Cardiac Motion Patterns Research Articles

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI.

Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for evaluation of heart function. Real-time cine MRI data acquisition during free breathing snapshot imaging enables imaging of patient cohorts that cannot be imaged with segmented or breath-hold acquisitions, but requires rapid imaging to achieve sufficient spatial-temporal resolutions. However, at high acceleration rates, conventional reconstruction techniques suffer from residual aliasing and temporal blurring, including advanced methods such as compressed sensing with radial trajectories. Recently, deep learning (DL) reconstruction has emerged as a powerful tool in MRI. However, its utility for free-breathing real-time cine MRI has been limited, as database-learning of spatio-temporal correlations with varying breathing and cardiac motion patterns across subjects has been challenging. Zero-shot self-supervised physics-guided deep learning (PG-DL) reconstruction has been proposed to overcome such challenges of database training by enabling subject-specific training. In this work, we adapt zero-shot PG-DL for real-time cine MRI with a spatio-temporal regularization. We compare our method to TGRAPPA, locally low-rank (LLR) regularized reconstruction and database-trained PG-DL reconstruction, both for retrospectively and prospectively accelerated datasets. Results on highly accelerated real-time Cartesian cine MRI show that the proposed method outperforms other reconstruction methods, both visibly in terms of noise and aliasing, and quantitatively.

Remote Respiratory and Cardiac Motion Patterns Separation with 4D Imaging Radars.

Radar-based noncontact physiological signals monitoring is meaningful for daily health monitoring, post-disaster rescue, and public security. This paper focuses on the theoretical and experimental study of noncontact respiratory and cardiac motion signals separation employing remote sensing by a four-dimensional (4D) imaging radar. To adaptively separate respiratory and cardiac motion patterns, we propose a variational mode separation (VMS) algorithm. VMS is established on optimizing a variational problem to separate different modes. It minimizes the energy overlap of the heartbeat and respiration signals as well as their harmonics with an equality constraint. Both simulation and real scene data results show that the proposed VMS algorithm is suitable for separating the weaker cardiac motion pattern from the strong respiratory motion pattern, restraining the influence of respiration harmonics on the heartbeat component. Also, the continuous remote monitoring of respiratory rate (RR) and heart rate (HR) by employing the proposed method in a real scene shows a strong consistency with the reference respiration belt and electrocardiogram (ECG). The root mean square error (RMSE) of RR and HR for the noncontact measurement are 0.13 breaths per minute (brpm) and 1.7 beats per minute (bpm), respectively.

Region-focused multi-view transformer-based generative adversarial network for cardiac cine MRI reconstruction.

Cardiac cine magnetic resonance imaging (MRI) reconstruction is challenging due to spatial and temporal resolution trade-offs. Temporal correlation in cardiac cine MRI is informative and vital for understanding cardiac dynamic motion. Exploiting the temporal correlations in cine reconstruction is crucial to resolve aliasing artifacts and maintaining the cardiac motion patterns. However, existing methods have the following shortcomings: (1) they simultaneously compute pairwise correlations along spatial and temporal dimensions to establish dependencies, ignoring that learning spatial contextual information first will benefit the temporal modeling. (2) most studies neglect to focus on reconstructing the local cardiac regions, resulting in insufficient reconstruction accuracy due to a relatively large field of view. To address these problems, we propose a region-focused multi-view transformer-based generative adversarial network for cardiac cine MRI reconstruction. The proposed transformer divides consecutive cardiac frames into multiple views for cross-view feature extraction, establishing long-distance dependencies among features and effectively learning the spatio-temporal information. We further design a cross-view attention for spatio-temporal information fusion, ensuring the interaction of different spatio-temporal information in each view and capturing more temporal correlations of the cardiac motion. In addition, we introduce a cardiac region detection loss for improving the reconstruction quality of the cardiac region. Experimental results demonstrated that our method outperforms state-of-the-art methods. Especially with an acceleration factor as high as 10×, our method can reconstruct images with better accuracy and perceptual quality.

