) were unchanged by motion-correction (7 ± 3, p = 0.88 and 15 ± 5, p = 0.94, respectively).Conclusions: MCR improves the visualization of coronary anatomy on sCTP images without degrading image characteristics. This algorithm is an important step towards the combined assessment of coronary anatomy and myocardial perfusion in a single scan, which will reduce study time, radiation exposure and contrast dose. [ABSTRACT FROM AUTHOR]

Background The aim of this study was to assess the potential for radiation dose reduction using knowledge-based iterative model reconstruction (K-IMR) algorithms in combination with ultra-low dose body mass index (BMI)-adapted protocols in coronary CT angiography (coronary CTA). Methods Forty patients undergoing clinically indicated coronary CTA were randomly assigned to two groups with BMI-adapted (I: <25.0 kg/m 2 , II: <28.0 kg/m 2 , III: <30.0 kg/m 2 , IV: ≥30.0 kg/m 2 ) low dose (LD, I: 100kV p /75 mAs, II: 100kV p /100 mAs, III: 100kV p /150 mAs, IV: 120kV p /150 mAs, n = 20) or ultra-low dose (ULD, I: 100kV p /50 mAs, II: 100kV p /75 mAs, III: 100kV p /100 mAs, IV: 120kV p /100 mAs, n = 20) protocols. Prospectively-triggered coronary CTA was performed using a 256-MDCT with the lowest reasonable scan length. Images were generated with filtered back projection (FBP), a noise-reducing hybrid iterative algorithm (iD, levels 2/5) and K-IMR using cardiac routine (CR) and cardiac sharp settings, levels 1–3. Results Groups were comparable regarding anthropometric parameters, heart rate, and scan length. The use of ULD protocols resulted in a significant reduction of radiation exposure (0.7 (0.6–0.9) mSv vs. 1.1 (0.9–1.7) mSv; p < 0.02). Image quality was significantly better in the ULD group using K-IMR CR 1 compared to FBP, iD 2 and iD 5 in the LD group, resulting in fewer non-diagnostic coronary segments (2.4% vs. 11.6%, 9.2% and 6.1%; p < 0.05). Conclusions The combination of K-IMR with BMI-adapted ULD protocols results in significant radiation dose savings while simultaneously improving image quality compared to LD protocols with FBP or hybrid iterative algorithms. Therefore, K-IMR allows for coronary CTA examinations with high diagnostic value and very low radiation exposure in clinical routine. [ABSTRACT FROM AUTHOR]

