The influence of motion-compensated reconstruction on coronary artery analysis for a dual-layer detector CT system: a dynamic phantom study.

OBJECTIVES: Cardiac motion artifacts hinder the assessment of coronary arteries in coronary computed tomography angiography (CCTA). We investigated the impact of motion compensation reconstruction (MCR) on motion artifacts in CCTA at various heart rates (HR) using a dynamic phantom. MATERIALS AND METHODS: An artificial hollow coronary artery (5-mm diameter lumen) filled with iodinated contrast agent (400 HU at 120 kVp), positioned centrally in an anthropomorphic chest phantom, was scanned using a dual-layer spectral detector CT. The artery was translated at constant horizontal velocities (0-80 mm/s, increment of 10 mm/s). For each velocity, five CCTA scans were repeated using a clinical protocol. Motion artifacts were quantified using the in-plane motion area. Regression analysis was performed to calculate the reduction in motion artifacts provided by MCR, by division of the slopes of non-MCR and MCR fitted lines. RESULTS: Reference mean (95% confidence interval) motion artifact area was 24.9 mm2 (23.8, 26.0). Without MCR, motion artifact areas for velocities exceeding 20 mm/s were significantly larger (up to 57.2 mm2 (40.1, 74.2)) than the reference. With MCR, no significant differences compared to the reference were shown for all velocities, except for 70 mm/s (29.0 mm2 (27.0, 31.0)). The slopes of the fitted data were 0.44 and 0.04 for standard and MCR reconstructions, respectively, resulting in an 11-time motion artifact reduction. CONCLUSION: MCR may improve CCTA assessment in patients by reducing coronary artery motion artifacts, especially in those with elevated HR who cannot receive beta blockers or do not attain the targeted HR. CLINICAL RELEVANCE STATEMENT: This vendor-specific motion compensation reconstruction may improve coronary computed tomography angiography assessment in patients by reduction of coronary artery motion artifacts, especially in those with elevated various heart rates (HR) who cannot receive beta blockers or do not attain the targeted HR. KEY POINTS: • Motion artifacts are known to hinder the assessment of coronary arteries on coronary CT angiography (CCTA), leading to more non-diagnostic scans. • This dynamic phantom study shows that motion compensation reconstruction (MCR) reduces motion artifacts at various velocities, which may help to decrease the number of non-diagnostic scans. • MCR in this study showed to reduce motion artifacts 11-fold.

Low Dose and Low Contrast Medium Coronary CT Angiography Using Dual-Layer Spectral Detector CT.

The aim of the present study was to investigate the performance of low keV mono-energetic reconstructions in spectral coronary computed tomography angiography (CCTA) using spectral detector CT (SDCT) with reduced contrast media and radiation dose.Sixty patients were randomly assigned to Groups A and B (both n = 30) to undergo CCTA on a dual-layer SDCT with tube voltage 120 kVp and 100 kVp (average tube current: 108.5 and 73.8 mAs, respectively), with contrast media volume of 36 mL used in both groups. The mono-energetic 40-80 keV and conventional 120 kVp images in Group A and conventional 100 kVp images in Group B were reconstructed. Quantitative and qualitative image quality (IQ) were evaluated in the aortic root and distal segments of the coronary arteries.The patient characteristics were not significantly different between the two groups (all P≥ 0.47), nor was the effective radiation dose (1.5 ± 0.3 and 1.4 ± 0.3 mSv, P = 0.20). The quantitative IQ in aorta and coronary arteries of mono-energetic 40-60 keV was superior to conventional 120 kVp and 100 kVp images (all P < 0.05). The noise in spectral images was lower compared to conventional images (all P < 0.01). The subjective IQ score of 40-50 keV images was not significantly different from that of 100 kVp images (P > 0.8).The mono-energetic 40-50 keV reconstructions from spectral CCTA using SDCT provide improved IQ compared to conventional techniques while facilitating reduced radiation dose and contrast media.

Discrepancies between coronary CT angiography and invasive coronary angiography with focus on culprit lesions which cause future cardiac events.

