Automatic phase determination for retrospectively gated cardiac CT

Image quality of automatic coronary CT angiography reconstruction for patients with HR ≥ 75 bpm using an AI-assisted 16-cm z-coverage CT scanner

Background

Coronary CT angiography (CCTA) is a complicated CT exam in comparison to other CT protocols. Exam success highly depends on image assessment of experienced radiologist and the procedure is often time-consuming. This study aims to evaluate feasibility of automatic CCTA reconstruction in 0.25 s rotation time, 16 cm coverage CT scanner with best phase selection and AI-assisted motion correction.

Methods

CCTA exams of 90 patients with heart rates higher than 75 bpm were included in this study. Two image series were reconstructed—one at automatically selected phase and another with additional motion correction. All reconstructions were performed without manual interaction of radiologist. A four-point Likert scale rating system was used to evaluate the image quality of coronary artery segment by two experienced radiologists, according to the 18-segment model. Analysis was done on per-segment basis.

Results

Total 1194 out of the 1620 segments were identified for quality evaluation in 90 patients. After automatic best phase selection, 1172 segments (98.3%) were rated as having diagnostic image quality (scores 2–4) and the average score is 3.64 ± 0.55. When motion corrections were applied, diagnostic segment number increases to 1192 (99.8%) and the average score is 3.85 ± 0.37.

Conclusions

With the help of 0.25 s rotation speed, 16-cm z-coverage and AI-assisted motion correction algorithm, CCTA exam reconstruction could be performed with minimum radiologist involvement and still meet image quality requirement.

Restricting motion effects in CT coronary angiography

OBJECTIVE

Evaluation of coronary CT image blur using multi segment reconstruction algorithm.

METHODS

Cardiac motion was simulated in a Catphan. CT coronary angiography was performed using 320 × 0.5 mm detector array and 275 ms gantry rotation. 1, 2 and 3 segment reconstruction algorithm, three heart rates (60, 80 and 100bpm), two peak displacements (4, 8 mm) and three cardiac phases (55, 35, 75%) were used. Wilcoxon test compared image blur from the different reconstruction algorithms.

RESULTS

Image blur for 1, 2 and 3 segments in: 60 bpm, 75% R-R interval and 8 mm peak displacement: 0.714, 0.588, 0.571 mm (1.18, 0.6, 0.4 mm displacement) 80 bpm, 35% R-R interval and 8 mm peak displacement: 0.869, 0.606, 0.606 mm (1.57, 0.79,0.52 mm displacement) 100 bpm, 35% R-R interval and 4 mm peak displacement: 0.645, 0.588, 0.571 mm (0.98, 0.49, 0.33 mm displacement). The median image blur overall for 1 and 2 segments was 0.714 mm and 0.588 mm respectively (p < 0.0001).

CONCLUSION

Two-segment reconstruction significantly reduces image blur.

ADVANCES IN KNOWLEDGE

Multisegment reconstruction algorithms during CT coronary angiography are a useful method to reduce image blur, improve visualization of the coronary artery wall and help the early detection of the plaque.

Automated quantification and evaluation of motion artifact on coronary CT angiography images

PURPOSE

This study developed and validated a Motion Artifact Quantification algorithm to automatically quantify the severity of motion artifacts on coronary computed tomography angiography (CCTA) images. The algorithm was then used to develop a Motion IQ Decision method to automatically identify whether a CCTA dataset is of sufficient diagnostic image quality or requires further correction.

METHOD

The developed Motion Artifact Quantification algorithm includes steps to identify the right coronary artery (RCA) regions of interest (ROIs), segment vessel and shading artifacts, and to calculate the motion artifact score (MAS) metric. The segmentation algorithms were verified against ground-truth manual segmentations. The segmentation algorithms were also verified by comparing and analyzing the MAS calculated from ground-truth segmentations and the algorithm-generated segmentations. The Motion IQ Decision algorithm first identifies slices with unsatisfactory image quality using a MAS threshold. The algorithm then uses an artifact-length threshold to determine whether the degraded vessel segment is large enough to cause the dataset to be nondiagnostic. An observer study on 30 clinical CCTA datasets was performed to obtain the ground-truth decisions of whether the datasets were of sufficient image quality. A five-fold cross-validation was used to identify the thresholds and to evaluate the Motion IQ Decision algorithm.