Rationale and Objectives Selecting the optimal phase for coronary artery evaluation can be challenging, especially at higher heart rates, given that the optimal phase may differ for each of the coronary arteries. This study aimed to evaluate a novel vessel-specific algorithm which automatically outputs the minimum motion phase per coronary artery. Materials and Methods The study included 44 patients who underwent 256-slice cardiac computed tomography for evaluation of chest pain. End-systolic and mid-diastolic minimal motion phases were automatically calculated by a previously validated global motion algorithm and by a new vessel-specific algorithm which calculates the minimum motion for each of the three main coronary arteries, separately. Two readers blindly evaluated all coronary segments for image quality. Median scores per coronary artery were compared by the Wilcoxon signed rank test. Results The variation, per patient, between the optimal phases of the three coronary arteries was 5.0 ± 4.5% (1%–22%) for end systole and 4.8 ± 4.1% (0%–19%) for mid diastole. The mean image quality scores per coronary artery were 4.0 ± 0.61 for the vessel-specific approach and 3.80 ± 0.69 for the global phase selection ( P < .001). Overall, 46 of 122 arteries had a better score with the vessel-specific approach and five with the standard global approach. Interreader agreement was substantial ( k = 0.72). Conclusions This study has shown that multiple phases are required to ensure optimal image quality for all three coronary arteries and that a vessel-specific phase selection algorithm achieves superior results to the standard global approach. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: The cardiac chamber volumes and functions can be assessed manually and automatically using the current computed tomography (CT) workstation system. We aimed to evaluate the accuracy and precision and to establish the reference values for both segmentation methods using cardiac CT angiography (CTA). Materials and Methods: A total of 134 subjects (mean age 55.3 years, 72 women) without heart disease were enrolled in the study. The cardiac four-chamber volumes, left ventricular (LV) mass, and biventricular functions were measured with manual, semiautomatic, and model-based fully automatic approaches. The accuracies of the semiautomated and fully automated approaches were validated by comparing them with manual segmentation as a reference. The precision error was determined and compared for both manual and automatic measurements. Results: No significant difference was found between the manual and semiautomatic assessments for the assessment of all functional parameters (P > .05). Using the manual method as a reference, the automatic approach provided a similar value in LV ejection fraction and left atrial volumes in both genders and right ventricular (RV) stroke volume in women (P > .05), with some underestimation of RV volume (P < .001) and overestimation of all remaining parameters (P < .05) in both genders. In addition, a significantly higher precision with a considerable association in intermeasurement (reproducibility) was observed using the automated approach. Conclusions: The model-based fully automatic segmentation algorithm can help with the assessment of the cardiac four-chamber volume and function. This may help in establishing reference values of functional parameters in patients who undergo cardiac CTA. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: To investigate whether “full” iterative reconstruction, a knowledge-based iterative model reconstruction (IMR), enables radiation dose reduction by 80% at cardiac computed tomography (CT). Materials and Methods: A total of 23 patients (15 men, eight women; mean age 64.3 ± 13.4 years) who underwent retrospectively electrocardiography-gated cardiac CT with dose modulation were evaluated. We compared full-dose (FD; 730 mAs) images reconstructed with filtered back projection (FBP) technique and the low-dose (LD; 146 mAs) images reconstructed with FBP and IMR techniques. Objective and subjective image quality parameters were compared among the three different CT images. Results: There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of LD-IMR (18.3 ± 10.6 Hounsfield units [HU]) was significantly lowest among the three reconstructions (41.9 ± 15.3 HU for FD-FBP and 109.9 ± 42.6 HU for LD-FBP; P < .01). The contrast-to-noise ratio of LD-IMR was better than that of FD-FBP and LD-FBP (P < .01). Visual evaluation score was also highest for LD-IMR. Conclusions: The IMR can provide improved image quality at super-low-dose cardiac CT with 20% of the standard tube current. [Copyright &y& Elsevier]

Objectives: To investigate the effects of a new model-based type of iterative reconstruction (M-IR) technique, the iterative model reconstruction, on image quality of prospectively gated coronary CT angiography (CTA) acquired at low-tube-voltage. Methods: Thirty patients (16 men, 14 women; mean age 52.2±13.2 years) underwent coronary CTA at 100-kVp on a 256-slice CT. Paired image sets were created using 3 types of reconstruction, i.e. filtered back projection (FBP), a hybrid type of iterative reconstruction (H-IR), and M-IR. Quantitative parameters including CT-attenuation, image noise, and contrast-to-noise ratio (CNR) were measured. The visual image quality, i.e. graininess, beam-hardening, vessel sharpness, and overall image quality, was scored on a 5-point scale. Lastly, coronary artery segments were evaluated using a 4-point scale to investigate the assessability of each segment. Results: There was no significant difference in coronary arterial CT attenuation among the 3 reconstruction methods. The mean image noise of FBP, H-IR, and M-IR images was 29.3±9.6, 19.3±6.9, and 12.9±3.3HU, respectively, there were significant differences for all comparison combinations among the 3 methods (p <0.01). The CNR of M-IR was significantly better than of FBP and H-IR images (13.5±5.0 [FBP], 20.9±8.9 [H-IR] and 39.3±13.9 [M-IR]; p <0.01). The visual scores were significantly higher for M-IR than the other images (p <0.01), and 95.3% of the coronary segments imaged with M-IR were of assessable quality compared with 76.7% of FBP- and 86.9% of H-IR images. Conclusions: M-IR can provide significantly improved qualitative and quantitative image quality in prospectively gated coronary CTA using a low-tube-voltage. [ABSTRACT FROM AUTHOR]