OBJECTIVES: To evaluate the clinical significance of discrepant lesions between coronary computed tomography angiography (CCTA) and invasive coronary angiography (ICA) in a longitudinal study. METHODS: In 220 patients with suspected coronary artery disease (CAD) who underwent both 256-row CCTA and ICA, the obstructive CAD (≥ 50% stenosis) on CCTA was compared with that on ICA as the reference standard. We analysed the causes of the discrepancy between CCTA and ICA. During a 40-month follow-up period, major adverse cardiac events (MACE) were assessed. RESULTS: Discordance between CCTA and ICA was observed in 121 of the 3166 coronary artery segments (3.8%). Common causes were calcification (45.9%) and positive remodelling (PR) (29.6%) in 83 false positive lesions, and noise (40.0%) and motion artefact (37.8%) in 38 false negative lesions. MACE occurred in seven lesions among the discrepant lesions; six among the 29 PR lesions (20.7%) and one among the 53 calcified lesions (1.9%). With respect to the prediction power of MACE in an intermediate stenosis, the CCTA-related value including PR was higher than the ICA-related value. CONCLUSIONS: PR was a frequent cause of MACE among the false positive lesions on CCTA. Therefore, the presence of PR on CCTA may suggest clinical significance, although it can be missed by ICA. KEY POINTS: • Compared to ICA, PR in CCTA may be cause of false positive lesion. • CCTA-related value including PR shows higher prediction power of MACE than ICA-related value. • PR reflects atherosclerotic burden that can be related to cardiac events. • PR in CCTA should be observed carefully, even if it is false positive.

Cardiac CT for planning redo cardiac surgery: effect of knowledge-based iterative model reconstruction on image quality.

OBJECTIVES: The purpose of this study was to investigate the effects of knowledge-based iterative model reconstruction (IMR) on image quality in cardiac CT performed for the planning of redo cardiac surgery by comparing IMR images with images reconstructed with filtered back-projection (FBP) and hybrid iterative reconstruction (HIR). METHODS: We studied 31 patients (23 men, 8 women; mean age 65.1 ± 16.5 years) referred for redo cardiac surgery who underwent cardiac CT. Paired image sets were created using three types of reconstruction: FBP, HIR, and IMR. Quantitative parameters including CT attenuation, image noise, and contrast-to-noise ratio (CNR) of each cardiovascular structure were calculated. The visual image quality--graininess, streak artefact, margin sharpness of each cardiovascular structure, and overall image quality--was scored on a five-point scale. RESULTS: The mean image noise of FBP, HIR, and IMR images was 58.3 ± 26.7, 36.0 ± 12.5, and 14.2 ± 5.5 HU, respectively; there were significant differences in all comparison combinations among the three methods. The CNR of IMR images was better than that of FBP and HIR images in all evaluated structures. The visual scores were significantly higher for IMR than for the other images in all evaluated parameters. CONCLUSIONS: IMR can provide significantly improved qualitative and quantitative image quality at in cardiac CT for planning of reoperative cardiac surgery. KEY POINTS: • Cardiac CT before redo surgery may mitigate increased risk • Iterative model reconstruction is the next generation in iterative reconstruction • Iterative model reconstruction improves the image quality in cardiac CT.

Diagnostic accuracy of low-dose 256-slice multi-detector coronary CT angiography using iterative reconstruction in patients with suspected coronary artery disease.

OBJECTIVES: To evaluate the accuracy of low-dose coronary CTA with iterative reconstruction (IR) in the diagnosis of coronary artery disease (CAD) in patients with suspected CAD. METHODS: Ninety-six patients with suspected CAD underwent low-dose prospective electrocardiogram-gated coronary CTA, with images reconstructed using IR. Image quality (IQ) of coronary segments were graded on a 4-point scale (4, excellent; 1, non-diagnostic). With invasive coronary angiography (ICA) considered the "gold standard", the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of coronary CTA were calculated on segment-, vessel- and patient-based levels. The patient data were divided into two groups (Agatston scores of ≥ 400 and <400). The differences in diagnostic performance between the two groups were tested. RESULTS: Diagnostic image quality was found in 98.1 % (1,232/1,256) of segments. The sensitivity, specificity, PPV, NPV and accuracy were 90.8 %, 95.3 %, 81.8 %, 97.8 % and 94.3 % (segment-based) and 97.2 %, 83.3 %, 94.6 %, 90.9 % and 93.8 % (patient-based). Significant differences between the two groups were seen in specificity, PPV and accuracy (92.1 % vs. 97.9 %, 76.0 % vs. 86.7 %, 91.7 % vs. 96.6 %, P < 0.05; segment-based). The average effective dose was 1.30 ± 0.15 mSv. CONCLUSION: Low-dose prospective coronary CTA with IR can acquire satisfactory image quality and show high diagnostic accuracy in patients with suspected CAD; however, blooming continues to pose a challenge in severely calcified segments. KEY POINTS: • Coronary artery disease (CAD) is increasingly investigated using coronary CTA. • The iterative reconstruction (IR) algorithm is promising in decreasing radiation doses. • Low-dose prospective coronary CTA with IR can acquire satisfactory image quality. • Low-dose prospective coronary CTA with IR can show high diagnostic accuracy.