RESULTS

The automated segmentation algorithms in the Motion Artifact Quantification algorithm resulted in Dice coefficients of 0.84 for the segmented vessel regions and 0.75 for the segmented shading artifact regions. The MAS calculated using the automated algorithm was within 10% of the values obtained using ground-truth segmentations. The MAS threshold and artifact-length thresholds were determined by the ROC analysis to be 0.6 and 6.25 mm by all folds. The Motion IQ Decision algorithm demonstrated 100% sensitivity, 66.7% ± 27.9% specificity, and a total accuracy of 86.7% ± 12.5% for identifying datasets in which the RCA required correction. The Motion IQ Decision algorithm demonstrated 91.3% sensitivity, 71.4% specificity, and a total accuracy of 86.7% for identifying CCTA datasets that need correction for any of the three main vessels.

CONCLUSION

The Motion Artifact Quantification algorithm calculated accurate (<10% error) motion artifact scores using the automated segmentation methods. The developed algorithms demonstrated high sensitivity (91.3%) and specificity (71.4%) in identifying datasets of insufficient image quality. The developed algorithms for automatically quantifying motion artifact severity may be useful for comparing acquisition techniques, improving best-phase selection algorithms, and evaluating motion compensation techniques.

Evaluation of motion artifact metrics for coronary CT angiography

PURPOSE

This study quantified the performance of coronary artery motion artifact metrics relative to human observer ratings. Motion artifact metrics have been used as part of motion correction and best-phase selection algorithms for Coronary Computed Tomography Angiography (CCTA). However, the lack of ground truth makes it difficult to validate how well the metrics quantify the level of motion artifact. This study investigated five motion artifact metrics, including two novel metrics, using a dynamic phantom, clinical CCTA images, and an observer study that provided ground-truth motion artifact scores from a series of pairwise comparisons.

METHOD

Five motion artifact metrics were calculated for the coronary artery regions on both phantom and clinical CCTA images: positivity, entropy, normalized circularity, Fold Overlap Ratio (FOR), and Low-Intensity Region Score (LIRS). CT images were acquired of a dynamic cardiac phantom that simulated cardiac motion and contained six iodine-filled vessels of varying diameter and with regions of soft plaque and calcifications. Scans were repeated with different gantry start angles. Images were reconstructed at five phases of the motion cycle. Clinical images were acquired from 14 CCTA exams with patient heart rates ranging from 52 to 82 bpm. The vessel and shading artifacts were manually segmented by three readers and combined to create ground-truth artifact regions. Motion artifact levels were also assessed by readers using a pairwise comparison method to establish a ground-truth reader score. The Kendall's Tau coefficients were calculated to evaluate the statistical agreement in ranking between the motion artifacts metrics and reader scores. Linear regression between the reader scores and the metrics was also performed.

RESULTS

On phantom images, the Kendall's Tau coefficients of the five motion artifact metrics were 0.50 (normalized circularity), 0.35 (entropy), 0.82 (positivity), 0.77 (FOR), 0.77(LIRS), where higher Kendall's Tau signifies higher agreement. The FOR, LIRS, and transformed positivity (the fourth root of the positivity) were further evaluated in the study of clinical images. The Kendall's Tau coefficients of the selected metrics were 0.59 (FOR), 0.53 (LIRS), and 0.21 (Transformed positivity). In the study of clinical data, a Motion Artifact Score, defined as the product of FOR and LIRS metrics, further improved agreement with reader scores, with a Kendall's Tau coefficient of 0.65.

CONCLUSION

The metrics of FOR, LIRS, and the product of the two metrics provided the highest agreement in motion artifact ranking when compared to the readers, and the highest linear correlation to the reader scores. The validated motion artifact metrics may be useful for developing and evaluating methods to reduce motion in Coronary Computed Tomography Angiography (CCTA) images.

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

PURPOSE

Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available.

METHODS

An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale.

RESULTS

There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase.

CONCLUSIONS

The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

Automatic determination of differential coronary artery motion minima for cardiac computed tomography optimal phase selection

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.