Background: Functional assessment of myocardial perfusion in computed tomography (CT) is a challenge. Objective: To evaluate CT dynamic myocardial perfusion imaging (MPI) using a wide-detector scanner. Methods: Time to peak (TTP), peak enhancement (PE), upslope (US), and the area under the curve (AUC) were calculated in 12 pigs (256-slice multidetector CT scanner). Results: The entire myocardium was covered by the scan volume. TTP was increased, and PE, US, and AUC were decreased in poststenotic myocardium. Conclusion: CT MPI with complete coverage of the myocardium is feasible, providing evaluation of the physiological significance of coronary artery stenosis. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To assess the image quality (IQ) of an iterative reconstruction (IR) technique (iDose4) from prospective electrocardiography (ECG)-triggered coronary computed tomography angiography (coronary CTA) on a 256-slice multi-detector CT (MDCT) scanner and determine the optimal dose reduction using IR that can provide IQ comparable to filtered back projection (FBP). Method and materials: 110 consecutive patients (69 men, 41 women; age: 54±10 years) underwent coronary CTA on a 256-slice MDCT (Brilliance iCT, Philips Healthcare). The control group (Group A, n =21) were scanned using the conventional tube output (120kVp, 210mAs) and reconstructed using FBP. The other 4 groups were scanned with the same kVp but successively reduced tube output as follows: B[n =15]: 125mAs; C[n =22]: 105mAs; D[n =36]: 84mAs: E[n =16]: 65mAs) and reconstructed using IR levels of L3 (Group B), L4 (Group C) and L5 (Groups D and E), to compensate for the noise increase. All images were reconstructed using the same kernel (XCB). Two radiologists graded IQ in a blinded fashion on a 4-point scale (4 – excellent, 3 – good, 2 – fair and 1 – poor). Quantitative measurements of CT values, image noise and contrast-to-noise (CNR) were measured in each group. A receiver-operating characteristic (ROC) analysis was performed to determine a radiation reduction threshold up to which excellent IQ was maintained. Results: There were no significant differences in objective noise, SNR and CNR values among Groups A, B, C, D, and E (P =0.14, 0.09, 0.17, respectively). There were no significant differences in the scores of the subjective IQ between Group A, and Groups B, C, D, E (P =0.23–0.97). Significant differences in image sharpness and study acceptability were observed between groups A and E (P <0.05). Using the criterion of excellent IQ (score 4), the ROC curve of dose levels and IQ acceptability established a reduction of 60% of tube output (Group D) as optimum cutoff point (AUC: 0.72, 95% CI: 0.59–0.86). Group D (84mAs with L5) provided equivalent subjective image ranking (with lumen sharpness taken into account) and objective IQ measurements (noise: 36.5±10.7; SNR: 13.6±4.9; CNR: 16.28±5.4) compared with FBP images in Group A (noise: 35.5±9.4; SNR: 12.4±2.5; CNR: 15.4±3.2) (P =0.14, 0.09, 0.17, respectively). The effective dose (ED) of Group D was 63% lower than that of Group A (1.2±0.1mSv versus 3.2±0.6mSv). Conclusion: Iterative reconstruction techniques can provide 63% ED reduction in prospectively-triggered coronary CTA using 256-slice MDCT while maintaining excellent image quality. [Copyright &y& Elsevier]

Abstract: Objectives: To evaluate the precision and accuracy in CT attenuation measurement of vascular wall using region-of-interest (ROI) supported by differentiation curves. Study design: We used vascular models (actual attenuation value of the wall: 87HU) with wall thicknesses of 1.5, 1.0, or 0.5mm, filled with contrast material of 250, 348, or 436HU. The nine vascular models were scanned with a 64-detector CT. The wall attenuation values were measured using three sizes (diameter: 0.5, 1.0, and 1.5mm) of ROIs without differentiation curves. Sixteen measurements were repeated for each vascular model by each of two operators. Measurements supported by differentiation curves were also performed. We used analyses of variance with repeated measures for the measured attenuations for each size of the ROI. Results: Without differentiation curves, there were significant differences in the attenuation values of the wall among the three densities of contrast material, and the attenuation values tended to be overestimated more as the contrast material density increased. Operator dependencies were also found in measurements for 0.5- and 1.5-mm thickness models. With differentiation curves, measurements were not possible for 0.5- and 1.0-mm thickness models. Using differentiation curves for 1.5-mm thickness models with a ROI of 1.0- or 1.5-mm diameter, the wall attenuations were not affected by the contrast material densities and were operator independent, measuring between 75 and 103HU. Conclusions: The use of differentiation curves can improve the precision and accuracy in wall attenuation measurement using a ROI technique, while measurements for walls of ≤1.0mm thickness are difficult. [Copyright &y& Elsevier]