Myocardium: dynamic versus single-shot CT perfusion imaging.

PURPOSE: To determine the diagnostic accuracy of dynamic computed tomographic (CT) perfusion imaging of the myocardium for the detection of hemodynamically relevant coronary artery stenosis compared with the accuracy of coronary angiography and fractional flow reserve (FFR) measurement. MATERIALS AND METHODS: This study was approved by the institutional review board and the Federal Radiation Safety Council (Bundesamt für Strahlenschutz). All patients provided written informed consent. Thirty-two consecutive patients in adenosine stress conditions underwent dynamic CT perfusion imaging (14 consecutive data sets) performed by using a 256-section scanner with an 8-cm detector and without table movement. Time to peak, area under the curve, upslope, and peak enhancement were determined after calculation of time-attenuation curves. In addition, myocardial blood flow (MBF) was determined quantitatively. Results were compared with those of coronary angiography and FFR measurement by using a receiver operating characteristic (ROC) analysis. In addition, threshold values based on the Youden index and sensitivity and specificity were calculated. RESULTS: Area under the ROC curve, sensitivity, and specificity, respectively, were 0.67, 41.4% (95% confidence interval [CI]: 23.5%, 61.1%), and 86.6% (95% CI: 76.0%, 93.7%) for time to peak; 0.74, 58.6% (95% CI: 38.9%, 76.5%), and 83.6% (95% CI: 72.5%, 91.5%) for area under the curve; 0.87, 82.8% (95% CI: 64.2%, 94.1%), and 88.1% (95% CI: 77.8%, 94.7%) for upslope; 0.83, 82.8% (95% CI: 64.2%, 94.1%), and 89.6% (95% CI: 79.6%, 95.7%) for peak enhancement; and 0.86, 75.9% (95% CI: 56.5%, 89.7%), and 100% (95% CI: 94.6%, 100%) for MBF. The thresholds determined by using the Youden index were 148.5 HU · sec for area under the curve, 12 seconds for time to peak, 2.5 HU/sec for upslope, 34 HU for peak enhancement, and 1.64 mL/g/min for MBF. CONCLUSION: The semiquantitative parameters upslope and peak enhancement and the quantitative parameter MBF showed similar high diagnostic accuracy. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13121441/-/DC1.

Improved bias and reproducibility of coronary artery calcification features using deconvolution.

Purpose: Our long-range goal is to improve whole-heart CT calcium scores by extracting quantitative features from individual calcifications. Here, we perform deconvolution to improve bias/reproducibility of small calcification assessments, which can be degraded at the normal CT calcium score image resolution. Approach: We analyzed features of individual calcifications on repeated standard (2.5 mm) and thin (1.25 mm) slice scans from QRM-Cardio phantom, cadaver hearts, and CARDIA study participants. Preprocessing to improve the resolution involved of Lucy-Richardson deconvolution with a measured point spread function (PSF) or three-dimensional blind deconvolution in which the PSF was iteratively optimized on high detail structures such as calcifications in images. Results: Using QRM with inserts having known mg-calcium, we determined that both blind and conventional deconvolution improved mass measurements nearly equally well on standard images. Further, deconvolved thin images gave an excellent recovery of actual mass scores, suggesting that such processing could be our gold standard. For CARDIA images, blind deconvolution greatly improved results on standard slices. Bias across 33 calcifications (without, with deconvolution) was (23%, 9%), (18%, 1%), and ( - 19 % , - 1 % ) for Agatston, volume, and mass scores, respectively. Reproducibility was (0.13, 0.10), (0.12, 0.08), and (0.11, 0.06), respectively. Mass scores were more reproducible than Agatston scores or volume scores. For many other calcification features, blind deconvolution improved reproducibility in 21 out of 24 features. Cadaver images showed similar improvements in bias/reproducibility and slightly better results with a measured PSF. Conclusions: Deconvolution improves bias and reproducibility of multiple features extracted from individual calcifications in CT calcium score exams. Blind deconvolution is useful for improving feature assessments of coronary calcification in archived datasets.

