Cine Magnetic Resonance Imaging Research Articles

C44 ATRIAL SEPTAL ABNORMALITIES: A CASE OF DOUBLE INTERATRIAL SEPTUM

Abstract The Case A 41–year–old asymptomatic male was referred to our cardiology outpatient clinic for diagnostic evaluation of a suspected bicuspid aortic valve at transthoracic echocardiography. Trans–oesophageal imaging ruled–out the bicuspid aortic valve, but detected an accessory membrane lining the interatrial septum with a double–layered appearance encompassing most of the fossa ovalis. Agitated saline infusion demonstrated an inter–atrial communication with right–to–left shunt under Valsalva manoeuvre. Cardiovascular magnetic resonance cine imaging confirmed the presence of a double interatrial septum featuring a midline recess enclosed by the two septa. Under end–expiratory breath–holding conditions, a transient right–to–left shunt was observed confirming the echocardiographic evaluation (Panel 1). No history of cerebrovascular disease and no clinical or imaging findings of right heart overload were registered. Discussion Double interatrial septum is a rare congenital condition, by morphological side, allegedly associated with an increased risk of left–sided embolic events due to blood stasis within the accessory interatrial chamber, that is often found in continuity with both atria through patent foramen ovale or additional septal fenestrations. In this case, multimodality imaging effectively was able to detect the presence of this rare atrial septal abnormality and to distinguish that from others alterations of the interatrial septum shown in the table below (Table 1). Nevertheless, the clinical significance of double interatrial septum remains uncertain, no clear relationship with embolic stroke is known and no recommendation can be made regarding the decision–making for long–term anti–thrombotic management. High quality evidences are needed to evaluate whether double atrial septum or other atrial septal abnormalities might be considered as actionable risk factors of ischemic stroke or not.

Three-dimensional sector-wise golden angle-improved k-space uniformity after electrocardiogram binning.

To develop and evaluate a 3D sector-wise golden-angle (3D-SWIG) profile ordering scheme for cardiovascular MR cine imaging that maintains high k-space uniformity after electrocardiogram (ECG) binning. Cardiovascular MR (CMR) was performed at 1.5 T. A balanced SSFP pulse sequence was implemented with a novel 3D-SWIG radial ordering, where k-space was divided into wedges, and each wedge was acquired in a separate heartbeat. The high uniformity of k-space coverage after physiological binning can be used to perform functional imaging using a very short acquisition. The 3D-SWIG was compared with two commonly used 3D radial trajectories for CMR (i.e., double golden angle and spiral phyllotaxis) in numerical simulations. Free-breathing 3D-SWIG and conventional breath-held 2D cine were compared in patients (n = 17) referred clinically for CMR. Quantitative comparison was performed based on left ventricular segmentation. Numerical simulations showed that 3D-SWIG both required smaller steps between successive readouts and achieved better k-space sampling uniformity after binning than either the double golden angle or spiral phyllotaxis trajectories. In vivo evaluation showed that measurements of left ventricular ejection fraction calculated from a 48 heart-beat free-breathing 3D-SWIG acquisition were highly reproducible and agreed with breath-held 2D-Cartesian cine (mean ± SD difference of -3.1 ± 3.5% points). The 3D-SWIG acquisition offers a simple solution for highly improved k-space uniformity after physiological binning. The feasibility of the 3D-SWIG method is demonstrated in this study through whole-heart cine imaging during free breathing with an acquisition time of less than 1 min.

Left ventricular myocardial motion tracking in cardiac cine magnetic resonance images based on a biomechanical model.

