Coronary Artery Motion Research Articles

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

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. 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 (0-80mm/s, increment of 10mm/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. Reference mean (95% confidence interval) motion artifact area was 24.9 mm2 (23.8, 26.0). Without MCR, motion artifact areas for velocities exceeding 20mm/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 70mm/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 artifactreduction. 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. 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. • 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.

Resting global longitudinal strain and stress echocardiography to detect coronary artery disease burden.

Stress echocardiography (SE) is a recommended diagnostic method in patients with suspected coronary artery disease (CAD).1 Resting global longitudinal strain (GLS), coronary flow velocity reserve in the left-anterior descending coronary artery (CFVR-LAD) and delta wall motion score index (d-WMSI) on SE have proven prognostic value.2,3 Diagnostic accuracy comparison of these parameters for the detection of CAD and CAD burden is lacking. The aim of this study was to compare the diagnostic accuracy of resting left-ventricular (LV) function variables (LVEF and GLS), and the stress-derived d-WMSI and CFVR-LAD in order to estimate the presence and the increasing severity of CAD. All consecutive patients who underwent SE for suspected CAD and coronary anatomy evaluation (invasive or not) within 90 days from SE were enrolled from 1 January 2009 to 31 December 2020 at the Parma University Hospital (Parma, Italy). The exclusion criteria were i) known heart disease or ii) poor acoustic window. All patients underwent transthoracic echocardiography at rest and SE with dipyridamole and contrast media for LV border enhancement (SonoVue, Bracco Imaging, Milan, Italy).4 Resting GLS measurements were calculated and expressed in absolute values by blinded operators (N.G., D.T.), after the recruitment was complete, using Philips QLAB software (version 10.7). The wall motion score index was calculated at baseline and at peak stress using a 17-segment model of the LV. The CFVR-LAD was calculated as the hyperemic and basal peak diastolic coronary velocity ratio.4 Obstructive CAD was defined as the presence of a luminal reduction of ≥50% in the epicardial vessels. The modified Duke Prognostic Index was used to classify CAD burden according to the extension, location, and coronary stenosis severity.5 Patients with Duke Prognostic Index class >5 were defined as having severe CAD burden.

Influence of right coronary artery motion, flow pulsatility and non-Newtonian rheology on wall shear stress metrics.

The patchy distribution of atherosclerosis within the arterial system is consistent with a controlling influence of hemodynamic wall shear stress (WSS). Patterns of low, oscillatory and transverse WSS have been invoked to explain the distribution of disease in the aorta. Disease of coronary arteries has greater clinical importance but blood flow in these vessels may be complicated by their movement during the cardiac cycle. Previous studies have shown that time average WSS is little affected by the dynamic geometry, and that oscillatory shear is influenced more. Here we additionally investigate effects on transverse WSS. We also investigate the influence of non-Newtonian blood rheology as it can influence vortical structure, on which transverse WSS depends; Carreau-Yasuda models were used. WSS metrics were derived from numerical simulations of blood flow in a model of a moving right coronary artery which, together with a subject-specific inflow waveform, was obtained by MR imaging of a healthy human subject in a previous study. The results confirmed that time average WSS was little affected by dynamic motion and that oscillatory WSS was more affected. They additionally showed that transverse WSS and its non-dimensional analogue, the Cross Flow Index, were affected still further. This appeared to reflect time-varying vortical structures caused by the changes in curvature. The influence of non-Newtonian rheology was significant with some physiologically realistic parameter values, and hence may be important in certain subjects. Dynamic geometry and non-Newtonian rheology should be incorporated into models designed to produce maps of transverse WSS in coronary arteries.

Quantitative assessment of motion effects in dual-source dual-energy CT and dual-source photon-counting detector CT.