Quantitative analysis of late iodine enhancement using dual-layer spectral detector computed tomography: comparison with magnetic resonance imaging.

BACKGROUND: To evaluate the segmental myocardial extracellular volume (ECV) fraction and to define a threshold ECV value that can be used to distinguish positive late gadolinium enhancement (LGE) segments from negative myocardial segments using dual-layer spectral detector computed tomography (SDCT), with magnetic resonance imaging (MRI) as a reference. METHODS: Fifty-six subjects with cardiac disease or suspected cardiac disease, underwent both late iodine enhancement on CT (CT-LIE) scanning and late gadolinium enhancement on MRI (MRI-LGE) scanning. Each procedure occurred within a week of the other. Global and segmental ECVs of the left ventricle were measured by CT and MRI images. According to the location and pattern of delayed enhancement on MRI image, myocardial segments were classified into 3 groups: ischemic LGE segments (group 1), nonischemic LGE segments (group 2) and negative LGE segments (group 3). The correlation and agreement between CT-ECV and MRI-ECV were compared on a per-segment basis. Receiver operating characteristic (ROC) curve analysis was performed to establish a threshold for LIE detection. RESULTS: Among the 56 patients, 896 segments were analyzed, and of these, 73 segments were in group 1, 229 segments were in group 2, and 594 segments were in group 3. In segmental analysis, CT-ECV in group 3 (27.0%; 24.9-28.9%) was significantly lower than that in group 1 (33.2%; 30.7-36.3%) and group 2 (34.9%; 32.3-39.8%; all P<0.001). Good correlations were seen between CT-ECV and MRI-ECV for all groups (group 1: r=0.920; group 2: r=0.936; group 3: r=0.799; all P<0.001). Bland-Altman analysis between CT-ECV and MRI-ECV showed a small bias in all 3 groups (group 1: -2.1%, 95% limits of agreement -11.3-7.1%; group 2: -0.6%, 95% limits of agreement -13.1-11.9%; group 3: 1.0%, 95% limits of agreement -12.7-14.7%). CT-ECV could differentiate between LGE-positive and LGE-negative segments with 83.1% sensitivity and 93.3% specificity at a cutoff of 31%. CONCLUSIONS: ECV values derived from CT imaging showed good correlation and agreement with MR imaging findings, and CT-ECV provided high diagnostic accuracy for discriminating between LGE-positive and LGE-negative segments. Thus, cardiac CT imaging might be a suitable noninvasive imaging technique for myocardial ECV quantification.

Performance of an Artificial Intelligence-based Application for the Detection of Plaque-based Stenosis on Monoenergetic Coronary CT Angiography: Validation by Invasive Coronary Angiography.

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.

Evaluation of image quality and radiation dose at prospective ECG-triggered axial 256-slice multi-detector CT in infants with congenital heart disease.

BACKGROUND: There are a limited number of reports on the technical and clinical feasibility of prospective electrocardiogram (ECG)-gated multi-detector computed tomography (MDCT) in infants with congenital heart disease (CHD). OBJECTIVE: To evaluate image quality and radiation dose at weight-based low-dose prospectively gated 256-slice MDCT angiography in infants with CHD. MATERIALS AND METHODS: From November 2009 to February 2010, 64 consecutive infants with CHD referred for pre-operative or post-operative CT were included. All were scanned on a 256-slice MDCT system utilizing a low-dose protocol (80 kVp and 60-120 mAs depending on weight: 60 mAs for ≤ 3 kg, 80 mAs for 3.1-6 kg, 100 mAs for 6.1-10 kg, 120 mAs for 10.1-15 kg). RESULTS: No serious adverse events were recorded. A total of 174 cardiac deformities, confirmed by surgery or heart catheterization, were studied. The sensitivity of MDCT for cardiac deformities was 97.1%; specificity, 99.4%; accuracy, 95.9%. The mean heart rate during scan was 136.7 ± 14.9/min (range, 91-160) with a corresponding heart rate variability of 2.8 ± 2.2/min (range, 0-8). Mean scan length was 115.3 ± 11.7 mm (range, 93.6-143.3). Mean volume CT dose index, mean dose-length product and effective dose were 2.1 ± 0.4 mGy (range, 1.5-2.8), 24.7 ± 5.9 mGy·cm (range, 14.7-35.8) and 1.6 ± 0.3 mSv (range, 1.1-2.5), respectively. Diagnostic-quality images were achieved in all cases. Satisfactory diagnostic quality for visualization of all/proximal/distal coronary artery segments was achieved in 88.4/98.8/80.0% of the scans. CONCLUSION: Low-dose prospectively gated axial 256-slice CT angiography is a valuable tool in the routine clinical evaluation of infants with CHD, providing a comprehensive three-dimensional evaluation of the cardiac anatomy, including the coronary arteries.