Seismocardiography-Based Detection of Cardiac Quiescence

Cardiac-computed tomography angiography (CTA) is a minimally invasive imaging technology for characterizing coronary arteries. A fundamental limitation of CTA imaging is cardiac movement, which can cause artifacts and reduce the quality of the obtained images. To mitigate this problem, current approaches involve gating the image based on the electrocardiogram (ECG) to predict the timing of quiescent periods of the cardiac cycle. This paper focuses on developing a foundation for using a mechanical alternative to the ECG for finding these quiescent periods: the seismocardiogram (SCG). SCG was used to determine beat-by-beat systolic and diastolic quiescent periods of the cardiac cycle for nine healthy subjects, and 11 subjects with various cardiovascular diseases. To reduce noise in the SCG, and quantify these quiescent periods, a Kalman filter was designed to extract the velocity of chest wall movement from the recorded SCG signals. The average systolic and diastolic quiescent periods were centered at 29% and 76% for the healthy subjects, and 33% and 79% for subjects with cardiovascular disease. Both inter and intrasubject variability in the quiescent phases were observed compared to ECG-predicted phases, suggesting that the ECG may be a suboptimal modality for predicting quiescence, and that the SCG provides complementary data to the ECG.

Image registration and analysis for quantitative myocardial perfusion: application to dynamic circular cardiac CT

Large area detector computed tomography systems with fast rotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively, ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce x-ray dose and limit motion artefacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occur due to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image-based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in this contribution. After circular cone-beam CT reconstruction of cardiac volumes covering large areas of the myocardial tissue, the complete series is aligned with respect to a chosen reference volume. The results of the registration process and the perfusion analysis with and without registration are evaluated quantitatively in this paper. The spatial alignment leads to improved quantification of myocardial perfusion for three different pig data sets.

Respiratory phase-correlated micro-CT imaging of free-breathing rodents

We provide a dedicated phase-correlated imaging procedure for respiratory gating in micro-CT imaging with automatic detection of the optimal data window providing the least amount of motion blurring. A rawdata-based motion function (kymogram) was used for synchronization purposes and for identification of the optimal data window used for phase-correlated image reconstruction. Measurements were performed on a dual-source micro-CT scanner. Projection data were acquired over ten rotations for multi-segment phase-correlated reconstruction. Visual assessment was performed on datasets of ten free-breathing subjects. The kymogram approach provided a reliable synchronization signal for phase-correlated image reconstruction. Also, it allowed for the identification of phase intervals of increased and decreased motion and the corresponding detection of the optimal reconstruction phase. Phase-correlated images showed a strong improvement with respect to motion blurring compared to standard image reconstruction. A reconstruction for the calculated optimal data window provided the least amount of motion blurring and even allowed for the assessment of small structures in the lung. The dedicated retrospective phase-correlated image reconstruction procedure for respiratory gating is a feasible approach for motion-free imaging. A subject-specific optimal reconstruction phase can minimize motion blurring and further improve image quality.

Low-dose CT coronary angiography using prospective ECG-triggering: impact of mean heart rate and heart rate variability on image quality

RATIONALE AND OBJECTIVES

The aim of this study was to evaluate the effect of mean heart rate (HR) and HR variability on image quality in low-dose computed tomographic coronary angiography (CTCA) using prospective electrocardiographic (ECG) triggering.

MATERIALS AND METHODS

One hundred thirty-six consecutive patients were scheduled for low-dose CTCA using prospective ECG triggering. The image quality of all coronary segments was rated on a 5-point scale by two independent readers (scores of 1-3 were considered diagnostic, and scores of 4 and 5 were considered nondiagnostic). Intravenous beta blockers were administered targeting HR < 65 beats/min before scanning, but not if HR increased during scanning.

RESULTS

After the exclusion of seven patients because of arrhythmia (n = 4) or mean HRs > 65 beats/min despite using beta blockers (n = 3), 129 patients underwent computed tomographic scanning. The estimated mean effective radiation dose was 2.2 +/- 0.7 mSv (range, 1.1-3.5). The mean HR during scanning was 58.4 +/- 6.6 beats/min (range, 44.2-80.1), with a variability of 1.6 +/- 1.0 beats/min (range, 0.2-5.3). Mean HR (r = 0.49, P < .001) but not mean HR variability (r = 0.14) was related to image quality. Nondiagnostic image quality on CTCA was found in 5% of the coronary segments in 21 of 129 patients. However, on receiver-operating characteristic analysis, a cutoff HR of 62 beats/min was determined, below which nondiagnostic segments were significantly less frequent (2% vs 14%, P < .001).