Characterization of motion patterns by a spatio-temporal saliency descriptor in cardiac cine MRI

Background and objective: Abnormalities of the heart motion reveal the presence of a disease. However, a quantitative interpretation of the motion is still a challenge due to the complex dynamics of the heart. This work proposes a quantitative characterization of regional cardiac motion patterns in cine magnetic resonance imaging (MRI) by a novel spatio-temporal saliency descriptor. Method: The strategy starts by dividing the cardiac sequence into a progression of scales which are in due turn mapped to a feature space of regional orientation changes, mimicking the multi-resolution decomposition of oriented primitive changes of visual systems. These changes are estimated as the difference between a particular time and the rest of the sequence. This decomposition is then temporarily and regionally integrated for a particular orientation and then for the set of different orientations. A final spatio-temporal 4D saliency map is obtained as the summation of the previously integrated information for the available scales. The saliency dispersion of this map was computed in standard cardiac locations as a measure of the regional motion pattern and was applied to discriminate control and hypertrophic cardiomyopathy (HCM) subjects during the diastolic phase. Results: Salient motion patterns were estimated from an experimental set, which consisted of 3D sequences acquired by MRI from 108 subjects (33 control, 35 HCM, 20 dilated cardiomyopathy (DCM), and 20 myocardial infarction (MINF) from heterogeneous datasets). HCM and control subjects were classified by an SVM that learned the salient motion patterns estimated from the presented strategy, by achieving a 94% AUC. In addition, statistical differences (test t-student, p<0.05) were found among groups of disease in the septal and anterior ventricular segments at both the ED and ES, with salient motion characteristics aligned with existing knowledge on the diseases. Conclusions: Regional wall motion abnormality in the apical, anterior, basal, and inferior segments was associated with the saliency dispersion in HCM, DCM, and MINF compared to healthy controls during the systolic and diastolic phases. This saliency analysis may be used to detect subtle changes in heart function.

SHAPE-REGULARIZED UNSUPERVISED LEFT VENTRICULAR MOTION NETWORK WITH SEGMENTATION CAPABILITY IN 3D+TIME ECHOCARDIOGRAPHY.

Accurate motion estimation and segmentation of the left ventricle from medical images are important tasks for quantitative evaluation of cardiovascular health. Echocardiography offers a cost-efficient and non-invasive modality for examining the heart, but provides additional challenges for automated analyses due to the low signal-to-noise ratio inherent in ultrasound imaging. In this work, we propose a shape regularized convolutional neural network for estimating dense displacement fields between sequential 3D B-mode echocardiography images with the capability of also predicting left ventricular segmentation masks. Manually traced segmentations are used as a guide to assist in the unsupervised estimation of displacement between a source and a target image while also serving as labels to train the network to additionally predict segmentations. To enforce realistic cardiac motion patterns, a flow incompressibility term is also incorporated to penalize divergence. Our proposed network is evaluated on an in vivo canine 3D+t B-mode echocardiographic dataset. It is shown that the shape regularizer improves the motion estimation performance of the network and our overall model performs favorably against competing methods.

Optimization of heart block in the left-sided whole breast radiation treatments.

Purpose: Blocks have been used to protect heart from potential radiation damage in left-sided breast treatments. Since cardiac motion pattern may not be fully captured on conventional 3DCT or 4DCT simulation scans, this study was intended to investigate the optimization of the heart block design taking the cardiac motion into consideration.Materials and Methods: Whole breast treatment plans using two opposed tangential fields were designed based on 4DCT simulation images for 10 left-sided breast cancer patients. Using an OBI system equipped to a Varian Linac, beam-eye viewed fluoroscopy images were acquired for each of the treatment beams after patient treatment setup, and the MLC heart blocks were overlaid onto the fluoroscopy images with an in-house software package. A non-rigid image registration and tracking algorithm was utilized to track the cardiac motion on the fluoroscopy images with minimal manual delineation for initialization, and the tracked cardiac motion information was used to optimize the heart block design to minimize the radiation damage to heart while avoiding the over-shielding that may lead to underdosing certain breast tissues.Results: Twenty-three sets of fluoroscopy images were acquired on 23 different days of treatment for the 10 patients. As expected, heart moved under the influences of both respiratory and cardiac motion. It was observed that for 16 out of the 23 treatments, heart moved beyond the planed heart block into treatment fields and MLC had to be adjusted to fully block heart. The adjustment was made for all but one patient. The number of the adjusted MLC leaves ranged from 1 to 16 (mean = 10), and the MLC leaf position adjustment ranged from 2 to 10 mm (mean = 6 mm). The added heart block areas ranged from 3 to 1230 mm2 (mean = 331 mm2).Conclusion: In left-sided whole breast radiation treatments, simulation CT (and 4DCT) based heart block design may not provide adequate heart protection for all the treatments. A fluoroscopy-based method has been developed to adaptively optimize the heart MLC block to achieve optimal heart protection.

MO‐A‐BRD‐08: Radiosurgery Beyond Cancer: Real‐Time Target Localization and Treatment Planning for Cardiac Radiosurgery Under MRI Guidance

Purpose:Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting &gt;2.5M Americans and &gt;4.5M Europeans. AF is usually treated with minimally‐invasive, time consuming catheter ablation techniques. Radiosurgery of the pulmonary veins (PV) has been proposed for AF treatment, however is challenging due to the complex respiratory and cardiac motion patterns. We hypothesize that an MRI‐linac could solve the difficult real‐time targeting and adaptation problem. In this study we quantified target motion ranges on cardiac MRI and analyzed the dosimetric benefits of margin reduction assuming real‐time MRI tracking was applied.Methods:For the motion study, four human subjects underwent real‐time cardiac MRI under free breathing. The target motion on coronal and axial cine planes was analyzed using a template matching algorithm. For the planning study, an ablation line at each PV antrum was defined as target on an AF patient scheduled for catheter ablation. Various safety margins ranging from 0mm (perfect tracking) to 8mm (untracked motion) were added to the target defining the PTV. 30Gy single fraction IMRT plans were then generated. Finally, the influence of a 1T magnetic field on treatment beam delivery was calculated using the Geant4 Monte Carlo algorithm to simulate the dosimetric impact of MRI guidance.Results:The motion study showed the mean respiratory motion of the target area on MRI was 8.4mm (SI), 1.7mm (AP) and 0.3mm (LR). Cardiac motion was small (&lt;2mm). The planning study showed that with increasing safety margins to encompass untracked motion, dose tolerances for OARs such as the esophagus and airways were exceeded by &gt;100%. The magnetic field had little impact on the dose distribution.Conclusion:Our results indicate that real‐time MRI tracking of the PVs seems feasible. Accurate image guidance for high‐dose AF radiosurgery is essential since safety margins covering untracked target motion will result in unacceptable treatment plans.

TH‐C‐WAB‐07: Optimization of Heart Block in the Left‐Sided Whole Breast Irradiation

Purpose: Blocks have been used to protect heart from potential radiation damage in left breast treatments. Since cardiac motion pattern may not be fully captured on co nventional 3DCT or 4DCT simulation scans, this study was intended to investigate the optimization of the heart block design taking the cardiac motion into co nsideration. Methods: Whole breast treatment plans using two opposed tangential fields were designed based on 4DCT simulation images for 10 left breast patients. Using an OBI system equipped to a Varian Linac, beam‐eye viewed fluorosco py images were acquired for each of the treatment beams after patient treatment setup, and the MLC heart blocks were overlaid onto the fluorosco py images with an in‐house software package. A non‐rigid image registration and tracking algorithm was utilized to track the cardiac motion on the fluorosco py images with minimal manual delineation, and the tracked cardiac motion information was used to optimize the heart block design to minimize the radiation damage to heart while avoiding the over‐shielding that may lead to underdosing breast tissues. Results: Heart moved under the influences of both respiratory and cardiac motion. For 4 out of 10 patients, it was observed that heart moved beyond the heart block into treatment fields. The average size of the heart portion irradiated inside the treatment fields was 0.4 mm (0.4mm‐0.4 mm), 3.6 mm (0.8 mm – 5.1 mm), 4.2 mm (0.4mm – 6.3mm), and 3.9 mm (0.2 mm–5.7mm) for the four patients, respectively. The optimization process changed the positions of 1, 8, 10, and 5 MLC leaves (5 mm wide per leaf) respectively to achieve the optimal heart protection. Co nclusion: Simulation 4DCT based heart block design may not provide adequate heart protection for all the treatments. A fluorosco py‐based method has been developed to adaptively optimize the heart MLC block to achieve optimal heart protection.

Accelerated whole‐heart 3D CSPAMM for myocardial motion quantification

Myocardial tissue tagging using complementary spatial modulation of magnetization (CSPAMM) allows detailed assessment of myocardial motion. To capture the complex 3D cardiac motion pattern, multiple 2D tagged slices are usually acquired in different orientations. These approaches are prone to slice misregistration and associated with long acquisition times. In this work, a fast method for acquiring 3D CSPAMM data is proposed that allows measuring deformation of the whole heart in three breath-holds of 18 heartbeats duration each. Three acquisitions are sequentially performed with line tag preparation in each orthogonal direction. Measurement acceleration is achieved by applying localized tagging preparation and a hybrid multishot, segmented echo-planar imaging sequence. Five healthy volunteers and five patients with myocardial infarction were measured. Midwall contours were tracked throughout the cardiac cycle with an enhanced variant of the harmonic phase (HARP) technique. Circumferential shortening at end-systole ranged from 14.1% (base) to 20.1% (apex) in healthy subjects. Hypokinetic regions in patients corresponded well with regions exhibiting hyperenhancement after contrast injection. Time to maximum circumferential shortening varied more significantly over the left ventricle in patients than in volunteers (P<0.01). The proposed measurement scheme was well tolerated by patients and holds considerable potential to investigate cardiac mechanics in various diseases.

Altered Myocardial Motion Pattern in Fabry Patients Assessed with CMR-Tagging

Progressive left ventricular hypertrophy is the hallmark of cardiac manifestations in patients with Fabry disease. Cardiovascular magnetic resonance with tissue tagging allows detailed assessment of the cardiac motion pattern. The aim was to test the hypothesis that not only Fabry patients with severe left ventricular hypertrophy exhibit changes in myocardial motion, but also Fabry patients with normal left ventricular mass. Magnetic resonance tagging using slice following complementary spatial modulation of magnetization (CSPAMM) combined with harmonic phase analysis (HARP) was applied to measure left ventricular shortening and contraction. Additionally, left ventricular rotation and global left ventricular torsion were examined. Twenty-nine Fabry patients grouped in patients with (n = 13) and without (n = 16) left ventricular hypertrophy were compared with 29 age and sex matched healthy volunteers. Long axis shortening and circumferential contraction showed reduced peak values with increasing left ventricular mass and were significantly reduced in Fabry patients with left ventricular hypertrophy (p < 0.001 and p < 0.05, respectively). Torsional deformation and apical rotation were increased both in Fabry patients with left ventricular hypertrophy as well as in patients with normal left ventricular mass (p < 0.001 for torsion) compared with controls. Applying the magnetic resonance tagging acquisition and analysis methods, myocardial motion abnormalities could not only be measured in Fabry patients with left ventricular hypertrophy but also in patients without macroscopic cardiac involvement.

True 2-D velocity display by multiscale motion mapping (triple-M imaging) allows new insights into complex cardiac motion patterns

True 2-D velocity display by multiscale motion mapping (triple-M imaging) allows new insights into complex cardiac motion patterns

Time delays in ultrasound systems can result in fallacious measurements

Even short time delays (less than 30 ms) in cardiac motion pattern may have clinical relevance. These delays can be measured with echocardiography, using techniques such as flow and tissue Doppler and M-mode together with external signals (e.g., ECG and phonocardiography). If one or more of these signals are delayed in relation to the other signals (asynchronous), an incorrect definition of cardiac time intervals can occur, the consequence of which is invalid measurement. To determine if this time delay in signal processing is a problem, we tested three common ultrasound (US) systems using the ECG as the reference signal. We used a digital ECG simulator and a Doppler string phantom to obtain test signals for flow and tissue pulsed Doppler, M-mode, phonocardiography, auxiliary and ECG signals. We found long time delays of up to 90 ms in one system, whereas delays were mostly short in the two other systems. The time delays varied relative to system settings. Consequently, to avoid these errors, precise knowledge of the characteristics of the system being used is essential. (E-mail:andrew.walker@ltvastmanland.se)

In vitro simulation and quantification of temporal jitter artifacts in ECG-gated dynamic three-dimensional echocardiography

The image quality of dynamic 3-D echocardiography is limited by temporal jitter artifacts that result from the asynchronous acquisition of video frames with the cardiac cycle. This paper analyzes the source and extent of these artifacts using in vitro studies. Dynamic 3-D images of a myocardial motion phantom were reconstructed and analyzed for eight cardiac motion patterns. The extent of temporal jitter artifacts was quantified, first, from the images by computing temporal jitter maps and, second, predicted from the motion waveforms. Temporal jitter appeared as a pattern of streak artifacts converging at the axis of rotation of the imaging plane, for the rotational scanning approach used in our study. The results of the experimental analysis techniques were compared with the waveform analysis using linear regression analysis. The least squares line showed good correlation between the data (r > 0.9) and its deviation from the line of identity was calculated to be <9%. (E-mail: afenster@irus.rri.on.ca)