Incremental improvement of diagnostic performance of coronary CT angiography for the assessment of coronary stenosis in the presence of calcium using a dual-layer spectral detector CT: validation by invasive coronary angiography.

To investigate value of spectral reconstructions for the quantification of coronary stenosis in the presence of calcified or partially calcified plaques using a dual-layer spectral detector CT (SDCT). Seventy-two consecutive patients were retrospectively enrolled. Conventional 120 kVp images, eight virtual monoenergetic images (VMI) (70 to 140 keV), the effective atomic number (Z effective) and iodine no water images were reconstructed. Invasive coronary angiography was used as the reference standard. Parallel and serial testing were used to assess the incremental diagnostic value of Z effective and iodine no water images to the best VMI series. 122 coronary lesions of 72 patients (49 men and 23 women; 63.7 ± 10.2 years) were enrolled in analysis. Reconstruction at 100 keV yielded optimal diagnostic performance, the sensitivity, specificity, PPV, NPV and diagnostic accuracy to identify stenosis ≥ 50% or ≥ 70% were 84%, 70%, 80%, 76%, 79% and 78%, 98%, 93%, 91%, 92%, respectively. A serial combination (100 keV VMI followed by Z effective images) resulted in an improved specificity (from 70 to 80%) with a moderate loss of sensitivity (81% from 84%) in identifying ≥ 50% stenosis (P = 0.021). For patients with high Agatston score, this combination could further reduce false positive cases and improve diagnostic accuracy. 100 keV VMI provide optimal diagnostic performance for the detection of coronary stenosis in the presence of calcified or partially calcified plaques using a dual-layer SDCT, with further improvements obtained with the combined use of Z effective images.

Comparison of automated beam hardening correction (ABHC) algorithms for myocardial perfusion imaging using computed tomography.

PURPOSE: Myocardial perfusion imaging using computed tomography (MPI-CT) and coronary CT angiography (CTA) have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening can prevent accurate blood flow estimation in dynamic MPI-CT and can create artifacts that resemble flow deficits in single-shot MPI-CT. In this work, we compare four automatic beam hardening correction algorithms (ABHCs) applied to CT images, for their ability to produce accurate single images of contrast and accurate MPI flow maps using images from conventional CT systems, without energy sensitivity. METHODS: Previously, we reported a method, herein called ABHC-1, where we iteratively optimized a cost function sensitive to beam hardening artifacts in MPI-CT images and used a low order polynomial correction on projections of segmentation-processed CT images. Here, we report results from two new algorithms with higher order polynomial corrections, ABHC-2 and ABHC-3 (with three and seven free parameters, respectively), having potentially better correction but likely reduced estimability. Additionally, we compared results to an algorithm reported by others in the literature (ABHC-NH). Comparisons were made on a digital static phantom with simulated water, bone, and iodine regions; on a digital dynamic anthropomorphic phantom, with simulated blood flow; and on preclinical porcine experiments. We obtained CT images on a prototype spectral detector CT (Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To test these methods' parameter optimization sensitivity to noise, we evaluated results on images obtained using different mAs. RESULTS: In images of the static phantom, ABHC-2 reduced beam hardening artifacts better than our previous ABHC-1 algorithm, giving artifacts smaller than 1.8 HU, even in the presence of high noise which should affect parameter optimization. Taken together, the quality of static phantom results ordered ABHC-2> ABHC-3> ABHC-1>> ABHC-NH. In an anthropomorphic MPI-CT simulator with homogeneous myocardial blood flow of 100 ml⋅min-1 ⋅100 g-1 , blood flow estimation results were 122 ± 24 (FBP), 135 ± 24 (ABHC-NH), 104 ± 14 (ABHC-1), 100 ± 12 (ABHC-2), and 108 ± 18 (ABHC-3) ml⋅min-1 ⋅100 g-1 , showing ABHC-2 as a clear winner. Visual and quantitative evaluations showed much improved homogeneity of myocardial flow with ABHC-2, nearly eliminating substantial artifacts in uncorrected flow maps which could be misconstrued as flow deficits. ABHC-2 performed universally better than ABHC-1, ABHC-3, and ABHC-NH in simulations with different acquisitions (varying noise and kVp values). In the presence of a simulated flow deficit, all ABHC methods retained the flow deficit, and ABHC-2 gave the most accurate flow ratio and homogeneity. ABHC-3 corrected phantom flow values were slightly better than ABHC-2, in noiseless images, suggesting that reduced quality in noisy images was due to reduced estimability. In an experiment with a pig expected to have uniform flow, ABHC-2 applied to conventional images improved flow maps to compare favorably to those from 70keV images. CONCLUSION: The automated algorithm can be used with different parametric BH correction models. ABHC-2 improved MPI-CT blood flow estimation as compared to other approaches and was robust to noisy images. In simulation and preclinical experiments, ABHC-2 gave results approaching gold standard 70 keV measurements.