CONCLUSION

Prospective triggering allows low-dose CTCA but requires a low HR. Because a low HR offers a prolonged diastole, widening the optimal phase for scanning, HR variability seems to have a negligible impact on image quality.

Improvement of cardiac CT reconstruction using local motion vector fields

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

Computerized assessment of motion-contaminated calcified plaques in cardiac multidetector CT

An automated method for evaluating the image quality of calcified plaques with respect to motion artifacts in noncontrast-enhanced cardiac computed tomography (CT) images is introduced. This method involves using linear regression (LR) and artificial neural network (ANN) regression models for predicting two patient-specific, region-of-interest-specific, reconstruction-specific and temporal phase-specific image quality indices. The first is a plaque motion index, which is derived from the actual trajectory of the calcified plaque and is represented on a continuous scale. The second is an assessability index, which reflects the degree to which a calcified plaque is affected by motion artifacts, and is represented on an ordinal five-point scale. Two sets of assessability indices were provided independently by two radiologists experienced in evaluating cardiac CT images. Inputs for the regression models were selected from 12 features characterizing the dynamic, morphological, and intensity-based properties of the calcified plaques. Whereas LR-velocity (LR-V) used only a single feature (three-dimensional velocity), the LR-multiple (LR-M) and ANN regression models used the same subset of these 12 features selected through stepwise regression. The regression models were parameterized and evaluated using a database of simulated calcified plaque images from the dynamic NCAT phantom involving nine heart rate/multi-sector gating combinations and 40 cardiac phases covering two cardiac cycles. Six calcified plaques were used for the plaque motion indices and three calcified plaques were used for both sets of assessability indices. In one configuration, images from the second cardiac cycle were used for feature selection and regression model parameterization, whereas images from the first cardiac cycle were used for testing. With this configuration, repeated measures concordance correlation coefficients (CCCs) and associated 95% confidence intervals for the LR-V, LR-M, and ANN were 0.817 [0.785, 0.848], 0.894 [0.869, 0.916], and 0.917 [0.892, 0.936] for the plaque motion indices. For the two sets of assess-ability indices, CCC values for the ANN model were 0.843 [0.791, 0.877] and 0.793 [0.747, 0.828]. These two CCC values were statistically greater than the CCC value of 0.689 [0.648, 0.727], which was obtained by comparing the two sets of assessability indices with each other. These preliminary results suggest that the variabilities of assessability indices provided by regression models can lie within the variabilities of the indices assigned by independent observers. Thus, the potential exists for using regression models and assessability indices for determining optimal phases for cardiac CT image interpretation.

Validation of a raw data-based synchronization signal (kymogram) for phase-correlated cardiac image reconstruction

Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation of the ECG and the kymogram was assessed. Additionally, we performed a double-blinded comparison of ECG-based and kymogram-based phase-correlated images. The two synchronization signals showed good correlation indicated by a mean difference in the detected heart rate of negligible 0.2 bpm. The mean image quality score was 2.0 points for kymogram-correlated images and 2.3 points for ECG-correlated images, respectively (3: best; 0: worst). The kymogram and the ECG provided images adequate for diagnosis for 93 and 97 patients, respectively. For 50% of the datasets the kymogram provided an equivalent or even higher image quality compared with the ECG signal. We conclude that an acceptable image quality can be assured in most cases by the kymogram. Improvements of image quality by the kymogram function were observed in a noticeable number of cases. The kymogram can serve as a backup solution when an ECG is not available or lacking in quality.

