Real-time Cine MRI Research Articles

CineVN: Variational network reconstruction for rapid functional cardiac cine MRI.

To develop a reconstruction method for highly accelerated cardiac cine MRI with high spatiotemporal resolution and low temporal blurring, and to demonstrate accurate estimation of ventricular volumes and myocardial strain in healthy subjects and in patients. The proposed method, called CineVN, employs a spatiotemporal Variational Network combined with conjugate gradient descent for optimized data consistency and improved image quality. The method is first evaluated on retrospectively undersampled cine MRI data in terms of image quality. Then, prospectively accelerated data are acquired in 18 healthy subjects both segmented over two heartbeats per slice as well as in real time with 1.6 mm isotropic resolution. Ventricular volumes and strain parameters are computed and compared to a compressed sensing reconstruction and to a conventional reference cine MRI acquisition. Lastly, the method is demonstrated in 46 patients and ventricular volumes and strain parameters are evaluated. CineVN outperformed compressed sensing in image quality metrics on retrospectively undersampled data. Functional parameters and myocardial strain were the most accurate for CineVN compared to two state-of-the-art compressed sensing methods. Deep learning-based reconstruction using our proposed method enables accurate evaluation of cardiac function in real-time cine MRI with high spatiotemporal resolution. This has the potential to improve cardiac imaging particularly for patients with arrhythmia or impaired breath-hold capability.

Computationally Efficient IMplicit Training Strategy for UNrolled NEtworks (IMUNNE): A preliminary analysis using accelerated real-time cardiac cine MRI.

Highly-undersampled, dynamic MRI reconstruction, particularly in multi-coil scenarios, is a challenging inverse problem. Unrolled networks achieve state-of-the-art performance in MRI reconstruction but suffer from long training times and extensive GPU memory cost. In this work, we propose a novel training strategy for IMplicit UNrolled NEtworks (IMUNNE) for highly-undersampled, multi-coil dynamic MRI reconstruction. It formulates the MRI reconstruction problem as an implicit fixed-point equation and leverages gradient approximation for backpropagation, enabling training of deep architectures with fixed memory cost. This study represents the first application of implicit network theory in the context of real-time cine MRI. The proposed method is evaluated using a prospectively undersampled, real-time cine dataset using radial k-space sampling, comprising balanced steady-state free precession (b-SSFP) readouts. Experiments include a hyperparameter search, head-to-head comparisons with a complex U-Net (CU-Net) and an alternating unrolled network (Alt-UN), and an analysis of robustness under noise perturbations; peak signal-to-noise ratio, structural similarity index, normalized root mean-square error, spatio-temporal entropic difference, and a blur metric were used. IMUNNE produced significantly and slightly better image quality compared to CU-Net and Alt-UN, respectively. Compared with Alt-UN, IMUNNE significantly reduced training and inference times, making it a promising approach for highly-accelerated, multi-coil real-time cine MRI reconstruction. IMUNNE strategy successfully applies unrolled networks to image reconstruction of highly-accelerated, real-time radial cine MRI. Implicit training enables rapid, high-quality, and cost-effective CMR exams by reducing training and inference times and lowering memory cost associated with advanced reconstruction methods.

Ultra-rapid, Free-breathing, Real-time Cardiac Cine MRI Using GRASP Amplified with View Sharing and KWIC Filtering.