Improved visualization of the coronary arteries using motion correction during vasodilator stress CT myocardial perfusion imaging.

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.

Diagnostic performance and image quality of iterative model-based reconstruction of coronary CT angiography using 100 kVp for heavily calcified coronary vessels.

OBJECTIVES: To evaluate the diagnostic performance and image quality of an iterative model-based reconstruction (IMR) using a 100-kVp protocol for the assessment of heavily calcified coronary vessels, compared to those of filtered back projection (FBP) and hybrid iterative technique (iDose4), and also compared to those of IMR with standard 120 kVp protocol. METHODS: Among patients with Agatston scores ≥ 400 who had undergone both coronary CT angiography (CCTA) and invasive coronary angiography (ICA), age- and sex-matched patients with body mass index < 30 were retrospectively enrolled from CCTA with low-kVp protocol (100 kVp, n = 30) and with standard-kVp protocol (120 kVp, n = 30). Image data were all reconstructed with FBP, iDose4, and IMR. In each dataset, the objective and subjective image quality, and diagnostic accuracy (> 50% in luminal reduction as compared with ICA) were assessed. RESULTS: IMR showed better objective and subjective image quality than FBP and iDose4 in both 100 kVp and 120 kVp groups (all p < 0.05). IMR showed a significantly improved all diagnostic performance compared with FBP (p < 0.05). Compared with iDose4, IMR significantly improved positive predictive value (85.0% vs. 80.5%; p < 0.05). There was no significant difference in image quality and diagnostic performance using IMR between the 100 kVp and 120 kVp groups. CONCLUSIONS: 100 kVp IMR may be useful for the assessment of heavily calcified coronary vessels, providing better diagnostic performance than FBP or iDose4 at the same dose, while maintaining similar diagnostic accuracy to 120 kVp IMR.

Calibration-free beam hardening correction for myocardial perfusion imaging using CT.