Coronary artery motion and cardiac phases: dependency on heart rate -- implications for CT image reconstruction

This study had institutional review board approval; written informed consent was obtained. The purpose was to prospectively determine the heart rate (HR) dependency of three-dimensional (3D) coronary artery motion by incorporating into analysis the durations of systole and diastole. Thirty patients (seven women, 23 men; mean age, 56.6 years +/- 12.7 [standard deviation]; HR: 45-100 beats per minute) underwent electrocardiographically gated 64-section computed tomographic (CT) coronary angiography to determine coronary motion velocities at bifurcation points. Significance of velocity differences (P < .05) was determined by using analysis of variance for repeated measures and Bonferroni post hoc tests. HR dependency was determined by using linear regression analysis. HR significantly affected 3D coronary motion (r = 0.47, P < .009) through nonproportional shortening of systole and diastole (r = -0.82, P < .001), leading to percentage reconstruction interval shifts of coronary velocity troughs and peaks (P < .01). Results suggest that image reconstruction algorithms at CT coronary angiography be adapted to the individual patient's HR.

Optimization of a retrospective technique for respiratory-gated high speed micro-CT of free-breathing rodents

The objective of this study was to develop a technique for dynamic respiratory imaging using retrospectively gated high-speed micro-CT imaging of free-breathing mice. Free-breathing C57Bl6 mice were scanned using a dynamic micro-CT scanner, comprising a flat-panel detector mounted on a slip-ring gantry. Projection images were acquired over ten complete gantry rotations in 50 s, while monitoring the respiratory motion in synchrony with projection-image acquisition. Projection images belonging to a selected respiratory phase were retrospectively identified and used for 3D reconstruction. The effect of using fewer gantry rotations--which influences both image quality and the ability to quantify respiratory function--was evaluated. Images reconstructed using unique projections from six or more gantry rotations produced acceptable images for quantitative analysis of lung volume, CT density, functional residual capacity and tidal volume. The functional residual capacity (0.15 +/- 0.03 mL) and tidal volumes (0.08 +/- 0.03 mL) measured in this study agree with previously reported measurements made using prospectively gated micro-CT and at higher resolution (150 microm versus 90 microm voxel spacing). Retrospectively gated micro-CT imaging of free-breathing mice enables quantitative dynamic measurement of morphological and functional parameters in the mouse models of respiratory disease, with scan times as short as 30 s, based on the acquisition of projection images over six gantry rotations.

Evaluation of the influence of acquisition and reconstruction parameters for 16-row multidetector CT on coronary calcium scoring using a stationary and dynamic cardiac phantom

A calcium-scoring phantom with hydroxyapatite-filled cylindrical holes (0.5 to 4 mm) was used. High-resolution scans were performed for an accuracy baseline. The phantom was mounted to a moving heart phantom. Non-moving data with the implementation of an ECG-signal were acquired for different pitches (0.2/0.3), heart rates (60/80/95 bpm) and collimations (16 x 0.75/16 x 1.5 mm). Images were reconstructed with a cone-beam multi-cycle algorithm at a standard thickness/increment of 3 mm/1.5 mm and the thinnest possible thickness (0.8/0.4 and 2/1). Subsequently, ECG-gated moving calcium-scoring phantom data were acquired. The calcium volume and Agatston score were measured. The temporal resolution and reconstruction cycles were calculated. High-resolution scans determine the calcium volume with a high accuracy (mean overestimation, 0.8%). In the non-moving measurements, the volume underestimation ranged from about 6% (16 x 0.75 mm; 0.8/0.4 mm) to nearly 25% (16 x 1.5 mm; 3/1.5 mm). Moving scans showed increased measurement errors depending on the reconstructed RR interval, collimation, pitch, heart rate and gantry rotation time. Also, a correlation with the temporal resolution could be found. The reliability of calcium-scoring results can be improved with the use of a narrower collimation, a lower pitch and the reconstruction of thinner images, resulting in higher patient doses. The choice of the correct cardiac phase within the RR interval is essential to minimize measurement errors.

Electrocardiogram-Independent Image Reconstruction in Cardiac Multidetector Computed Tomography Using Retrospective Motion Synchronization

OBJECTIVE

We sought to evaluate an electrocardiogram (ECG)-independent image reconstruction technique for coronary computed tomography (CT)-angiography based on cardiac motion.