Purpose To achieve ultra-high temporal resolution (approximately 20 msec) in free-breathing, real-time cardiac cine MRI using golden-angle radial sparse parallel (GRASP) reconstruction amplified with view sharing (VS) and k-space-weighted image contrast (KWIC) filtering. Materials and Methods Fourteen pediatric patients with congenital heart disease (mean age [SD], 9 years ± 2; 13 male) and 10 adult patients with arrhythmia (mean age, 62 years ± 8; nine male) who underwent both standard breath-hold cine and free-breathing real-time cine using GRASP were retrospectively identified. To achieve high temporal resolution, each time frame was reconstructed using six radial spokes, corresponding to acceleration factors ranging from 24 to 32. To compensate for loss in spatial resolution resulting from over-regularization in GRASP, VS and KWIC filtering were incorporated. The blur metric, visual image quality scores, and biventricular parameters were compared between clinical and real-time cine images. Results In pediatric patients, the incorporation of VS and KWIC into GRASP (ie, GRASP + VS + KWIC) produced significantly (P < .05) sharper x-y-t (blur metric: 0.36 ± 0.03, 0.41 ± 0.03, 0.48 ± 0.03, respectively) and x-y-f (blur metric: 0.28 ± 0.02, 0.31 ± 0.03, 0.37 ± 0.03, respectively) component images compared with GRASP + VS and conventional GRASP. Only the noise score differed significantly between GRASP + VS + KWIC and clinical cine; all visual scores were above the clinically acceptable (3.0) cutoff point. Biventricular volumetric parameters strongly correlated (R2 > 0.85) between clinical and real-time cine images reconstructed with GRASP + VS + KWIC and were in good agreement (relative error < 6% for all parameters). In adult patients, the visual scores of all categories were significantly lower (P < .05) for clinical cine compared with real-time cine with GRASP + VS + KWIC, except for noise (P = .08). Conclusion Incorporating VS and KWIC filtering into GRASP reconstruction enables ultra-high temporal resolution (approximately 20 msec) without significant loss in spatial resolution. Keywords: Cine, View Sharing, k-Space-weighted Image Contrast Filtering, Radial k-Space, Pediatrics, Arrhythmia, GRASP, Compressed Sensing, Real-Time, Free-Breathing Supplemental material is available for this article. © RSNA, 2024.

Kiosk 7R-FB-02 - Highly-accelerated FBee-breathing Real-time Cine MRI Produces Relatively Accurate Quantification of Left and Right Ventricular Function in Patients with a Cardiac Implantable Electronic Device

Kiosk 7R-FB-02 - Highly-accelerated FBee-breathing Real-time Cine MRI Produces Relatively Accurate Quantification of Left and Right Ventricular Function in Patients with a Cardiac Implantable Electronic Device

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.

Feasibility of delivered dose reconstruction for MR-guided SBRT of pancreatic tumors with fast, real-time 3D cine MRI

Background and purposeIn MR-guided SBRT of pancreatic cancer, intrafraction motion is typically monitored with (interleaved) 2D cine MRI. However, tumor surroundings are often not fully captured in these images, and motion might be distorted by through-plane movement. In this study, the feasibility of highly accelerated 3D cine MRI to reconstruct the delivered dose during MR-guided SBRT was assessed. Materials and methodsA 3D cine MRI sequence was developed for fast, time-resolved 4D imaging, featuring a low spatial resolution that allows for rapid volumetric imaging at 430 ms. The 3D cines were acquired during the entire beam-on time of 23 fractions of online adaptive MR-guided SBRT for pancreatic tumors on a 1.5 T MR-Linac. A 3D deformation vector field (DVF) was extracted for every cine dynamic using deformable image registration. Next, these DVFs were used to warp the partial dose delivered in the time interval between consecutive cine acquisitions. The warped dose plans were summed to obtain a total delivered dose. The delivered dose was also calculated under various motion correction strategies. Key DVH parameters of the GTV, duodenum, small bowel and stomach were extracted from the delivered dose and compared to the planned dose. The uncertainty of the calculated DVFs was determined with the inverse consistency error (ICE) in the high-dose regions. ResultsThe mean (SD) relative (ratio delivered/planned) D99% of the GTV was 0.94 (0.06), and the mean (SD) relative D0.5cc of the duodenum, small bowel, and stomach were respectively 0.98 (0.04), 1.00 (0.07), and 0.98 (0.06). In the fractions with the lowest delivered tumor coverage, it was found that significant lateral drifts had occurred. The DVFs used for dose warping had a low uncertainty with a mean (SD) ICE of 0.65 (0.07) mm. ConclusionWe employed a fast, real-time 3D cine MRI sequence for dose reconstruction in the upper abdomen, and demonstrated that accurate DVFs, acquired directly from these images, can be used for dose warping. The reconstructed delivered dose showed only a modest degradation of tumor coverage, mostly attainable to baseline drifts. This emphasizes the need for motion monitoring and development of intrafraction treatment adaptation solutions, such as baseline drift corrections.