Cardiac cine magnetic resonance (CCMR) imaging plays an important role in the clinical cardiovascular disease (CVD) examination and evaluation. To accurately reconstruct the displacement field and describe the motion of the left ventricular myocardium (LVM), this study proposes and tests a new approach for tracking myocardial motion of the left ventricle based on a biomechanical model. CCMR imaging data acquired from 103 patients are enrolled, including two simulated and 101 clinical data. A non-rigid image registration method with a combination of a thin-plate spline function and random sample consensus is used to recover the observed displacement field of LVM. Next, a biomechanical model and a material matrix are introduced to solve the dense displacement field of LVM using a finite element framework. Then, the tracking precision and error of results for the two groups are analyzed. Displacement results of the simulated data show correlation coefficient≥0.876 and mean square error≤0.159, while displacement results of the clinical data show Dice≥0.97 and mean contour distance≤0.464. Additionally, the strain results show correlation coefficient≥0.717. This study demonstrates that the proposed new method enables to accurately track the motion of the LVM and evaluate strain, which has clinical auxiliary value in the diagnosis of CVD.

A bidirectional registration neural network for cardiac motion tracking using cine MRI images

Using cine magnetic resonance imaging (cine MRI) images to track cardiac motion helps users to analyze the myocardial strain, and is of great importance in clinical applications. At present, most of the automatic deep learning-based motion tracking methods compare two images without considering temporal information between MRI frames, which easily leads to the lack of consistency of the generated motion fields. Even though a small number of works take into account the temporal factor, they are usually computationally intensive or have limitations on image length. To solve this problem, we propose a bidirectional convolution neural network for motion tracking of cardiac cine MRI images. This network leverages convolutional blocks to extract spatial features from three-dimensional (3D) image registration pairs, and models the temporal relations through a bidirectional recurrent neural network to obtain the Lagrange motion field between the reference image and other images. Compared with previous pairwise registration methods, the proposed method can automatically learn spatiotemporal information from multiple images with fewer parameters. We evaluated our model on three public cardiac cine MRI datasets. The experimental results demonstrated that the proposed method can significantly improve the motion tracking accuracy. The average Dice coefficient between estimated segmentation and manual segmentation has reached almost 0.85 on the widely used Automatic Cardiac Diagnostic Challenge (ACDC) dataset.

Cine MR feature tracking analysis for diagnosing thymic epithelial tumors: a feasibility study

BackgroundTo assess the feasibility of the cine MR feature tracking technique for the evaluation of cardiovascular-induced morphological deformation in the diagnosis of thymic epithelial tumors (TETs).MethodsOur study population consisted of 43 patients with pathologically proven TETs including 10 low-grade thymomas, 23 high-grade thymomas, and 10 thymic carcinomas. Cine MR images were acquired using a balanced steady-state free precession sequence with short periods of breath-hold in the axial and oblique planes in the slice with the largest lesion cross-sectional area. The tumor margin was manually delineated in the diastolic phase and was automatically tracked for all other cardiac phases. The change rates of the long-to-short diameter ratio (∆LSR) and tumor area (∆area) associated with pulsation were compared between the three pathological groups using the Kruskal–Wallis H test and the Mann–Whitney U test. A receiver-operating characteristic (ROC) curve analysis was performed to assess the ability of each parameter to differentiate thymic carcinomas from thymomas.Results∆LSR and ∆area were significantly different among the three groups in the axial plane (p = 0.028 and 0.006, respectively) and in the oblique plane (p = 0.034 and 0.043, respectively). ∆LSR and ∆area values were significantly lower in thymic carcinomas than in thymomas in the axial plane (for both, p = 0.012) and in the oblique plane (p = 0.015 and 0.011, respectively). The area under the ROC curves for ∆LSR and ∆area for the diagnosis of thymic carcinoma ranged from 0.755 to 0.764.ConclusionsEvaluation of morphological deformation using cine-MR feature tracking analysis can help diagnose histopathological subtypes of TETs and identify thymic carcinomas preoperatively.