MATERIALS AND METHODS

The raw data from 20 patients was reconstructed with both an ECG-gated algorithm and a motion-dependent algorithm that calculates the cardiac motion-function directly from the CT raw data using a center of mass technique. Images were reconstructed in 5% steps over the R-R interval and the cardiac motion-cycle. For both approaches multiplanar reformations were created and the set of images with the least motion artifacts was used for the evaluation. Motion artifacts affecting the ascending aorta, the left main coronary artery and the entire course of the LAD, LCX and RCA were scored using a 5-point scale.

RESULTS

The mean optimal reconstruction window was at 60% of the R-R interval and 30% of the cardiac motion cycle. A total of 73 of 100 vascular regions showed no motion artifacts in ECG-gated images, with the motion-synchronized algorithm only 41 regions were free of motion artifacts. The mean motion-score was 1.4 (+/-0.6) and 2.4 (+/-1.2) respectively (P < 0.05).

CONCLUSION

In the currently implemented form the motion-gated algorithm is inferior to ECG-gated image reconstruction but can be used in patients with an incomplete or corrupt ECG-signal.

Cardiac CT: coronary arteries and beyond

Multi-detector-row computed tomography (MDCT) has emerged as a rapidly developing method for non-invasive imaging of the heart. An understanding of ECG synchronization, contrast material administration, patient preparation and image post-processing is needed to optimize image quality. The basic technical principles and essentials of these technical basics are described here. Correctly applied cardiac MDCT allows imaging of the coronary arteries including coronary anatomy and stenosis detection. The same is true for evaluation of coronary artery bypass grafts and, to some extent, coronary artery stents. While quantification of total calcified plaque burden has been long established, coronary MDCT allows assessing plaque morphology and constitution. Recent approaches go beyond the coronaries and include evaluation of left ventricular function at rest and myocardial viability. In combination with experimental approaches for assessing aortic valve function and myocardial perfusion imaging, cardiac MDCT offers the potential for a comprehensive examination of the heart using a single breath-hold examination.

CEnPiT: Helical cardiac CT reconstruction

Computer tomography (CT) scanners with an increasing number of detector rows offer the potential of shorter scanning times. Nevertheless, the reconstruction problem becomes more challenging, since cone beam artifacts are likely to enter. Here, we consider helical cardiac CT. We analyze how a relationship can be established between exact reconstruction algorithms and the demand to perform a cardiac gating. Utilizing the redundancies requires the consideration of all kinds of Radon planes. For the reconstruction algorithm proposed here, we separate the data into two parts. The first part contains contributions of Radon planes, which are measured with a large number of redundancies. The second part contains the remaining contributions. As it turns out, the second part contributes rather to the low-frequency contents of trans-axial slices. Therefore, we propose to perform a gated back-projection only for the first part, while the second part is back-projected in an ungated way. Data from the complete source trajectory are employed in the reconstruction process in contrary to conventional helical cardiac reconstruction methods. Moreover, all different types of Radon planes are taken into account in the reconstruction, though an ECG-dependent cardiac gating is applied. The reconstruction results, which we present for clinical and simulated data, demonstrate the high potential of CEnPiT for helical cardiac CT with large cone angle systems.

Angle-independent measure of motion for image-based gating in 3D coronary angiography

The role of three-dimensional (3D) image guidance for interventional procedures and minimally invasive surgeries is increasing for the treatment of vascular disease. Currently, most interventional procedures are guided by two-dimensional x-ray angiography, but computed rotational angiography has the potential to provide 3D geometric information about the coronary arteries. The creation of 3D angiographic images of the coronary arteries requires synchronization of data acquisition with respect to the cardiac cycle, in order to minimize motion artifacts. This can be achieved by inferring the extent of motion from a patient's electrocardiogram (ECG) signal. However, a direct measurement of motion (from the 2D angiograms) has the potential to improve the 3D angiographic images by ensuring that only projections acquired during periods of minimal motion are included in the reconstruction. This paper presents an image-based metric for measuring the extent of motion in 2D x-ray angiographic images. Adaptive histogram equalization was applied to projection images to increase the sharpness of coronary arteries and the superior-inferior component of the weighted centroid (SIC) was measured. The SIC constitutes an image-based metric that can be used to track vessel motion, independent of apparent motion induced by the rotational acquisition. To evaluate the technique, six consecutive patients scheduled for routine coronary angiography procedures were studied. We compared the end of the SIC rest period (rho) to R-waves (R) detected in the patient's ECG and found a mean difference of 14 +/- 80 ms. Two simultaneous angular positions were acquired and rho was detected for each position. There was no statistically significant difference (P = 0.79) between rho in the two simultaneously acquired angular positions. Thus we have shown the SIC to be independent of view angle, which is critical for rotational angiography. A preliminary image-based gating strategy that employed the SIC was compared to an ECG-based gating strategy in a porcine model. The image-based gating strategy selected 61 projection images, compared to 45 selected by the ECG-gating strategy. Qualitative comparison revealed that although both the SIC-based and ECG-gated reconstructions decreased motion artifact compared to reconstruction with no gating, the SIC-based gating technique increased the conspicuity of smaller vessels when compared to ECG gating in maximum intensity projections of the reconstructions and increased the sharpness of a vessel cross section in multi-planar reformats of the reconstruction.