Conventional dual-source CT scanners can be used to either provide better temporal resolution or dual-energy imaging, but not both at the same time. This presents a dilemma in cardiac CT as both high temporal resolution and multi-energy imaging are desirable. The current study evaluated a dual-source photon-counting-detector (DS-PCD) CT which can acquire multi-energy images at high temporal resolution. A cardiac motion phantom with a 3-mm diameter iodinated rod, mimicking the right coronary artery, was scanned 25 times using a DS-PCD CT (66 ms resolution) and a dual-source dual-energy (DS-DE, 125 ms resolution) CT. Low/high energy images and iodine maps were reconstructed at 40% and 75% cardiac phases. To quantify the impact of motion on image quality, dice similarity coefficient was computed between the low/high energy images while the circularity and effective diameter of the iodinated rod were computed on the iodine maps. The dice coefficients were higher for DS-PCD with a mean of 0.89 and 0.91 at the 40% and 70% phases, while DS-DE had a lower mean of 0.20 and 0.78, respectively. The circularity was excellent for DS-PCD with a mean of 0.97 and 0.98 at the 40% and 75% phases, while DS-DE had a mean of 0.71 and 0.98, respectively. The effective diameter was accurate for DS-PCD with a mean of 2.9 mm (true size of 3 mm) at both phases, while DS-DE had a mean of 4.0 mm and 3.2 mm at the 40% and 75% phases, respectively. These results indicate that DS-PCD CT enables simultaneous high temporal resolution and multi-energy cardiac imaging with minimal motion artifacts.

Entrapped Coronary Arteries in Constrictive Pericarditis.

Pericardial constriction can be present without pericardial calcium and often without pericardial thickening. This epicardial coronary artery motion abnormality due to entrapment in a thickened, fibrotic pericardium, is characteristic of constrictive pericarditis, and differentiates this entity from other close differential diagnoses, such as restrictive and dilated cardiomyopathy.

Deep learning-based coronary artery motion estimation and compensation for short-scan cardiac CT.

During a typical cardiac short scan, the heart can move several millimeters. As a result, the corresponding CT reconstructions may be corrupted by motion artifacts. Especially the assessment of small structures, such as the coronary arteries, is potentially impaired by the presence of these artifacts. In order to estimate and compensate for coronary artery motion, this manuscript proposes the deep partial angle-based motion compensation (Deep PAMoCo). The basic principle of the Deep PAMoCo relies on the concept of partial angle reconstructions (PARs), that is, it divides the short scan data into several consecutive angular segments and reconstructs them separately. Subsequently, the PARs are deformed according to a motion vector field (MVF) such that they represent the same motion state and summed up to obtain the final motion-compensated reconstruction. However, in contrast to prior work that is based on the same principle, the Deep PAMoCo estimates and applies the MVF via a deep neural network to increase the computational performance as well as the quality of the motion compensated reconstructions. Using simulated data, it could be demonstrated that the Deep PAMoCo is able to remove almost all motion artifacts independent of the contrast, the radius and the motion amplitude of the coronary artery. In any case, the average error of the CT values along the coronary artery is about 25HU while errors of up to 300HU can be observed if no correction is applied. Similar results were obtained for clinical cardiac CT scans where the Deep PAMoCo clearly outperforms state-of-the-art coronary artery motion compensation approaches in terms of processing time as well as accuracy. The Deep PAMoCo provides an efficient approach to increase the diagnostic value of cardiac CT scans even if they are highly corrupted by motion.

Correcting motion artifacts in coronary computed tomography angiography images using a dual-zone cycle generative adversarial network.

Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality to detect and diagnose coronary artery disease. Due to the limitations of equipment and the patient's physiological condition, some CCTA images collected by 64-slice spiral computed tomography (CT) have motion artifacts in the right coronary artery, left circumflex coronary artery and other positions. To perform coronary artery motion artifact correction on clinical CCTA images collected by Siemens 64-slice spiral CT and evaluate the artifact correction method. We propose a novel method based on the generative adversarial network (GAN) to correct artifacts of CCTA clinical images. We use CCTA clinical images collected by 64-slice spiral CT as the original dataset. Pairs of regions of interest (ROIs) cropped from original dataset or images with and without motion artifacts are used to train the dual-zone GAN. When predicting the CCTA images, the network inputs only the clinical images with motion artifacts. Experiments show that this network effectively corrects CCTA motion artifacts. Regardless of ROIs or images, the peak signal to noise ratio (PSNR), structural similarity (SSIM), mean square error (MSE) and mean absolute error (MAE) of the generated images are greatly improved compared to those of the input data. In addition, based on scores from physicians, the average score for the coronary artery artifact correction of the output images is higher. This study demonstrates that the dual-zone GAN has the excellent ability to correct motion artifacts in the coronary arteries and maintain the overall characteristics of CCTA clinical images.