Real-Time Motion Monitoring Using Orthogonal Cine MRI during MR-Guided Radiation Therapy for Liver Cancer

<h3>Purpose/Objective(s)</h3> This work investigates the feasibility of real-time motion monitoring (MM) using orthogonal cine MRI during MR guided Adaptative Radiation Therapy (MRgART) for liver tumors that are normally invisible on cine MRI with no contrast agent. <h3>Materials/Methods</h3> An investigational package, Motion Monitoring Research Package (MMRP), was developed to measure real-time target motion between orthogonal cine MRI and the daily baseline 3D MRI. The MMRP package was evaluated on 8 liver cancer patients treated on a 1.5T MR-Linac. For all patients, a 3D mid-position (MidP) image derived from a daily 4D MRI was used to delineate a sub-liver volume (SLV) encompassing the tumor. During the same session, real-time 2D T2/T1-weighted bFFE cine MRI were collected with free breathing during MRgART. The cine images were acquired with a temporal resolution of 200 ms interleaved between coronal and sagittal orientations. MMRP workflow included two steps: (1) creating a 2D template in each orientation using cine data acquired over the first 12 s, followed by a rigid registration between the combined templates and the MidP image over the SLV region; (2) measuring the SLV motion by registering the rest of the 2D cine series with the corresponding template. To evaluate the MM accuracy from MMRP, the ground-truth contours on cine MRI were created manually. Common visible vessels and segments of liver boundaries in proximity to the tumor were used as anatomical landmarks for reproducible delineations on both the 3D and cine images. MM accuracy was measured using the standard deviation of the error (SDE) to compare the center of mass position of the ground-truth and the monitored motion. Maximum of tumor motion was assessed on 4D MRI. <h3>Results</h3> In 6 of the 8 cases, the assessed mean (range) centroid motions were 8.8 (4.6-13.8), 1.5 (0.7-2.8) and 3.2 (1.5-5) mm with mean SDE (range) values of 1.2 (0.7-1.6), 0.94 (0.4-1.7), and 1 (0.4-1.4) mm in superior inferior (SI), left right, and anterior posterior (AP) directions, respectively. The mean (range) of the maximum tumor motion from the 4D MRI was 8 (5-11) mm in SI direction, smaller than the centroid MM, indicating the importance of motion capture using the MM in real-time. For the remaining two cases, quantitative MM was challenging due to target deformation and large through-plane motion in the AP direction. <h3>Conclusion</h3> We have demonstrated the feasibility of accurate real-time MM of a liver tumor using a sub-liver volume as a tumor surrogate, based on real-time orthogonal cine MRI during MRgART. The approach overcomes difficulty due to the invisibility of liver tumor on the T2/T1-w 2D cine without using a contrast agent and the need of implanting radio-opaque clips or the approximation of the whole liver motion as the tumor motion. With further investigation with more patient data, the real-time MM technique may be implemented in MRgART to manage intrafraction liver motion.

Initial observation of contrast profiles for 3D and 2D MRI sequences in MR-guided radiation therapy for locally advanced pancreatic cancer.

541 Background: MR-guided stereotactic body radiation therapy (MR-SBRT) is a novel method of treating mobile tumors with soft-tissue gating and on-table adaptive planning. In our experience using the ViewRay MRIdian system (VR) for treating locally advanced pancreatic cancer (PA) with MR-SBRT, the true-fast imaging with steady-state free precession (TRUFI) sequences on the VR impart differing intensities for relevant structures seen on the pre-treatment high resolution 3D MRI (3D MRI) versus the real-time 2D cine MRI (2D cine) used for target tracking. Since these variations can confound target tracking selection, we propose that an understanding of the differing contrast profiles could improve selection of tracking structures and optimize treatment delivery. Methods: We retrospectively reviewed both 3D MRI and 2D cine images for patients (pts) with PA (n =20) treated on the VR. At simulation, an appropriate tracking target was identified and contoured on a single 3mm sagittal slice of the 3D MRI. This sagittal slice was directly compared to the registered 7mm 2D cine to identify structures with notable discrepancies in signal intensity. The 3D MRI was then explored in additional planes to confirm structure identities. For quantitative verification of the clinically observed differences, the pixel intensity distributions of 3D MRI and 2D cine DICOM image datasets were statistically compared. Results: In all pts reviewed, arteries (aorta, celiac, SMA) appeared with similar contrast profiles on both images. However, veins (portal vein, SMV) appeared hypointense on 3D MRI but hyperintense on 2D cine. Biliary structures appeared hyperintense on 3D MRI but only mildly hyperintense on 2D cine. The pixel intensity distributions extracted from 3D MRI and 2D cine images were confirmed to differ significantly (two sample Kolmogorov-Smirnov test; test statistic =0.40; p &lt; 0.001). Conclusions: There are significant variations in image intensity between the initial treatment planning 3D MRI and the immediate pre-treatment 2D cine obtained with the VR. Understanding these discrepancies can guide radiation oncologists in choosing optimal tracking targets. Future work will focus on identifying the particular causes and frequencies of target tracking failures and exploring alternative tracking algorithms using artificial intelligence which could ultimately allow for VMAT on the ViewRay system.

Real-Time Motion Tracking Based on Orthogonal Cine MRI During MR-Guided Radiation Therapy for Prostate Cancer

In contrast to radiographic imaging with implanted radio-opaque fiducials, the high soft tissue contrast and noninvasive nature of MRI are advantageous for real-time motion tracking of prostate motion. The purpose of this study is to investigate the feasibility of tracking the intrafraction prostate motion using an intensity-based template registration technique between real-time 2D cine and 3D MRI acquired during MR-guided Adaptative Radiation Therapy (MRgART).The motion tracking algorithm includes two steps: (1) creating a template by rigidly registering a set of cine images with a 3D reference MRI, and (2) tracking the target motion by registering incoming (i.e., real-time) cine with the template with a known relationship to the 3D volume. The daily 3D T2 MRI and 2D T2/T1 bFFE real-time cine MRI acquired on a 1.5T MR-Linac during MRgART for 6 prostate cancer patients were selected to test the algorithm limits. The cine images were acquired with a temporal resolution of 0.2 s for a total duration of 9-11 minutes interleaved between coronal and sagittal orientations. A 2D template image set was generated in the coronal and sagittal planes using the cine data acquired during the first 20 s registered to the 3D volume using in-plane rigid-body image registration based on a region of interest defined by the prostate contour on 3D T2 MRI. Motion tracking of the prostate was performed by registering the rest of the 2D cine series with the corresponding template. Manually delineated contours on sampled cine frames were used as the ground truth. Tracking accuracy was defined as the standard deviation of the error (SDE) between the center of mass (CM) of the ground-truth and tracked motions in 1 min. Prostate drift was evaluated by tracking the CM shift with the algorithm every 8-9 s for 9-11 min.The prostate tracking algorithm was qualitatively validated by visual assessment of 6 prostate cases. Overall, the tracking was found robust to implant-induced image artefacts in two cases, large change in bladder size in one case, and body motion in one other case. The tracking algorithm was also validated quantitatively on 2 cases for which ground truth contours were available and reliable. Mean SDE for the two cases was 0.45, 0.32, and 0.31 mm in superior-inferior, left-right, and anterior-posterior directions, respectively. A continuous motion drift of the prostate was observed over a 600 s period for one of these two cases and was accurately tracked by the technique.We have demonstrated the feasibility to track prostate motion based on real-time orthogonal cine MRI without implanting fiducials. With further investigation on more patients and following careful workflow, the real-time motion tracking technique may be implemented in MRgART to manage intrafraction motion.H. Jassar: None. A. Tai: None. X. Chen: None. T. Keiper: None. E.S. Paulson: Research Grant; Siemens Healthineers, Elekta Instruments AB.F. Lathuiliere: None. S. Bériault: None. D. Cooper: None. F. Hebert: None. L. Savard: None. S. Cloake: None. W.A. Hall: Research Grant; Elekta, National Cancer Institute, American Cancer Society. C.A. Lawton: None. A. Li: Research Grant; Elekta AB, Accuray Inc, Siemens Healthineers, Manteia Med. Honoraria; Elekta AB, Accuray Inc. Patent/License Fees/Copyright; Manteia Med.

Comparison of Complex k-Space Data and Magnitude-Only for Training of Deep Learning–Based Artifact Suppression for Real-Time Cine MRI

Propose: The purpose of this study was to compare the performance of deep learning networks trained with complex-valued and magnitude images in suppressing the aliasing artifact for highly accelerated real-time cine MRI.Methods: Two 3D U-net models (Complex-Valued-Net and Magnitude-Net) were implemented to suppress aliasing artifacts in real-time cine images. ECG-segmented cine images (n = 503) generated from both complex k-space data and magnitude-only DICOM were used to synthetize radial real-time cine MRI. Complex-Valued-Net and Magnitude-Net were trained with fully sampled and synthetized radial real-time cine pairs generated from highly undersampled (12-fold) complex k-space and DICOM images, respectively. Real-time cine was prospectively acquired in 29 patients with 12-fold accelerated free-breathing tiny golden-angle radial sequence and reconstructed with both Complex-Valued-Net and Magnitude-Net. Cardiac function, left-ventricular (LV) structure, and subjective image quality [1(non-diagnostic)-5(excellent)] were calculated from Complex-Valued-Net– and Magnitude-Net–reconstructed real-time cine datasets and compared to those of ECG-segmented cine (reference).Results: Free-breathing real-time cine reconstructed by both networks had high correlation (all R2 &amp;gt; 0.7) and good agreement (all p &amp;gt; 0.05) with standard clinical ECG-segmented cine with respect to LV function and structural parameters. Real-time cine reconstructed by Complex-Valued-Net had superior image quality compared to images from Magnitude-Net in terms of myocardial edge sharpness (Complex-Valued-Net = 3.5 ± 0.5; Magnitude-Net = 2.6 ± 0.5), temporal fidelity (Complex-Valued-Net = 3.1 ± 0.4; Magnitude-Net = 2.1 ± 0.4), and artifact suppression (Complex-Valued-Net = 3.1 ± 0.5; Magnitude-Net = 2.0 ± 0.0), which were all inferior to those of ECG-segmented cine (4.1 ± 1.4, 3.9 ± 1.0, and 4.0 ± 1.1).Conclusion: Compared to Magnitude-Net, Complex-Valued-Net produced improved subjective image quality for reconstructed real-time cine images and did not show any difference in quantitative measures of LV function and structure.

Evaluation of super-resolution on 50 pancreatic cancer patients with real-time cine MRI from 0.35T MRgRT

MR-guided radiotherapy (MRgRT) systems provide excellent soft tissue imaging immediately prior to and in real time during radiation delivery for cancer treatment. However, 2D cine MRI often has limited spatial resolution due to high temporal resolution. This work applies a super resolution machine learning framework to 3.5 mm pixel edge length, low resolution (LR), sagittal 2D cine MRI images acquired on a MRgRT system to generate 0.9 mm pixel edge length, super resolution (SR), images originally acquired at 4 frames per second (FPS). LR images were collected from 50 pancreatic cancer patients treated on a ViewRay MR-LINAC. SR images were evaluated using three methods. 1) The first method utilized intrinsic image quality metrics for evaluation. 2) The second used relative metrics including edge detection and structural similarity index (SSIM). 3) Finally, automatically generated tumor contours were created on both low resolution and super resolution images to evaluate target delineation and compared with DICE and SSIM. Intrinsic image quality metrics all had statistically significant improvements for SR images versus LR images, with mean (±1 SD) BRISQUE scores of 29.65 ± 2.98 and 42.48 ± 0.98 for SR and LR, respectively. SR images showed good agreement with LR images in SSIM evaluation, indicating there was not significant distortion of the images. Comparison of LR and SR images with paired high resolution (HR) 3D images showed that SR images had a mean (±1 SD) SSIM value of 0.633 ± 0.063 and LR a value of 0.587 ± 0.067 (p ≪ 0.05). Contours generated on SR images were also more robust to noise addition than those generated on LR images. This study shows that super resolution with a machine learning framework can generate high spatial resolution images from 4fps low spatial resolution cine MRI acquired on the ViewRay MR-LINAC while maintaining tumor contour quality and without significant acquisition or post processing delay.

Rapid reconstruction of highly undersampled, non-Cartesian real-time cine k-space data using a perceptual complex neural network (PCNN).

Highly accelerated real-time cine MRI using compressed sensing (CS) is a promising approach to achieve high spatio-temporal resolution and clinically acceptable image quality in patients with arrhythmia and/or dyspnea. However, its lengthy image reconstruction time may hinder its clinical translation. The purpose of this study was to develop a neural network for reconstruction of non-Cartesian real-time cine MRI k-space data faster (<1 min per slice with 80 frames) than graphics processing unit (GPU)-accelerated CS reconstruction, without significant loss in image quality or accuracy in left ventricular (LV) functional parameters. We introduce a perceptual complex neural network (PCNN) that trains on complex-valued MRI signal and incorporates a perceptual loss term to suppress incoherent image details. This PCNN was trained and tested with multi-slice, multi-phase, cine images from 40 patients (20 for training, 20 for testing), where the zero-filled images were used as input and the corresponding CS reconstructed images were used as practical ground truth. The resulting images were compared using quantitative metrics (structural similarity index (SSIM) and normalized root mean square error (NRMSE)) and visual scores (conspicuity, temporal fidelity, artifacts, and noise scores), individually graded on a five-point scale (1, worst; 3, acceptable; 5, best), and LV ejection fraction (LVEF). The mean processing time per slice with 80 frames for PCNN was 23.7 ± 1.9 s for pre-processing (Step 1, same as CS) and 0.822 ± 0.004 s for dealiasing (Step 2, 166 times faster than CS). Our PCNN produced higher data fidelity metrics (SSIM = 0.88 ± 0.02, NRMSE = 0.014 ± 0.004) compared with CS. While all the visual scores were significantly different (P < 0.05), the median scores were all 4.0 or higher for both CS and PCNN. LVEFs measured from CS and PCNN were strongly correlated (R2 = 0.92) and in good agreement (mean difference = -1.4% [2.3% of mean]; limit of agreement = 10.6% [17.6% of mean]). The proposed PCNN is capable of rapid reconstruction (25 s per slice with 80 frames) of non-Cartesian real-time cine MRI k-space data, without significant loss in image quality or accuracy in LV functional parameters.

Fusion of 3D real-time echocardiography and cine MRI using a saliency analysis.

This paper presents a novel 3D multimodal registration strategy to fuse 3D real-time echocardiography images with cardiac cine MRI images. This alignment is performed in a saliency space, which is designed to maximize similarity between the two imaging modalities. This fusion improves the quality of the available information. The method performs in two steps: temporal and spatial registrations. A temporal alignment is firstly achieved by nonlinearly matching pairs of correspondences between the two modalities using a dynamic time warping. A temporal registration is then carried out by applying nonrigid transformations in a common saliency space where normalized cross correlation between temporal pairs of salient volumes is maximized. The alignment performance was evaluated with a set of 18 subjects, 3 with cardiomyopathies and 15 healthy, by computing the Dice score and Hausdorff distance with respect to manual delineations of the left ventricle cavity in both modalities. A Dice score and Hausdorff distance of [Formula: see text] and [Formula: see text], respectively, were obtained. In addition, the deformation field was estimated by quantifying its foldings, obtaining a 98% of regularity in the deformation field. The 3D multimodal registration strategy presented is performed in a saliency space. Unlike state-of-the-art methods, the presented one takes advantage of the temporal information of the heart to construct this common space, ending up with two well-aligned modalities and regular deformation fields. This preliminary study was evaluated on heterogeneous data composed of two different datasets, healthy and pathological cases, showing similar performances in both cases. Future work will focus on testing the presented strategy in a larger dataset with a balanced number of classes.

On-line Adaptive Radiotherapy Using MRI-Guided Technique

In our institution, we installed MRI-guided radiotherapy system (MRIdian, ViewRay Inc.), allowing to perform on-line adaptive radiotherapy (ART). The MRIdian has three 60Co sources with 120 degrees apart, equipped with MRI system using a static magnetic field of 0.35 T. The tumor can be monitored and identified in real-time Cine-MRI during treatments, and gated-radiotherapy is possible based on the boundaries. On-line ART can provide the optimum delivery where high dose coverages to the tumor and sparing dose to health organs can be achieved. However, patient specific QA in on-line ART has a limitation of activities, because patients stay in the couth while planning. In this report, we summarized the commissioning of the MRIdian, and the patient specific QA established in on-line ART was described.

Remediating abnormal oral cavity motor strategies in a horn player using RT-MRI: a case study

This study uses real-time (cine) MRI to examine how orofacial myofunctional disorders (OMDs) affect muscle function during speech and horn playing. Dynamic MRI images were captured of an OMD subject and control subjects reciting a speech task and sustaining a note on an MRI-compatible horn. A following visual feedback session allowed the OMD subject to view and react to their (cine) MRI next to the image of an elite subject. Profile lines created in MATLAB allowed analysis of muscle function and changes in oral cavitation between the OMD and control subjects. In both the speech and horn films, the OMD subject consistently utilized maladaptive muscle movements, resulting in low and forward tongue position against the front teeth. Both control subjects had tongue placement free of the front teeth, and the horn control subject could elevate the tongue to narrow the air stream and play higher pitches. The MRI films suggest a connection between speech disorders and compromised horn-playing technique. OMDs limit the ability of the tongue to make the changes in oral cavitation used to play different pitches on the horn.

Validation of highly accelerated real-time cardiac cine MRI with radial k-space sampling and compressed sensing in patients at 1.5T and 3T.

To validate an optimal 12-fold accelerated real-time cine MRI pulse sequence with radial k-space sampling and compressed sensing (CS) in patients at 1.5T and 3T. We used two strategies to reduce image artifacts arising from gradient delays and eddy currents in radial k-space sampling with balanced steady-state free precession readout. We validated this pulse sequence against a standard breath-hold cine sequence in two patient cohorts: a myocardial infarction (n = 16) group at 1.5T and chronic kidney disease group (n = 18) at 3T. Two readers independently performed visual analysis of 68 cine sets in four categories (myocardial definition, temporal fidelity, artifact, noise) on a 5-point Likert scale (1 = nondiagnostic, 2 = poor, 3 = adequate or moderate, 4 = good, 5 = excellent). Another reader calculated left ventricular (LV) functional parameters, including ejection fraction. Compared with standard cine, real-time cine produced nonsignificantly different visually assessed scores, except for the following categories: 1) temporal fidelity scores were significantly lower (P = 0.013) for real-time cine at both field strengths, 2) artifacts scores were significantly higher (P = 0.013) for real-time cine at both field strengths, and 3) noise scores were significantly (P = 0.013) higher for real-time cine at 1.5T. Standard and real-time cine pulse sequences produced LV functional parameters that were in good agreement (e.g., absolute mean difference in ejection fraction <4%). This study demonstrates that an optimal 12-fold, accelerated, real-time cine MRI pulse sequence using radial k-space sampling and CS produces good to excellent visual scores and relatively accurate LV functional parameters in patients at 1.5T and 3T. Magn Reson Med 79:2745-2751, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The ratios of rolling and sliding movements of huemral head during axial rotation in the dynamic glenohumeral instability using real-time cine MRI

The ratios of rolling and sliding movements of huemral head during axial rotation in the dynamic glenohumeral instability using real-time cine MRI

Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla— Simulations and First Application

A novel method for real-time magnetic resonance imaging for the assessment of cardiac function in mice at 9.4 T is proposed. The technique combines a highly undersampled radial gradient echo acquisition with an image reconstruction utilizing both parallel imaging and compressed sensing. Simulations on an in silico phantom were performed to determine the achievable acceleration factor and to optimize regularization parameters. Several parameters characterizing the quality of the reconstructed images (such as spatial and temporal image sharpness or compartment areas) were calculated for this purpose. Subsequently, double-gated segmented cine data as well as non-gated undersampled real-time data using only six projections per timeframe (temporal resolution ∼10 ms) were acquired in a mid-ventricular slice of four normal mouse hearts in vivo. The highly accelerated data sets were then subjected to the introduced reconstruction technique and results were validated against the fully sampled references. Functional parameters obtained from real-time and fully sampled data agreed well with a comparable accuracy for left-ventricular volumes and a slightly larger scatter for mass. This study introduces and validates a real-time cine-MRI technique, which significantly reduces scan time in preclinical cardiac functional imaging and has the potential to investigate mouse models with abnormal heart rhythm.

Evaluation of highly accelerated real‐time cardiac cine MRI in tachycardia

Electrocardiogram (ECG)-gated breath-hold cine MRI is considered to be the gold standard test for the assessment of cardiac function. However, it may fail in patients with arrhythmia, impaired breath-hold capacity and poor ECG gating. Although ungated real-time cine MRI may mitigate these problems, commercially available real-time cine MRI pulse sequences using parallel imaging typically yield relatively poor spatiotemporal resolution because of their low image acquisition efficiency. As an extension of our previous work, the purpose of this study was to evaluate the diagnostic quality and accuracy of eight-fold-accelerated real-time cine MRI with compressed sensing (CS) for the quantification of cardiac function in tachycardia, where it is challenging for real-time cine MRI to provide sufficient spatiotemporal resolution. We evaluated the performances of eight-fold-accelerated cine MRI with CS, three-fold-accelerated real-time cine MRI with temporal generalized autocalibrating partially parallel acquisitions (TGRAPPA) and ECG-gated breath-hold cine MRI in 21 large animals with tachycardia (mean heart rate, 104 beats per minute) at 3T. For each cine MRI method, two expert readers evaluated the diagnostic quality in four categories (image quality, temporal fidelity of wall motion, artifacts and apparent noise) using a Likert scale (1-5, worst to best). One reader evaluated the left ventricular functional parameters. The diagnostic quality scores were significantly different between the three cine pulse sequences, except for the artifact level between CS and TGRAPPA real-time cine MRI. Both ECG-gated breath-hold cine MRI and eight-fold accelerated real-time cine MRI yielded all four scores of ≥ 3.0 (acceptable), whereas three-fold-accelerated real-time cine MRI yielded all scores below 3.0, except for artifact (3.0). The left ventricular ejection fraction (LVEF) measurements agreed better between ECG-gated cine MRI and eight-fold-accelerated real-time cine MRI (mean difference, -1.6%) than between ECG-gated cine MRI and three-fold-accelerated real-time cine MRI (mean difference, -5.7%). Eight-fold-accelerated real-time cine MRI with CS yields acceptable diagnostic quality and relatively accurate LVEF measurements in the challenging setting of tachycardia.

Novel highly accelerated real-time CINE-MRI featuring compressed sensing with k-t regularization in comparison to TSENSE segmented and real-time Cine imaging

Background In patients with breath-holding difficulties or arrhythmia, real-time CINE-MRI is preferred over segmented acquisitions in one breath-hold. However, common real-time sequences require a deteriorating trade-off between spatial and temporal resolution. In the current work, highly accelerated real-time CINE-MRI which features compressed sensing with k t regularization [1] was evaluated against segmented and real-time imaging with TSENSE in healthy volunteers as a potential alternative providing both high spatial and temporal resolution in real time.