Aperture weighted cardiac reconstruction for cone-beam CT

Multi-row detectors together with fast rotating gantries made cardiac imaging possible for CT. Due to the cardiac motion, ECG gating has to be integrated into the reconstruction of the data measured on a low pitch helical trajectory. Since the first multi-row scanners were introduced, it has been shown that approximative true cone-beam reconstruction methods are most suitable for the task of retrospectively gated cardiac volume CT. In this paper, we present the aperture weighted cardiac reconstruction (AWCR), which is a three-dimensional reconstruction algorithm of the filtered back-projection type. It is capable of handling all illumination intervals of an object point, which occur as a consequence of a low pitch helical cone-beam acquisition. Therefore, this method is able to use as much redundant data as possible, resulting in an improvement of the image homogeneity, the signal to noise ratio and the temporal resolution. Different optimization techniques like the heart rate adaptive cardiac weighting or the automatic phase determination can be adopted to AWCR. The excellent image quality achieved by AWCR is presented for medical datasets acquired with both a 40-slice and a 64-slice cone-beam CT scanner.

Cardiac imaging using multislice computed tomography scanners: technical considerations

Conventional coronary angiography is currently the gold standard in the detection and diagnosis of coronary artery disease. This modality, however, is invasive in nature. Hence, there is a need for noninvasive imaging techniques to provide comprehensive assessment of coronary artery disease, especially in stable patients at low to moderate risk of disease. In recent years, a number of noninvasive modalities have found wide applications in cardiac imaging. Most recent investigations have used magnetic resonance imaging, multislice computed tomography and electron-beam computed tomography scanners. This review discusses the clinical challenges existing in the field of cardiac imaging and focuses on the technical advancements of multislice computed tomography scanners that have made them a very attractive noninvasive option for the detection and diagnosis of coronary artery disease.

Rawdata-Based Detection of the Optimal Reconstruction Phase in ECG-Gated Cardiac Image Reconstruction

In order to achieve diagnostically useful CT (computed tomography) images of the moving heart, the standard image reconstruction has to be modified to a phase-correlated reconstruction, which considers the motion phase of the heart and generates a quasi-static image in one defined motion phase. For that purpose a synchronization signal is needed, typically a concurrent ECG recording. Commonly, the reconstruction phase is adapted by the user to the patient-specific heart motion to improve the image quality and thus the diagnostic value. The purpose of our work is to automatically identify the optimal reconstruction phase for cardiac CT imaging with respect to motion artifacts. We provide a solution for a patient- and heart rate-independent detection of the optimal phase in the cardiac cycle which shows a minimum of cardiac movement. We validated our method by the correlation with the reconstruction phase selected visually on the basis of ECG-triggering and used for the medical diagnosis. The mean difference between both reconstruction phases was 12.5% with respect to a whole cardiac motion cycle indicating a high correlation. Additionally, reconstructed cardiac images are shown which confirm the results expressed by the correlation measurement and in some cases even indicating an improvement using the proposed method.