Further Improving Image Quality of Cardiovascular Computed Tomography Angiography for Children With High Heart Rates Using Second-Generation Motion Correction Algorithm.

The state-of-art motion correction algorithm is inadequate for correcting motion artifacts in coronary arteries in cardiovascular computed tomography angiography (CCTA) for children with high heart rates, and even less effective for heart structures beyond coronary arteries. This study aimed to evaluate the effectiveness of a second-generation, whole-heart motion correction algorithm in improving the heart image quality of CCTA for children with high heart rates. Forty-two consecutive symptomatic cardiac patients with high heart rates (122.6 ± 18.8 beats/min) were enrolled. All patients underwent CCTA on a 256-row CT using a prospective electrocardiogram-triggered single-beat protocol. Images were reconstructed using a standard algorithm (STD), state-of-the-art first-generation coronary artery motion correction algorithm (MC1), and second-generation, whole-heart motion correction algorithm (MC2). The image quality of the origin of left coronary, right coronary, aortic valve, pulmonary valve, mitral valve, tricuspid valve, aorta root, pulmonary artery root, ventricular septum (VS), and atrial septum (AS) was assessed by 2 experienced radiologists using a 4-point scale (1, nondiagnostic; 2, detectable; 3, measurable; and 4, excellent); nonparametric test was used to analyze and compare the differences among 3 groups; and post hoc multiple comparisons were used between different methods. There were group differences for cardiac structures except VS and AS, with MC2 having the best image quality and STD having the worst image quality. Post hoc multiple comparisons showed that MC2 was better than MC1 and STD in all structures except VS and AS where all 3 algorithms performed equally, whereas MC1 was better than STD only in the origin of left coronary, right coronary, and mitral valve. A second-generation, whole-heart motion correction algorithm further significantly improves cardiac image quality beyond the coronaries in CCTA for pediatric patients with high heart rates.

Evaluation of the proximal coronary arteries in suspected pulmonary embolism: diagnostic images in 51% of patients using non-gated, dual-source CT pulmonary angiography.

This retrospective study reports the frequency and severity of coronary artery motion on dual-source high-pitch (DSHP), conventional pitch single-source (SS), and dual-source dual-energy (DE) CT pulmonary angiography (CTPA) studies. Two hundred eighty-eight consecutive patients underwent CTPA scans for suspected pulmonary embolism between September 1, 2013 and January 31, 2014. One hundred ninety-four at DSHP scans, 57 SS scans, and 37 DE scans were analyzed. Coronary arteries were separated into nine segments, and coronary artery motion was qualitatively scored using a scale from 1 to 4 (non-interpretable to diagnostic with no motion artifacts). Signal intensity, noise, and signal to noise ratio (SNR) of the aorta, main pulmonary artery, and paraspinal muscles were also assessed. DSHP CTPA images had significantly less coronary artery motion, with 30.1% of coronary segments being fully evaluable compared to 4.2% of SS segments and 7.9% of DE segments (p < 0.05 for all comparisons). When imaging with DSHP, the proximal coronary arteries were more frequently evaluable than distal coronary arteries (51% versus 11.3%, p < 0.001). Without ECG synchronization and heart rate control, the distal left anterior descending coronary artery and mid right coronary artery remain infrequently interpretable (7% and 9%, respectively) on DSHP images. DSHP CTPA decreases coronary artery motion artifacts and allows for full evaluation of the proximal coronary arteries in 51% of cases. The study highlights the increasing importance of proximal coronary artery review when interpreting CTPA for acute chest pain.