PURPOSE: Computed tomography myocardial perfusion imaging (CT-MPI) and coronary CTA have the potential to make CT an ideal noninvasive imaging gatekeeper exam for invasive coronary angiography. However, beam hardening (BH) artifacts prevent accurate blood flow calculation in CT-MPI. BH correction methods require either energy-sensitive CT, not widely available, or typically, a calibration-based method in conventional CT. We propose a calibration-free, automatic BH correction (ABHC) method suitable for CT-MPI and evaluate its ability to reduce BH artifacts in single "static-perfusion" images and to create accurate myocardial blood flow (MBF) in dynamic CT-MPI. METHODS: In the algorithm, we used input CT DICOM images and iteratively optimized parameters in a polynomial BH correction until a BH-sensitive cost function was minimized on output images. An input image was segmented into a soft tissue image and a highly attenuating material (HAM) image containing bones and regions of high iodine concentrations, using mean HU and temporal enhancement properties. We forward projected HAM, corrected projection values according to a polynomial correction, and reconstructed a correction image to obtain the current iteration's BH corrected image. The cost function was sensitive to BH streak artifacts and cupping. We evaluated the algorithm on simulated CT and physical phantom images, and on preclinical porcine with optional coronary obstruction and clinical CT-MPI data. Assessments included measures of BH artifact in single images as well as MBF estimates. We obtained CT images on a prototype spectral detector CT (SDCT, Philips Healthcare) scanner that provided both conventional and virtual keV images, allowing us to quantitatively compare corrected CT images to virtual keV images. To stress test the method, we evaluated results on images from a different scanner (iCT, Philips Healthcare) and different kVp values. RESULTS: In a CT-simulated digital phantom consisting of water with iodine cylinder insets, BH streak artifacts between simulated iodine inserts were reduced from 13 ± 2 to 0 ± 1 HU. In a similar physical phantom having higher iodine concentrations, BH streak artifacts were reduced from 48 ± 6 to 1 ± 5 HU and cupping was reduced by 86%, from 248 to 23 HU. In preclinical CT-MPI images without coronary obstruction, BH artifact was reduced from 24 ± 6 HU to less than 5 ± 4 HU at peak enhancement. Standard deviation across different regions of interest (ROI) along the myocardium was reduced from 13.26 to 6.86 HU for ABHC, comparing favorably to measurements in the corresponding virtual keV image. Corrections greatly reduced variations in preclinical MBF maps as obtained in normal animals without obstruction (FFR = 1). Coefficients of variations were 22% (conventional CT), 9% (ABHC), and 5% (virtual keV). Moreover, variations in flow tended to be localized after ABHC, giving result which would not be confused with a flow deficit in a coronary vessel territory. CONCLUSION: The automated algorithm can be used to reduce BH artifact in conventional CT and improve CT-MPI accuracy particularly by removing regions of reduced estimated flow which might be misinterpreted as flow deficits.

A functionally personalized boundary condition model to improve estimates of fractional flow reserve with CT (CT-FFR).

PURPOSE: The purpose of this study is to develop and evaluate a functionally personalized boundary condition (BC) model for estimating the fractional flow reserve (FFR) from coronary computed tomography angiography (CCTA) using flow simulation (CT-FFR). MATERIALS AND METHODS: The CCTA data of 90 subjects with subsequent invasive FFR in 123 lesions within 21 days (range: 0-83) were retrospectively collected. We developed a functionally personalized BC model accounting specifically for the coronary microvascular resistance dependency on the coronary outlets pressure suggested by several physiological studies. We used the proposed model to estimate the hemodynamic significance of coronary lesions with an open-loop physics-based flow simulation. We generated three-dimensional (3D) coronary tree geometries using automatic software and corrected manually where required. We evaluated the improvement in CT-FFR estimates achieved using a functionally personalized BC model over anatomically personalized BC model using k-fold cross-validation. RESULTS: The functionally personalized BC model slightly improved CT-FFR specificity in determining hemodynamic significance of lesions with intermediate diameter stenosis (30%-70%, N = 72), compared to the anatomically personalized model lesions with invasive FFR measurements as the reference (sensitivity/specificity: 0.882/0.79 vs 0.882/0.763). For the entire set of 123 coronary lesions, the functionally personalized BC model improved only the area under the curve (AUC) but not the sensitivity/specificity in determining the hemodynamic significance of lesions, compared to the anatomically personalized model (AUC: 0.884 vs 0.875, sensitivity/specificity: 0.848/0.805). CONCLUSION: The functionally personalized BC model has the potential to improve the quality of CT-FFR estimates compared to an anatomically personalized BC model.

The role of acquisition and quantification methods in myocardial blood flow estimability for myocardial perfusion imaging CT.