Respiratory-Correlated 4-Dimensional Magnetic Resonance Fingerprinting for Liver Cancer Radiation Therapy Motion Management

The objective of this study was to develop a respiratory-correlated (RC) 4-dimensional (4D) imaging technique based on magnetic resonance fingerprinting (MRF) (RC-4DMRF) for liver tumor motion management in radiation therapy. Thirteen patients with liver cancer were prospectively enrolled in this study. k-space MRF signals of the liver were acquired during free-breathing using the fast acquisition with steady-state precession sequence on a 3T scanner. The signals were binned into 8 respiratory phases based on respiratory surrogates, and interphase displacement vector fields were estimated using a phase-specific low-rank optimization method. Hereafter, the tissue property maps, including T1 and T2 relaxation times, and proton density, were reconstructed using a pyramid motion-compensated method that alternatively optimized interphase displacement vector fields and subspace images. To evaluate the efficacy of RC-4DMRF, amplitude motion differences and Pearson correlation coefficients were determined to assess measurement agreement in tumor motion between RC-4DMRF and cine magnetic resonance imaging (MRI); mean absolute percentage errors of the RC-4DMRF-derived tissue maps were calculated to reveal tissue quantification accuracy using digital human phantom; and tumor-to-liver contrast-to-noise ratio of RC-4DMRF images was compared with that of planning CT and contrast-enhanced MRI (CE-MRI) images. A paired Student t test was used for statistical significance analysis with a P value threshold of .05. RC-4DMRF achieved excellent agreement in motion measurement with cine MRI, yielding the mean (± standard deviation) Pearson correlation coefficients of 0.95 ± 0.05 and 0.93 ± 0.09 and amplitude motion differences of 1.48 ± 1.06 mm and 0.81 ± 0.64 mm in the superior-inferior and anterior-posterior directions, respectively. Moreover, RC-4DMRF achieved high accuracy in tissue property quantification, with mean absolute percentage errors of 8.8%, 9.6%, and 5.0% for T1, T2, and proton density, respectively. Notably, the tumor contrast-to-noise ratio in RC-4DMRI-derived T1 maps (6.41 ± 3.37) was found to be the highest among all tissue property maps, approximately equal to that of CE-MRI (6.96 ± 1.01, P=.862), and substantially higher than that of planning CT (2.91 ± 1.97, P=.048). RC-4DMRF demonstrated high accuracy in respiratory motion measurement and tissue properties quantification, potentially facilitating tumor motion management in liver radiation therapy.

Multi-channel deep learning model-based myocardial spatial–temporal morphology feature on cardiac MRI cine images diagnoses the cause of LVH

BackgroundTo develop a fully automatic framework for the diagnosis of cause for left ventricular hypertrophy (LVH) via cardiac cine images.MethodsA total of 302 LVH patients with cine MRI images were recruited as the primary cohort. Another 53 LVH patients prospectively collected or from multi-centers were used as the external test dataset. Different models based on the cardiac regions (Model 1), segmented ventricle (Model 2) and ventricle mask (Model 3) were constructed. The diagnostic performance was accessed by the confusion matrix with respect to overall accuracy. The capability of the predictive models for binary classification of cardiac amyloidosis (CA), hypertrophic cardiomyopathy (HCM) or hypertensive heart disease (HHD) were also evaluated. Additionally, the diagnostic performance of best Model was compared with that of 7 radiologists/cardiologists.ResultsModel 3 showed the best performance with an overall classification accuracy up to 77.4% in the external test datasets. On the subtasks for identifying CA, HCM or HHD only, Model 3 also achieved the best performance with AUCs yielding 0.895–0.980, 0.879–0.984 and 0.848–0.983 in the validation, internal test and external test datasets, respectively. The deep learning model showed non-inferior diagnostic capability to the cardiovascular imaging expert and outperformed other radiologists/cardiologists.ConclusionThe combined model based on the mask of left ventricular segmented from multi-sequences cine MR images shows favorable and robust performance in diagnosing the cause of left ventricular hypertrophy, which could be served as a noninvasive tool and help clinical decision.

Evaluation of Cardiac Function in Young Mdx Mice Using MRI with Feature Tracking and Self-Gated Magnetic Resonance Cine Imaging

This study aimed to evaluate cardiac function in a young mouse model of Duchenne muscular dystrophy (mdx) using cardiac magnetic resonance imaging (MRI) with feature tracking and self-gated magnetic resonance cine imaging. Cardiac function was evaluated in mdx and control mice (C57BL/6JJmsSlc mice) at 8 and 12 weeks of age. Preclinical 7-T MRI was used to capture short-axis, longitudinal two-chamber view and longitudinal four-chamber view cine images of mdx and control mice. Strain values were measured and evaluated from cine images acquired using the feature tracking method. The left ventricular ejection fraction was significantly less (p < 0.01 each) in the mdx group at both 8 (control, 56.6 ± 2.3% mdx, 47.2 ± 7.4%) and 12 weeks (control, 53.9 ± 3.3% mdx, 44.1 ± 2.7%). In the strain analysis, all strain value peaks were significantly less in mdx mice, except for the longitudinal strain of the four-chamber view at both 8 and 12 weeks of age. Strain analysis with feature tracking and self-gated magnetic resonance cine imaging is useful for assessing cardiac function in young mdx mice.

Intra-fraction motion of pelvic oligometastases and feasibility of PTV margin reduction using MRI guided adaptive radiotherapy.

This study assesses the impact of intra-fraction motion and PTV margin size on target coverage for patients undergoing radiation treatment of pelvic oligometastases. Dosimetric sparing of the bowel as a function of the PTV margin is also evaluated. Seven patients with pelvic oligometastases previously treated on our MR-linac (35 Gy in 5 fractions) were included in this study. Retrospective adaptive plans were created for each fraction on the daily MRI datasets using PTV margins of 5mm, 3mm, and 2mm. Dosimetric constraint violations and GTV coverage were measured as a function of PTV margin size. The impact of intra-fraction motion on GTV coverage was assessed by tracking the GTV position on the cine MR images acquired during treatment delivery and creating an intra-fraction dose distribution for each IMRT beam. The intra-fraction dose was accumulated for each fraction to determine the total dose delivered to the target for each PTV size. All OAR constraints were achieved in 85.7%, 94.3%, and 100.0% of fractions when using 5mm, 3mm, and 2mm PTV margins while scaling to 95% PTV coverage. Compared to plans with a 5mm PTV margin, there was a 27.4 ± 12.3% (4.0 ± 2.2 Gy) and an 18.5 ± 7.3% (2.7 ± 1.4 Gy) reduction in the bowel D0.5cc dose for 2mm and 3mm PTV margins, respectively. The target dose (GTV V35 Gy) was on average 100.0 ± 0.1% (99.6 - 100%), 99.6 ± 1.0% (97.2 - 100%), and 99.0 ± 1.4% (95.0 - 100%), among all fractions for the 5mm, 3mm, and 2mm PTV margins on the adaptive plans when accounting for intra-fraction motion, respectively. A 2mm PTV margin achieved a minimum of 95% GTV coverage while reducing the dose to the bowel for all patients.

SUCCESSIVE SUBSPACE LEARNING FOR CARDIAC DISEASE CLASSIFICATION WITH TWO-PHASE DEFORMATION FIELDS FROM CINE MRI.

Cardiac cine magnetic resonance imaging (MRI) has been used to characterize cardiovascular diseases (CVD), often providing a noninvasive phenotyping tool. While recently flourished deep learning based approaches using cine MRI yield accurate characterization results, the performance is often degraded by small training samples. In addition, many deep learning models are deemed a "black box," for which models remain largely elusive in how models yield a prediction and how reliable they are. To alleviate this, this work proposes a lightweight successive subspace learning (SSL) framework for CVD classification, based on an interpretable feedforward design, in conjunction with a cardiac atlas. Specifically, our hierarchical SSL model is based on (i) neighborhood voxel expansion, (ii) unsupervised subspace approximation, (iii) supervised regression, and (iv) multi-level feature integration. In addition, using two-phase 3D deformation fields, including end-diastolic and end-systolic phases, derived between the atlas and individual subjects as input offers objective means of assessing CVD, even with small training samples. We evaluate our framework on the ACDC2017 database, comprising one healthy group and four disease groups. Compared with 3D CNN-based approaches, our framework achieves superior classification performance with 140× fewer parameters, which supports its potential value in clinical use.

Application of Magnetic Resonance Strain Analysis Using Feature Tracking in a Myocardial Infarction Model

This study validates the usefulness of myocardial strain analysis with cardiac cine magnetic resonance imaging (MRI) by evaluating the changes in the cardiac function and myocardial strain values longitudinally in a myocardial disease model. Six eight-week-old male Wistar rats were used as a model of myocardial infarction (MI). Cine images were taken in the short axis, two-chamber view longitudinal axis, and four-chamber view longitudinal axis directions in rats 3 and 9 days after MI and in control rats, with preclinical 7-T MRI. The control images and the images on days 3 and 9 were evaluated by measuring the ventricular ejection fraction (EF) and the strain values in the circumferential (CS), radial (RS), and longitudinal directions (LS). The CS decreased significantly 3 days after MI, but there was no difference between the images on days 3 and 9. The two-chamber view LS was -9.7 ± 2.1% at 3 days and -13.9 ± 1.4% at 9 days after MI. The four-chamber view LS was -9.9 ± 1.5% at 3 days and -11.9 ± 1.3% at 9 days after MI. Both the two- and four-chamber LS values were significantly decreased 3 days after MI. Myocardial strain analysis is, therefore, useful for assessing the pathophysiology of MI.

An Image-Based Computational Fluid Dynamics Study of Mitral Regurgitation in Presence of Prolapse.

In this work we performed an imaged-based computational study of the systolic fluid dynamics in presence of mitral valve regurgitation (MVR). In particular, we compared healthy and different regurgitant scenarios with the aim of quantifying different hemodynamic quantities. We performed computational fluid dynamic (CFD) simulations in the left ventricle, left atrium and aortic root, with a resistive immersed method, a turbulence model, and with imposed systolic wall motion reconstructed from Cine-MRI images, which allowed us to segment also the mitral valve. For the regurgitant scenarios we considered an increase of the heart rate and a dilation of the left ventricle. Our results highlighted that MVR gave rise to regurgitant jets through the mitral orifice impinging against the atrial walls and scratching against the mitral valve leading to high values of wall shear stresses (WSSs) with respect to the healthy case. CFD with prescribed wall motion and immersed mitral valve revealed to be an effective tool to quantitatively describe hemodynamics in case of MVR and to compare different regurgitant scenarios. Our findings highlighted in particular the presence of transition to turbulence in the atrium and allowed us to quantify some important cardiac indices such as cardiac output and WSS.

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.

Cardiac cine with compressed sensing real-time imaging and retrospective motion correction for free-breathing assessment of left ventricular function and strain in clinical practice.

Free-breathing cardiac cine magnetic resonance imaging (MRI) comparable to the traditional breath-hold 2D segmented cine imaging (SegBH) is clinically required for cardiac function and strain analysis. This study is to assess the feasibility and accuracy of a free-breathing cardiac cine technique (RTCSCineMoCo) combined with highly accelerated real-time acquisition, compressed sensing, and fully automated non-rigid motion correction for left ventricular (LV) function and strain analysis, using SegBH as the reference and comparing with free-breathing single-shot real-time compressed sensing cine imaging (RTCSCine) without motion correction. A total of 67 patients scheduled for clinical cardiac MRI were included. Cine images were acquired using three techniques (SegBH, RTCSCineMoCo, RTCSCine) consecutively at 3.0 T. LV functional parameters, including ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), stroke volumes (SV), and LV mass (LVM) were measured and compared. Strain parameters including global radial (GRS), circumferential (GCS), and longitudinal (GLS) strain as well as corresponding time to peak strain (TPS) were computed by magnetic resonance (MR) feature tracking and compared. Subgroup analyses were performed according to heart rate (HR), left ventricular ejection fraction (LVEF), and etiology. All quantitative parameters of LV function and strain measured by RTCSCineMoCo (r≥0.766) and RTCSCine (r≥0.712) showed strong correlations with SegBH (all P<0.001). LV functional parameters were not statistically different between RTCSCineMoCo and SegBH (all P>0.05), but an overestimation of LV end-systolic volume (LVESV) and underestimation of LVEF and LVM were observed using RTCSCine (all P<0.001). GRS, GCS, and GLS by RTCSCineMoCo and RTCSCine were significantly different than those by SegBH (all P<0.05). All TPS values by RTCSCineMoCo showed no significant differences (all P>0.05) compared with SegBH, but TPS in longitudinal directions (TPSL) by RTCSCine was significantly different (P=0.011). There were no significant differences for GRS or GCS between RTCSCineMoCo and SegBH in patients with HR <70 bpm or LVEF <50%. GRS by RTCSCineMoCo showed similar results compared to SegBH in patients with pulmonary hypertension. RTCSCineMoCo is a promising method for robust free-breathing cardiac cine imaging, yielding more precise quantitative analytic results for LV function compared with RTCSCine. RTCSCineMoCo mildly underestimated GRS, GCS, and GLS, but showed smaller bias compared to RTCSCine in LV strain analysis.

Real-time motion monitoring using orthogonal cine MRI during MR-guided adaptive radiation therapy for abdominal tumors on 1.5T MR-Linac.

Real-time motion monitoring (RTMM) is necessary for accurate motion management of intrafraction motions during radiation therapy (RT). Building upon a previous study, this work develops and tests an improved RTMM technique based on real-time orthogonal cine magnetic resonance imaging (MRI) acquired during magnetic resonance-guided adaptive RT (MRgART) for abdominal tumors on MR-Linac. A motion monitoring research package (MMRP) was developed and tested for RTMM based on template rigid registration between beam-on real-time orthogonal cine MRI and pre-beam daily reference 3D-MRI (baseline). The MRI data acquired under free-breathing during the routine MRgART on a 1.5T MR-Linac for 18 patients with abdominal malignancies of 8 liver, 4 adrenal glands (renal fossa) and 6 pancreas cases were used to evaluate the MMRP package. For each patient, a 3D mid-position image derived from an in-house daily 4D-MRI was used to define a target mask or a surrogate sub-region encompassing the target. Additionally, an exploratory case reviewed for an MRI dataset of a healthy volunteer acquired under both free-breathing and deep inspiration breath-hold (DIBH) was used to test how effectively the RTMM using the MMRP can address through-plane motion (TPM). For all cases, the 2D T2/T1-weighted cine MRIs were captured with a temporal resolution of 200 ms interleaved between coronal and sagittal orientations. Manually delineated contours on the cine frames were used as the ground-truth motion. Common visible vessels and segments of target boundaries in proximity to the target were used as anatomical landmarks for reproducible delineations on both the 3D and the cine MRI images. Standard deviation of the error (SDE) between the ground-truth and the measured target motion from the MMRP package were analyzed to evaluate the RTMM accuracy. The maximum target motion (MTM) was measured on the 4D-MRI for all cases during free-breathing. The mean (range) centroid motions for the 13 abdominal tumor cases were 7.69 (4.71-11.15), 1.73 (0.81-3.05), and 2.71 (1.45-3.93) mm with an overall accuracy of <2 mm in the superior-inferior (SI), the left-right (LR), and the anterior-posterior (AP) directions, respectively. The mean (range) of the MTM from the 4D-MRI was 7.38 (2-11) mm in the SI direction, smaller than the monitored motion of centroid, demonstrating the importance of the real-time motion capture. For the remaining patient cases, the ground-truth delineation was challenging under free-breathing due to the target deformation and the large TPM in the AP direction, the implant-induced image artifacts, and/or the suboptimal image plane selection. These cases were evaluated based on visual assessment. For the healthy volunteer, the TPM of the target was significant under free-breathing which degraded the RTMM accuracy. RTMM accuracy of <2 mm was achieved under DIBH, indicating DIBH is an effective method to address large TPM. We have successfully developed and tested the use of a template-based registration method for an accurate RTMM of abdominal targets during MRgART on a 1.5T MR-Linac without using injected contrast agents or radio-opaque implants. DIBH may be used to effectively reduce or eliminate TPM of abdominal targets during RTMM. This article is protected by copyright. All rights reserved.

Thymoma: a rare cause for an intracardiac tumour.

A 56-year-old man presented with superior vena cava syndrome after recovery from severe COVID-19. Chest X-rays showed multiple bilateral pulmonary nodules (Panel A). A transthoracic echocardiogram revealed a mass in the right atrium of 54 × 31 mm, that protruded through the tricuspid valve and generated an obstructive gradient of 15 mmHg (Panel B; Supplementary Video 1). Contrast-enhanced chest computed tomography (CT) showed multiple pulmonary nodules (Panel C), and an intravascular extension of the intracardiac mass, deep into the innominate veins (Panels D and E). Volume 3D rendering CT showed extensive collateral venous circulation (Panel F). Steady-state free precession cine magnetic resonance imaging sequence showed an isointense mass with hyperintense areas in the right atrium, that measured 6.8 × 6.3 × 3.8 cm and prolapsed through the tricuspid valve (Panel G; Supplementary Video 2). The intracardiac mass was T1- and T2-weighted hyperintense (Panels H and I). Additionally, a mediastinum mass of 25 × 26 mm was found, with similar characteristics than the intracardiac mass.

Swallowing analysis in hemi-tongue reconstruction using motor-innervated free flaps: A cine-magnetic resonance imaging study.

This study aimed to explore the outcomes of motor-innervated free flaps in hemi-tongue reconstruction by assessing the tongue mobility through midsagittal images from cine-magnetic resonance imaging. In this retrospective study, 47 patients who underwent tongue reconstruction following hemi-glossectomy and 10 control subjects without any surgical history were included. Patients were classified into two groups: the motor and no-motor innervation group. Various spatial parameters related to tongue mobility that were acquired from midsagittal sections were compared during consecutive swallowing phases. Overall, the motor group showed improved functional swallowing scale compared with the no-motor group. In case of tongue base resection, the motor group showed improved mobility of the tongue base during pharyngeal phase, whereas the no-motor group showed increased laryngeal elevation for compensatory movement. The tongue reconstruction with motor-innervated free flaps may facilitate swallowing capacity in patients with a hemi-tongue defect combined with tongue base resection.

Comparison between pre- and post-contrast cardiac MRI cine images: the impact on ventricular volume and strain measurement.

To explore whether contrast agent administration will affect ventricular volume and strain parameters measured on cardiac magnetic resonance cine images. This prospective study enrolled 88 patients, including 32 patients with cardiac amyloidosis (CA), 32 patients with hypertrophic cardiomyopathy (HCM), and 24 control participants, to perform steady-state free precession (SSFP)-cine imaging twice, respectively before and after contrast agent injection. Indexed left and right ventricular (LV and RV) volume and LV strain parameters (peak radial strain [PRS], peak circumferential strain [PCS], peak longitudinal strain [PLS]) were analyzed and compared between the pre- and post-contrast cine groups. Compared to the group of pre-contrast cine, the end-diastolic volume index (EDVi) and end-systolic volume index (ESVi) significantly increased in the group using post-contrast cine images (all p < 0.05), especially in the right ventricle. After contrast injection, the right ventricular ejection fraction (RVEF) decreased significantly (p < 0.05), while the left ventricular ejection fraction (LVEF) only reduced for patients with HCM (p < 0.05). The PRS (37.1 ± 15.2 vs. 32.0 ± 15.4, p < 0.001) and PCS (-14.9 ± 4.3 vs. -14.0 ± 4.1, p < 0.001) derived from post-contrast cine images reduced significantly in all patients and this tendency remained in subgroup analysis except for PCS in the control group. The administration of a contrast agent may influence the measurements of ventricular volume and strain. Acquiring pre-contrast cine images were suggested for patients who required more accurate right ventricle evaluation or precise strain assessment.

Commissioning, clinical implementation, and initial experience with a new brain tumor treatment package on a low-field MR-linac.

To evaluate the image quality, dosimetric properties, setup reproducibility, and planar cine motion detection of a high-resolution brain coil and integrated stereotactic brain immobilization system that constitute a new brain treatment package (BTP) on a low-field magnetic resonance imaging (MRI) linear accelerator (MR-linac). Image quality of the high-resolution brain coil was evaluated with the 17cm diameter spherical phantom and the American College of Radiology (ACR) Large MRI Phantom. Patient imaging studies approved by the institutional review board (IRB) assisted in selecting image acquisition parameters. Radiographic and dosimetric evaluation of the high-resolution brain coil and the associated immobilization devices was performed using dose calculations and ion chamber measurements. End-to-end testing was performed simulating a cranial lesion in a phantom. Inter-fraction setup variability and motion detection tests were evaluated on four healthy volunteers. Inter-fraction variability was assessed based on three repeat setups for each volunteer. Motion detection was evaluated using three-plane (axial, coronal, and sagittal) MR-cine imaging sessions, where volunteers were asked to perform a set of specific motions. The images were post-processed and evaluated using anin-house program. Contrast resolution of the high-resolution brain coil is superior to the head/neck and torso coils. The BTP receiver coils have an average HU value of 525 HU. The most significant radiation attenuation (3.14%) of the BTP, occurs through the lateral portion of the overlay board where the high-precision lateral-profile mask clips attach to the overlay. The greatest inter-fraction setup variability occurred in the pitch (average 1.08 degree) and translationally in the superior/inferior direction (average 4.88mm). Three plane cine imaging with the BTP was able to detect large and small motions. Small voluntary motions, sub-millimeter in magnitude (maximum 0.9mm), from motion of external limbs were detected. Imaging tests, inter-fraction setup variability, attenuation, and end-to-end measurements were quantified and performed for the BTP. Results demonstrate better contrast resolution and low contrast detectability that allows for better visualization of soft tissue anatomical changes relative to head/neck and torso coil systems.

Papillary Muscle Involvement during Acute Myocardial Infarction: Detection by Cardiovascular Magnetic Resonance Using T1 Mapping Technique and Papillary Longitudinal Strain

Papillary muscle (PPM) involvement in myocardial infarction (MI) increases the risk of secondary mitral valve regurgitation or PPM rupture and may be diagnosed using late gadolinium enhancement (LGE) imaging. The native T1-mapping (nT1) technique and PPM longitudinal strain (PPM-ls) have been used to identify PPM infarction (iPPM) without the use of the contrast agent. This study aimed to assess the diagnostic performance of nT1 and PPM-ls in the identification of iPPM. Forty-six patients, who performed CMR within 14-30 days after MI, were retrospectively enrolled: sixteen showed signs of iPPM on LGE images. nT1 values were measured within the infarcted area (IA), remote myocardium (RM), blood pool (BP), and anterolateral and posteromedial PPMs and compared using ANOVA. PPM-ls values have been assessed on cineMR images as the percentage of shortening between end-diastolic and end-systolic phases. Higher nT1 values and lower PPM-ls were found in infarcted compared to non-infarcted PPMs (nT1: 1219.3 ± 102.5 ms vs. 1052.2 ± 80.5 ms and 17.6 ± 6.3% vs. 21.6 ± 4.3%; p-value < 0.001 for both), with no significant differences between the nT1 of infarcted PPMs and IA and between the non-infarcted PPMs and RM. ROC analysis demonstrated an excellent discriminatory power for nT1 in detecting the iPPM (AUC = 0.874; 95% CI: 0.784-0.963; p < 0.001). nT1 and PPM-ls are valid tools in assessing iPPM with the advantage of avoiding contrast media administration.