Cardiac cone-beam CT volume reconstruction using ART

Modern computed tomography systems allow volume imaging of the heart. Up to now, approximately two-dimensional (2D) and 3D algorithms based on filtered backprojection are used for the reconstruction. These algorithms become more sensitive to artifacts when the cone angle of the x-ray beam increases as it is the current trend of computed tomography (CT) technology. In this paper, we investigate the potential of iterative reconstruction based on the algebraic reconstruction technique (ART) for helical cardiac cone-beam CT. Iterative reconstruction has the advantages that it takes the cone angle into account exactly and that it can be combined with retrospective cardiac gating fairly easily. We introduce a modified ART algorithm for cardiac CT reconstruction. We apply it to clinical cardiac data from a 16-slice CT scanner and compare the images to those obtained with a current analytical reconstruction method. In a second part, we investigate the potential of iterative reconstruction for a large area detector with 256 slices. For the clinical cases, iterative reconstruction produces excellent images of diagnostic quality. For the large area detector, iterative reconstruction produces images superior to analytical reconstruction in terms of cone-beam artifacts.

Automatic determination of minimal cardiac motion phases for computed tomography imaging: initial experience

Low motion phases for cardiac computed tomography reconstructions are currently detected manually in a user-dependent selection process which is often time consuming and suboptimal. The concept of motion maps was recently introduced to achieve automatic phase selection. This pilot study compared the accuracy of motion-map phase selection to that with manual iterative selection. The study included 20 patients, consisting of one group with low and one with high heart rate. The technique automatically derives a motion strength function between multiple low-resolution reconstructions through the cardiac cycle, with periods of lowest difference between neighboring phases indicating minimal cardiac motion. A high level of agreement was found for phase selection achieved with the motion map approach compared with the manual iterative selection process. The motion maps allowed automated quiescent phase detection of the cardiac cycle in 85% of cases, with best results at low heart rates and for the left coronary artery. They can also provide additional information such as the presence of breathing artifacts. Motion maps show promise as a rapid off-line tool to automatically detect quiescent cardiac phases in a variety of patients.

Helical cardiac cone beam CT reconstruction with large area detectors: a simulation study

Retrospectively gated cardiac volume CT imaging has become feasible with the introduction of heart rate adaptive cardiac CT reconstruction algorithms. The development in detector technology and the rapid introduction of multi-row detectors has demanded reconstruction schemes which account for the cone geometry. With the extended cardiac reconstruction (ECR) framework, the idea of approximate helical cone beam CT has been extended to be used with retrospective gating, enabling heart rate adaptive cardiac cone beam reconstruction. In this contribution, the ECR technique is evaluated for systems with an increased number of detector rows, which leads to larger cone angles. A simulation study has been carried out based on a 4D cardiac phantom consisting of a thorax model and a dynamic heart insert. Images have been reconstructed for different detector set-ups. Reconstruction assessment functions have been calculated for the detector set-ups employing different rotation times, relative pitches and heart rates. With the increased volume coverage of large area detector systems, low-pitch scans become feasible without resulting in extensive scan times, inhibiting single breath hold acquisitions. ECR delivers promising image results when being applied to systems with larger cone angles.

Artifact analysis and reconstruction improvement in helical cardiac cone beam CT

With the introduction of cone beam (CB) scanners, cardiac volumetric computed tomography (CT) imaging has the potential to become a noninvasive imaging tool in clinical routine for the diagnosis of various heart diseases. Heart rate adaptive reconstruction schemes enable the reconstruction of high-resolution volumetric data sets of the heart. Artifacts, caused by strong heart rate variations, high heart rates and obesity, decrease the image quality and the diagnostic value of the images. The image quality suffers from streak artifacts if suboptimal scan and reconstruction parameters are chosen, demanding improved gating techniques. In this paper, an artifact analysis is carried out which addresses the artifacts due to the gating when using a three-dimensional CB cardiac reconstruction technique. An automatic and patient specific cardiac weighting technique is presented in order to improve the image quality. Based on the properties of the reconstruction algorithm, several assessment techniques are introduced which enable the quantitative determination of the cycle-to-cycle transition smoothness and phase homogeneity of the image reconstruction. Projection data of four patients were acquired using a 16-slice CBCT system in low pitch helical mode with parallel electrocardiogram recording. For each patient, image results are presented and discussed in combination with the assessment criteria.