TCT-231 An artificial intelligence based solution for fully automated cardiac phase and end-diastolic frame detection on coronary angiographies

Invasive angiography is the gold standard in coronary artery imaging. Anatomical and non-invasive functional assessment of coronary stenoses is performed on end-diastolic angiographic frames (EDF), when coronary artery motion is minimal. We evaluate the performance of a workflow based on deep neural

Automated determination of cardiac rest period on whole-heart coronary magnetic resonance angiography by extracting high-speed motion of coronary arteries

PurposeThe aim of the present study was to develop an automated system for determining the cardiac rest period during whole-heart coronary magnetic resonance angiography (CMRA) examination. Materials and methodsTen healthy male volunteers (25–51 years old, 50–77 beats/min heart rate) were enrolled in this prospective study. A motion area map was generated from a cine image set by extracting high-speed component of cardiac motion, and it was used to specify the rest period in the proposed CMRA. In conventional CMRA, the rest period was determined based on the visual inspection of cine images. Agreement of the start time, end time, and trigger time between the two methods was assessed by the Bland-Altman plot analysis. Two observers visually evaluated the quality of the curved planar reformation (CPR) image of the coronary arteries. ResultsThe proposed method significantly prolonged the start time (mean systematic difference 37.7 ms, P < 0.05) compared with the conventional method. Good agreement was observed for the end time (mean systematic difference 8.9 ms) and trigger time (mean systematic difference −28.8 ms) between the two methods. A significantly higher image quality (P < 0.05) was provided for the left circumflex artery in the proposed CMRA (mean grading score 3.88) than in conventional CMRA (mean grading score 3.68). ConclusionOur system enabled detection of the rest period automatically without operator intervention and demonstrated somewhat higher image quality compared with conventional CMRA. Its use may be useful to improve the imaging workflow for CMRA in clinical practice.

4D Quantitative Coronary Artery Motion Analysis: A Novel Method for Culprit Lesion Prediction

This study aims to determine if measuring four-dimensional quantitative coronary artery motion (QCAM) and change in tortuosity (∆T) on invasive biplane coronary angiogram is predictive of the location of culprit lesions responsible for myocardial infarctions. Invasive coronary angiograms have no current clinical application for the prediction of future coronary events. Previous studies have shown promise in demonstrating the effects of coronary artery motion on plaque formation and location, but this has yet to fully translate into a directed diagnostic method. QCAM and ΔT were calculated with CAAS QCA4D prototype software (Pie Medical Imaging, the Netherlands) for sections of the culprit coronary artery using biplane coronary angiograms of fourteen patients undergoing percutaneous coronary intervention for myocardial infarction. Prediction of the artery section containing the culprit lesion was performed using one sample t-testing, generalised linear latent and mixed statistical modelling with grouping by patient, and logistic regression modelling. QCAM was a significant predictor of the location of culprit lesions (p = 0.047). ΔT was not a significant predictor of the location of culprit lesions (p=0.49). QCAM has a role in predicting the location of culprit lesions, and may allow for targeted local therapy to prevent future events.

Evaluation of motion artifact metrics for coronary CT angiography.

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. 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 82bpm. 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. 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. 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.

Motion compensation in the region of the coronary arteries based on partial angle reconstructions from short-scan CT data.

In order to mitigate motion-induced artifacts, several motion compensation (MoCo) methods have been developed, which are either able to (a) compensate for severe artifacts, but utilize the data for the reconstruction of several cardiac phases, or (b) improve image quality of a single reconstruction with only moderate motion artifacts. We propose a method combining both benefits: dose efficiency by utilizing only the data needed for a single short-scan reconstruction while still being able to compensate for severe artifacts. We introduce a MoCo method, which we call PAMoCo, to improve the visualization of the coronary arteries of a standard coronary CT angiography exam by reducing motion artifacts. As a first step, we segment a region of interest covering a chosen coronary artery. We subdivide a volume covering the whole heart into several stacks, which are sub-volumes, reconstructed from phase-correlated short-scan data acquired during different heart cycles. Motion-compensated reconstruction is performed for each stack separately, based on partial angle reconstructions, which are derived by dividing the data corresponding to the segmented stack volume into several double-overlapping sectors. We model motion along the coronary artery center line obtained from segmentation and the temporal dimension by a low-degree polynomial and create a dense 3D motion vector field (MVF). The parameters defining the MVF are estimated by optimizing an image artifact measuring cost function and we employ a semi-global optimization routine by re-initializing the optimization multiple times. The algorithm was evaluated on the basis of a phantom measurement and clinical data. For the phantom measurement an artificial vessel equipped with calcified lesions mounted on a moving robot arm was measured, where typical coronary artery motion patterns for 70 bpm and 90 bpm have been applied. For analysis, we calculated the calcified volume V inside an ROI and measured the maximum vessel diameter d based on cross-sectional views to compare the performances of standard reconstructions obtained via filtered backprojection (FBP) and PAMoCo reconstructions between 20% and 80% of the cardiac cycle. Further, the new algorithm was applied to six clinical cases of patients with heart rates between 50 bpm and 74 bpm. Standard FBP, PAMoCo reconstructions were performed and compared to best phase FBP reconstructions and another MoCo algorithm, which is based on motion artifact metrics (MAM), via visual inspection. In case of the phantom measurement we found a strong dependence of V and d on the cardiac phase in case of the FBP reconstructions. When applying PAMoCo, V and d became almost constant due to a better discrimination from calcium to vessel and water background and values close to the ground truth have been derived. In the clinical study we chose reconstructions showing strong motion artifacts and observed a substantially improved delineation of the coronary arteries in PAMoCo reconstructions compared to the standard FBP reconstructions and also the MAM images, confirming the findings of the phantom measurement. Due to the fast reconstruction of PAMoCo images and the introduction of a new motion model, we were able to re-initialize the optimization routine at pre-selected parameter sets and thereby increase the potential of the MAM algorithm. From the phantom measurement we conclude that PAMoCo performed almost equally well in all cardiac phases and suggest applying the PAMoCo algorithm for single source systems in case of patients with high or irregular heart rates.

Quantification of coronary artery motion and internal risk volume from ECG gated radiotherapy planning scans

BackgroundRadiotherapy for carcinoma of breast and thoracic structures involves inadvertent radiation to heart and coronary arteries (CA). Coronary artery stenosis in high radiation dose segments has been documented. Cardiac and respiratory motion induced displacement of CA and internal risk volume (IRV) margin remains inadequately quantified. Material and methodsTwenty cases of carcinoma breast, lung and lung metastasis were enrolled in this study. ECG gated intravenous contrast enhanced computed tomography (CECT) scans were performed in inspiratory breath hold (IBH) and expiratory breath hold (EBH). The images were segregated into inspiratory systole (IS), inspiratory diastole (ID), expiratory systole (ES) and expiratory diastole (ED) sets. Left anterior descending (LAD), limited segment of LAD close to chest wall (short LAD), right coronary artery (RCA), Left circumflex artery (LCX) and left ventricle (LV) were delineated in all four sets. Mean displacements in systole versus diastole and inspiration versus expiration were calculated in three co-ordinates [anterio-posterior (Z), left–right (X) and cranio-caudal (Y)]. ResultsMean of displacement (mm) between systole and diastole (IS versus ID; and ES versus ED) in X, Y, Z co-ordinates were: LAD 3.0(±1.6), 2.8(±1.5), 3.6(±2.0); Short-LAD 3.0(±1.1), 0.8(±0.4), 2.4(±0.6); LV 2.4(±1.6), 1.7(±1), 5.0(±1.5); LCX 4.9(±1.6), 2.9(±1.3), 5.1(±1.9); RCA 6.6(±2.2), 3.6(±2.1), 5.9(±2.2). Mean displacement between inspiration and expiration (IS versus ES; and ID versus ED) in X, Y, Z axes were: LAD 3.3(±1.5), 8.0(±3.4), 3.8(±1.8); Short-LAD 2.7(±1), 12.2(±4.4), 3.3(±1.5); LV 2.9(±1.4), 9.8(±3.3), 4.7(±1.9); LCX 2.9(±.8), 9.7(±3.2), 6.2(±2.5); RCA 2.6(±1.3), 7.6(±2.5), 3.8(±1.7). ConclusionRadial (RM), cranio-caudal margin (CC) of 7mm, 4mm in breath-hold radiotherapy whereas RM, CC of 7mm, 13mm respectively in free breath radiotherapy will cover the range of motions of CA, LV and can be recommended as IRV for these structures.

TH‐CD‐206‐12: Image‐Based Motion Estimation for Plaque Visualization in Coronary Computed Tomography Angiography

Purpose:Visualization and quantification of coronary artery calcification and atherosclerotic plaque benefits from coronary artery motion (CAM) artifact elimination. This work applies a rigid linear motion model to a Volume of Interest (VoI) for estimating motion estimation and compensation of image degradation in Coronary Computed Tomography Angiography (CCTA).Methods:In both simulation and testbench experiments, translational CAM was generated by displacement of the imaging object (i.e. simulated coronary artery and explanted human heart) by ∼8 mm, approximating the motion of a main coronary branch. Rotation was assumed to be negligible. A motion degraded region containing a calcification was selected as the VoI. Local residual motion was assumed to be rigid and linear over the acquisition window, simulating motion observed during diastasis. The (negative) magnitude of the image gradient of the reconstructed VoI was chosen as the motion estimation objective and was minimized with Covariance Matrix Adaptation Evolution Strategy (CMAES).Results:Reconstruction incorporated the estimated CAM yielded signification recovery of fine calcification structures as well as reduced motion artifacts within the selected local region. The compensated reconstruction was further evaluated using two image similarity metrics, the structural similarity index (SSIM) and Root Mean Square Error (RMSE). At the calcification site, the compensated data achieved a 3% increase in SSIM and a 91.2% decrease in RMSE in comparison with the uncompensated reconstruction.Conclusion:Results demonstrate the feasibility of our image‐based motion estimation method exploiting a local rigid linear model for CAM compensation. The method shows promising preliminary results for the application of such estimation in CCTA. Further work will involve motion estimation of complex motion corrupted patient data acquired from clinical CT scanner.

Defining the optimal systolic phase targets using absolute delay time for reconstructions in dual-source coronary CT angiography.

To define the optimal systolic phase for dual-source computed tomography angiography using an absolute reconstruction delay time after the R-R interval based on the coronary artery motion, we analyzed images reconstructed between 200 and 420 miliseconds (ms) after the R wave at 20 ms increments in 21 patients. Based on the American Heart Association coronary segmentation guidelines, the origin of six coronary artery landmarks (RCA, AM1, PDA, LM, OM1, and D2) were selected to calculate the coronary artery motion velocity. The velocity of the given landmark was defined as the quotient of the route and the length of the time interval. The x, y and z-coordinates of the selected landmark were recorded, and were used for the calculation of the 3D route of coronary artery motion by using a specific equation. Differences in velocities were assessed by analysis of variance for repeated measures; Bonferroni post hoc tests were used for multiple pair wise comparisons. 1488 landmarks were measured (6 locations at 12 systolic time points) in 21 patients and were analyzed. The mean values of the minimum velocities were calculated separately for each heart rate group (i.e. <65; 65-80; and >80 bpm). The mean lowest coronary artery velocities in each segment occurred in the middle period of each time interval of the acquired systolic phase i.e. 280-340 ms. No differences were found in the minimal coronary artery velocities between the three HR groups, with the exception of the AM1 branch (p = 0.00495) between <65 and >80 bpm (p = 0.03), and at HRs of 65-80 versus >80 bpm (p = 0.006). During an absolute delay of 200-420 ms after the R-wave, the ideal reconstruction interval varies significantly among coronary artery segments. Decreased velocities occur between 280 to 340 ms. Therefore a narrow range of systolic intervals, rather than a single phase, should be acquired.

TU-EF-304-04: A Heart Motion Model for Proton Scanned Beam Chest Radiotherapy

Purpose: To model fast-moving heart surface motion as a function of cardiac-phase in order to compensate for the lack of cardiac-gating in evaluating accurate dose to coronary structures. Methods: Ten subjects were prospectively imaged with a breath-hold, cardiac-gated MRI protocol to determine heart surface motion. Radial and planar views of the heart were resampled into a 3-dimensional volume representing one heartbeat. A multi-resolution optical flow deformable image registration algorithm determined tissue displacement during the cardiac-cycle. The surface of the heart was modeled as a thin membrane comprised of voxels perpendicular to a pencil beam scanning (PBS) beam. The membrane's out-of-plane spatial displacement was modeled as a harmonic function with Lame's equations. Model accuracy was assessed with the root mean squared error (RMSE). The model was applied to a cohort of six chest wall irradiation patients with PBS plans generated on phase-sorted 4DCT. Respiratory motion was separated from the cardiac motion with a previously published technique. Volumetric dose painting was simulated and dose accumulated to validate plan robustness (target coverage variation accepted within 2%). Maximum and mean heart surface dose assessed the dosimetric impact of heart and coronary artery motion. Results: Average and maximum heart surface displacements were 2.54±0.35mm and 3.6mm from the end-diastole phase to the end-systole cardiac-phase respectively. An average RMSE of 0.11±0.04 showed the model to be accurate. Observed errors were greatest between the circumflex artery and mitral valve level of the heart anatomy. Heart surface displacements correspond to a 3.6±1.0% and 5.1±2.3% dosimetric impact on the maximum and mean heart surface DVH indicators respectively. Conclusion: Although heart surface motion parallel to beam's direction was substantial, its maximum dosimetric impact was 5.1±2.3%. Since PBS delivers low doses to coronary structures relative to photon radiotherapy, it is unknown whether this variation would be clinically significant for late effects.

Respiratory motion estimation in x-ray angiography for improved guidance during coronary interventions

During percutaneous coronary interventions (PCI) catheters and arteries are visualized by x-ray angiography (XA) sequences, using brief contrast injections to show the coronary arteries. If we could continue visualizing the coronary arteries after the contrast agent passed (thus in non-contrast XA frames), we could potentially lower contrast use, which is advantageous due to the toxicity of the contrast agent. This paper explores the possibility of such visualization in mono-plane XA acquisitions with a special focus on respiratory based coronary artery motion estimation.We use the patient specific coronary artery centerlines from pre-interventional 3D CTA images to project on the XA sequence for artery visualization. To achieve this, a framework for registering the 3D centerlines with the mono-plane 2D + time XA sequences is presented. During the registration the patient specific cardiac and respiratory motion is learned. We investigate several respiratory motion estimation strategies with respect to accuracy, plausibility and ease of use for motion prediction in XA frames with and without contrast. The investigated strategies include diaphragm motion based prediction, and respiratory motion extraction from the guiding catheter tip motion. We furthermore compare translational and rigid respiratory based heart motion.We validated the accuracy of the 2D/3D registration and the respiratory and cardiac motion estimations on XA sequences of 12 interventions. The diaphragm based motion model and the catheter tip derived motion achieved 1.58 mm and 1.83 mm median 2D accuracy, respectively. On a subset of four interventions we evaluated the artery visualization accuracy for non-contrast cases. Both diaphragm, and catheter tip based prediction performed similarly, with about half of the cases providing satisfactory accuracy (median error < 2 mm).

PCA-derived respiratory motion surrogates from X-ray angiograms for percutaneous coronary interventions.

PurposeIntraoperative coronary motion modeling with motion surrogates enables prospective motion prediction in X-ray angiograms (XA) for percutaneous coronary interventions. The motion of coronary arteries is mainly affected by patients breathing and heartbeat. Purpose of our work is therefore to extract coronary motion surrogates that are related to respiratory and cardiac motion. In particular, we focus on respiratory motion surrogates extraction in this paper.MethodsWe propose a fast automatic method for extracting patient-specific respiratory motion surrogate from cardiac XA. The method starts with an image preprocessing step to remove all tubular and curvilinear structures from XA images, such as vessels and guiding catheters, followed by principal component analysis on pixel intensities. The respiratory motion surrogate of an XA image is then obtained by projecting its vessel-removed image onto the first principal component.ResultsThis breathing motion surrogate was demonstrated to get high correlation with ground truth diaphragm motion (correlation coefficient over 0.9 on average). In comparison with other related methods, the method we developed did not show significant difference (p>0.05), but did improve robustness and run faster on monoplane and biplane data in retrospective and prospective scenarios.Conclusionswe developed and evaluated a method in extraction of respiratory motion surrogate from interventional X-ray images that is easy to implement and runs in real time and thus allows extracting respiratory motion surrogates during interventions.