In this work, we clarified the role of acquisition parameters and quantification methods in myocardial blood flow (MBF) estimability for myocardial perfusion imaging using CT (MPI-CT). We used a physiologic model with a CT simulator to generate time-attenuation curves across a range of imaging conditions, i.e. tube current-time product, imaging duration, and temporal sampling, and physiologic conditions, i.e. MBF and arterial input function width. We assessed MBF estimability by precision (interquartile range of MBF estimates) and bias (difference between median MBF estimate and reference MBF) for multiple quantification methods. Methods included: six existing model-based deconvolution models, such as the plug-flow tissue uptake model (PTU), Fermi function model, and single-compartment model (SCM); two proposed robust physiologic models (RPM1, RPM2); model-independent singular value decomposition with Tikhonov regularization determined by the L-curve criterion (LSVD); and maximum upslope (MUP). Simulations show that MBF estimability is most affected by changes in imaging duration for model-based methods and by changes in tube current-time product and sampling interval for model-independent methods. Models with three parameters, i.e. RPM1, RPM2, and SCM, gave least biased and most precise MBF estimates. The average relative bias (precision) for RPM1, RPM2, and SCM was ⩽11% (⩽10%) and the models produced high-quality MBF maps in CT simulated phantom data as well as in a porcine model of coronary artery stenosis. In terms of precision, the methods ranked best-to-worst are: RPM1 > RPM2 > Fermi > SCM > LSVD > MUP [Formula: see text] other methods. In terms of bias, the models ranked best-to-worst are: SCM > RPM2 > RPM1 > PTU > LSVD [Formula: see text] other methods. Models with four or more parameters, particularly five-parameter models, had very poor precision (as much as 310% uncertainty) and/or significant bias (as much as 493%) and were sensitive to parameter initialization, thus suggesting the presence of multiple local minima. For improved estimates of MBF from MPI-CT, it is recommended to use reduced models that incorporate prior knowledge of physiology and contrast agent uptake, such as the proposed RPM1 and RPM2 models.

Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

PURPOSE: The goal of this study was to assess the potential added benefit of accounting for partial volume effects (PVE) in an automatic coronary lumen segmentation algorithm that is used to determine the hemodynamic significance of a coronary artery stenosis from coronary computed tomography angiography (CCTA). MATERIALS AND METHODS: Two sets of data were used in our work: (a) multivendor CCTA datasets of 18 subjects from the MICCAI 2012 challenge with automatically generated centerlines and 3 reference segmentations of 78 coronary segments and (b) additional CCTA datasets of 97 subjects with 132 coronary lesions that had invasive reference standard FFR measurements. We extracted the coronary artery centerlines for the 97 datasets by an automated software program followed by manual correction if required. An automatic machine-learning-based algorithm segmented the coronary tree with and without accounting for the PVE. We obtained CCTA-based FFR measurements using a flow simulation in the coronary trees that were generated by the automatic algorithm with and without accounting for PVE. We assessed the potential added value of PVE integration as a part of the automatic coronary lumen segmentation algorithm by means of segmentation accuracy using the MICCAI 2012 challenge framework and by means of flow simulation overall accuracy, sensitivity, specificity, negative and positive predictive values, and the receiver operated characteristic (ROC) area under the curve. We also evaluated the potential benefit of accounting for PVE in automatic segmentation for flow simulation for lesions that were diagnosed as obstructive based on CCTA which could have indicated a need for an invasive exam and revascularization. RESULTS: Our segmentation algorithm improves the maximal surface distance error by ~39% compared to previously published method on the 18 datasets from the MICCAI 2012 challenge with comparable Dice and mean surface distance. Results with and without accounting for PVE were comparable. In contrast, integrating PVE analysis into an automatic coronary lumen segmentation algorithm improved the flow simulation specificity from 0.6 to 0.68 with the same sensitivity of 0.83. Also, accounting for PVE improved the area under the ROC curve for detecting hemodynamically significant CAD from 0.76 to 0.8 compared to automatic segmentation without PVE analysis with invasive FFR threshold of 0.8 as the reference standard. Accounting for PVE in flow simulation to support the detection of hemodynamic significant disease in CCTA-based obstructive lesions improved specificity from 0.51 to 0.73 with same sensitivity of 0.83 and the area under the curve from 0.69 to 0.79. The improvement in the AUC was statistically significant (N = 76, Delong's test, P = 0.012). CONCLUSION: Accounting for the partial volume effects in automatic coronary lumen segmentation algorithms has the potential to improve the accuracy of CCTA-based hemodynamic assessment of coronary artery lesions.

Improved image quality with simultaneously reduced radiation exposure: Knowledge-based iterative model reconstruction algorithms for coronary CT angiography in a clinical setting.

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/m2, II: <28.0 kg/m2, III: <30.0 kg/m2, IV: ≥30.0 kg/m2) low dose (LD, I: 100kVp/75 mAs, II: 100kVp/100 mAs, III: 100kVp/150 mAs, IV: 120kVp/150 mAs, n = 20) or ultra-low dose (ULD, I: 100kVp/50 mAs, II: 100kVp/75 mAs, III: 100kVp/100 mAs, IV: 120kVp/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.

Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p < 0.05). The use of IMR enables significant improvement of image quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR.