Clinical Cardiac Magnetic Resonance Imaging Research Articles

Test-retest repeatability of myocardial radiomic features from quantitative cardiac magnetic resonance T1 and T2 mapping

Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance.The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps.A representative group of 24 subjects (mean age 54 ± 18 years) referred for clinical cardiac MR imaging were enrolled in the study. For each subject, T1 and T2 mapping through MOLLI and T2-prepared TrueFISP acquisition sequences, respectively, were performed at 1.5 T. Then, 98 radiomic features of different classes (shape, first-order, second-order) were extracted from a region of interest encompassing the whole left ventricle myocardium in a short axis slice. The repeatability was assessed performing different and complementary analyses: intraclass correlation coefficient (ICC) and limits of agreement (LOA) (i.e., the interval within which 95% of the percentage differences between two repeated measures are expected to lie).Radiomic features were characterized by a relatively wide range of repeatability degree in terms of both ICC and LOA. Overall, 44.9% and 38.8% of radiomic features showed ICC values > 0.75 for T1 and T2 maps, respectively, while 25.5% and 23.4% of radiomic features showed LOA between ±10%. A subset of radiomic features for T1 (Mean, Median, 10Percentile, 90Percentile, RootMeanSquared, Imc2, RunLengthNonUniformityNormalized, RunPercentage and ShortRunEmphasis) and T2 (MaximumDiameter, RunLengthNonUniformityNormalized, RunPercentage, ShortRunEmphasis) maps presented both ICC > 0.75 and LOA between ±5%.Overall, radiomic features extracted from T1 maps showed better repeatability performance than those extracted from T2 maps, with shape features characterized by better repeatability than first-order and textural features. Moreover, only a limited subset of 9 and 4 radiomic features for T1 and T2 maps, respectively, showed high repeatability degree in terms of both ICC and LOA. These results confirm the importance of assessing test-retest repeatability degree in radiomic feature estimation and might be useful for a more effective/reliable use of myocardial T1 and T2 mapping radiomics in clinical or research studies.

Technical Note: Swing golden angle - A navigator-interleaved golden angle trajectory with eddy current suppression - Application in free-running cardiac MRI.

Golden angle (GA) radial trajectory is advantageous for dynamic magnetic resonance imaging (MRI). Recently, several advanced algorithms have been developed based on navigator-interleaved GA trajectory to realize free-running cardiac MRI. However, navigator-interleaved GA trajectory suffers from the eddy-current effect, which reduces the image quality. This work aims to integrate the navigator-interleaved GA trajectory with clinical cardiac MRI acquisition, with the minimum eddy-current artifacts. The ultimate goal is to realize a high-quality free-running cardiac imaging technique. In this paper, we propose a new "swing golden angle" (swingGA) radial profile order. SwingGA samples the k-space by rotating back and forth at the generalized golden ratio interval, with smoothly interleaved navigator readouts. The sampling efficiency and angle increment distributions were investigated by numerical simulations. Static phantom imaging experiments were conducted to evaluate the eddy current effect, compared with cartesian, golden angle radial (GA), and tiny golden angle (tGA) trajectories. Furthermore, 12 heart-healthy subjects (aged 21-25years) were recruited for free-running cardiac imaging with different sampling trajectories. Dynamic images were reconstructed by a low-rank subspace-constrained algorithm. The image quality was evaluated by signal-to-noise-ratio and spectrum analysis in the heart region, and compared with traditional clinical cardiac MRI images. SwingGA pattern achieves the highest sampling efficiency (mSE>0.925) and the minimum azimuthal angle increment (mAD<1.05). SwingGA can effectively suppress eddy currents in static phantom images, with the lowest normalized root mean square error (nRMSE) values among radial trajectories. For the in-vivo cardiac images, swingGA enjoys the highest SNR both in the blood pool and myocardium, and contains the minimum level of high-frequency artifacts. The free-running cardiac images have good consistency with traditional clinical cardiac MRI, and the swingGA sampling pattern achieves the best image quality among all sampling patterns. The proposed swingGA sampling pattern can effectively improve the sampling efficiency and reduce the eddy currents for the navigator-interleaved GA sequence. SwingGA is a promising sampling pattern for free-running cardiac MRI.

A predictive signal model for dynamic cardiac magnetic resonance imaging

Robust dynamic cardiac magnetic resonance imaging (MRI) has been a long-standing endeavor—as real-time imaging can provide information on the temporal signatures of disease we currently cannot assess—with the past decade seeing remarkable advances in acceleration using compressed sensing (CS) and artificial intelligence (AI). However, substantial limitations to real-time imaging remain and reconstruction quality is not always guaranteed. To improve reconstruction fidelity in dynamic cardiac MRI, we propose a novel predictive signal model that uses a priori statistics to adaptively predict temporal cardiac dynamics. By using a small training set obtained from the same patient, the new signal model can achieve robust dynamic cardiac MRI in the presence of irregular cardiac rhythm. Evaluation on simulated irregular cardiac dynamics and prospectively undersampled clinical cardiac MRI data demonstrate improved reconstruction quality for two reconstruction frameworks: Kalman filter and CS. The predictive model also works with different undersampling patterns (cartesian, radial, spiral) and can serve as a versatile foundation for robust dynamic cardiac MRI.

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.

GMCNet: A Generative Multi-Resolution Framework for Cardiac Registration

Deformable image registration plays a crucial role in estimating cardiac deformation from a sequence of images. However, existing registration methods primarily process images as pairs instead of processing all images in a sequence together. This study proposes a novel end-to-end learning-free generative multi-resolution convolutional neural network (GMCNet) with the primary focus of registering images in a sequence. Even though learning-based methods have yielded high performance for image registration, their performance depends on their ability to learn information from a large number of samples which are difficult to obtain and might bias the framework to the specific domain of data. The proposed learning-free method eliminates the need for a dedicated training set while exploiting the capabilities of neural networks to achieve accurate deformation fields. Due to its capability of parameter sharing through the architecture, the GMCNet can be used as a groupwise registration as well as pairwise registration. The proposed method was evaluated on three different clinical cardiac magnetic resonance imaging datasets and compared quantitatively against nine other state-of-the-art learning and optimization-based algorithms. The proposed method outperformed other methods in all comparisons and yielded average Dice metric values ranging from 0.85 to 0.88 for the datasets. Different aspects of the GMCNet are also explored by assessing 1) the robustness; 2) performance on pairwise registration; 3) the influence of spatial transformation in a controlled environment; and 4) the impact of different multi-resolution structures. The results demonstrate that using temporal information to estimate the deformation fields leads to more accurate registration results and improved robustness under different noise levels. Moreover, the proposed method does not need images for training, and therefore, its prediction is not domain-specific and can be applied to any sequence of images.

Correlation between Volumes Determined by Echocardiography and Cardiac MRI in Controls and Atrial Fibrillation Patients.

Aims: We aimed to compare cardiac volumes measured with echocardiography (echo) and cardiac magnetic resonance imaging (MRI) in a mixed cohort of healthy controls (controls) and patients with atrial fibrillation (AF). Materials and methods: In total, 123 subjects were included in our study; 99 full datasets were analyzed. All the participants underwent clinical evaluation, EKG, echo, and cardiac MRI acquisition. Participants with full clinical data were grouped into 63 AF patients and 36 controls for calculation of left atrial volume (LA Vol) and 51 AF patients and 30 controls for calculation of left ventricular end-diastolic volume (LV EDV), end-systolic volume (ESV), and LV ejection fraction (LV EF). Results: No significant differences in LA Vol were observed (p > 0.05) when measured by either echo or MRI. However, echo provided significantly lower values for left ventricular volume (p < 0.0001). The echo LA Vol of all the subjects correlated well with that measured by MRI (Spearmen correlation coefficient r = 0.83, p < 0.0001). When comparing the two methods, significant positive correlations of EDV (all subjects: r = 0.55; Controls: r = 0.71; and AF patients: r = 0.51) and ESV (all subjects: r = 0.62; Controls: r = 0.47; and AF patients: r = 0.66) were found, with a negative bias for values determined using echo. For a subgroup of participants with ventricular volumes smaller than 49.50 mL, this bias was missing, thus in this case echocardiography could be used as an alternative for MRI. Conclusion: Good correlation and reduced bias were observed for LA Vol and EF determined by echo as compared to cardiac MRI in a mixed cohort of patients with AF and healthy volunteers. For the determination of volume values below 49.50 mL, an excellent correlation was observed between values obtained using echo and MRI, with comparatively reduced bias for the volumes determined by echo. Therefore, in certain cases, echocardiography could be used as a less expensive, less time-consuming, and contraindication free alternative to MRI for cardiac volume determination.

Semiquantitative characterization of dynamic magnetic resonance perfusion of the liver in pediatric Fontan patients.

Dynamic contrast-enhanced magnetic resonance imaging (MRI) of the liver in pediatric Fontan patients often shows peripheral reticular areas of hypoenhancement, which has not been studied in detail. To semiquantitatively score the hepatic MR perfusion abnormality seen in pediatric Fontan patients, and to correlate the perfusion abnormality with functional clinical and hemodynamic parameters. All children (< 18years old) after Fontan palliation with combined clinical cardiac and liver MRI performed between May 2017 and April 2019 were considered for inclusion. A semiquantitative perfusion score was used to assess the severity of the hepatic reticular pattern seen on dynamic contrast-enhanced liver imaging. The liver was divided into four sections: right posterior, right anterior, left medial and left lateral. Each liver section was assigned a score from 0 to 4 depending on the amount of abnormal reticular hypoenhancement. Scoring was assigned for each section of the liver across eight successive dynamic contrast-enhanced modified spoiled gradient echo runs. Scores were correlated with clinical and hemodynamic parameters. All Fontan children showed hepatic reticular hypoenhancement by MRI, most severe in the early portal venous phase with a median maximum total perfusion abnormality score of 12 (range: 9-14). All perfusion abnormalities progressively resolved during the hepatic venous phase. Perfusion abnormality scores were greatest in the right compared to left hepatic lobes (7 range: [6-8] vs. 5 [range: 3-6], P < 0.01). The maximum left hepatic lobe perfusion abnormality scores were greatest in children with versus without imaging signs of portal hypertension (8 [range: 7-8] vs. 4 [range: 3-5], P < 0.01). High unconjugated bilirubin and low platelets correlated with greater perfusion abnormality (R = 0.450, P = 0.024, and R = - 0.458, P < 0.01, respectively). Age at MRI, time from Fontan, focal liver lesions and cardiac MRI hemodynamic parameters did not show significant correlations with the severity of the liver perfusion abnormality. All Fontan children have hepatic reticular hypoenhancement abnormalities seen with MRI that are most severe in the right hepatic lobe and universally show gradual resolution through the hepatic venous phase. Perfusion abnormality in the left hepatic lobe is worse in children with portal hypertension.

Cardiac magnetic resonance imaging in patients with Beh\xe7et's disease

BackgroundBehçet’s disease (BD) is a multisystemic vasculitis that may affect the heart. However, the incidence and nature of cardiac involvement in BD have not been clearly documented yet. The aim of this study was to delineate the cardiac magnetic resonance imaging (MRI) appearances of cardiac involvement in BD patients.MethodsThis cross-sectional observational study was carried out 30 BD patients without known cardiac disease. Patients were subjected to history taking, physical examination, echocardiography and cardiac MRI.ResultsAt least one abnormality on cardiac MRI was observed in 20/30 patients (66.67%). Myocardial oedema was observed in 3 patients (10%) and late gadolinium enhancement in 1 patient (3.3%). Pericardial effusion was found in 3 patients (10.0%), global hypokinesia in 6 patients (20.0%) and intra-cardiac thrombosis in only 1 patient (3.3%). Pulmonary artery was dilated in 4 patients (13.3%). Left ventricular (LV) and right ventricular (RV) end diastolic volume were altered in 4 patients (13.3%) and 7 patients (23.3%) respectively. LV and RV end systolic volume were abnormal in 7 patients (23.3%) and 5 patients (16.7%) respectively. There was aortic valve regurge in 2 patients (6.7%), tricuspid valve regurge in 9 patients (30%), and mitral valve regurge in 9 patients (30%). Dilated left main coronary artery was found in 2 patients (6.7%) and arrhythmogenic right ventricular dysplasia in only one patient 1 patient (3.3%). On logistic regression analysis, BD activity index score was a significant predictor of cardiac abnormalities.ConclusionBD may cause cardiac abnormalities without clinical manifestations and cardiac MRI may represent a tool for early detection of these subtle abnormalities. Higher BD activity index scores are strongly linked to cardiac problems.

Implementation and prospective clinical validation of AI‐based planning and shimming techniques in cardiac MRI

PurposeCardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce image acquisition time without compromising image quality (IQ), and improve magnetic field uniformity. Here, we aim to implement two AI‐based deep learning techniques for automatic slice alignment and cardiac shimming and evaluate their performance in clinical cardiac magnetic resonance imaging (MRI).MethodsTwo deep neural networks were developed, trained, and validated on pre‐acquired cardiac MRI datasets (>500 subjects) to achieve automatic slice planning and shimming (implemented in the scanner) for CMR. To examine the performance of our automated cardiac planning (EasyScan) and AI‐based shim (AI shim), two prospective studies were performed subsequently. For the EasyScan validation, 10 healthy subjects underwent two identical CMR protocols: with manual cardiac planning and with AI‐based EasyScan to assess protocol scan time difference and accuracy of cardiac plane prescriptions on a 1.5 T clinical MRI scanner. For the AI shim validation, a total of 20 subjects were recruited: 10 healthy and 10 cardio‐oncology patients with referrals for a CMR examination. Cine images were obtained with standard cardiac volume shim and with AI shim to assess signal‐to‐noise ratio (SNR), contrast‐to‐noise ratio (CNR), overall IQ (sharpness and MR image degradation), ejection fraction (EF), and absolute wall thickening. A hybrid statistical method using of nonparametric (Wilcoxon) and parametric (t‐test) assessments was employed for statistical analyses.ResultsCMR protocol with AI‐based plane prescriptions, EasyScan, minimized operator dependence and reduced overall scanning time by over 2 min (∼13 % faster, p < 0.001) compared to the protocol with manual cardiac planning. EasyScan plane prescriptions also demonstrated more accurate (less plane angulation errors from planes manually prescribed by a certified cardiac MRI technologist) cardiac planes than previously reported strategies. Additionally, AI shim resulted in improved B0 field homogeneity. Cine images obtained with AI shim revealed a significantly higher SNR (12.49%; p = 0.002) than those obtained with volume shim (volume shim: 32.90 ± 7.42 vs. AI shim: 37.01 ± 8.87) for the left ventricle (LV) myocardium. LV myocardium CNR was 12.48% higher for cine imaging with AI shim (149.02 ± 39.15) than volume shim (132.49 ± 33.94). Images obtained with AI shim resulted in sharper images than those obtained with volume shim (p = 0.012). The LVEF and absolute wall thickening also showed that differences exist between the two shimming methods. The LVEF by AI shim was shown to be slightly larger than LVEF by volume shim in two groups: 2.87% higher with AI shim for the healthy group and 1.70% higher with AI shim for the patient group. The LV absolute wall thickening (in mm) also showed that differences exist between shimming methods for each group with larger changes observed in the patient group (healthy: 3.31%, p = 0.234 and patient group: 7.29%, p = 0.059).ConclusionsCMR exams using EasyScan for cardiac planning demonstrated accelerated cardiac exam compared to the CMR protocol with manual cardiac planning. Improved and more uniform B0 magnetic field homogeneity also achieved using AI shim technique compared to volume shimming.

Abstract 10622: Z Scores in Pediatric Cardiac Magnetic Resonance: Reclassification of Smaller, Younger Hearts with Novel Calculator

Introduction: The use of z scores to describe growth of normal structures is necessary in the management of pediatric cardiac disorders, particularly in babies and toddlers. Z score calculators for cardiac magnetic resonance (CMR) have traditionally relied on a convenience sample given complexity of the test. A recently published, novel z score calculator from prospectively-imaged, awake, healthy children ages 0-12 years may add value to assessments of ventricular size compared to traditional calculators. Hypothesis: A novel z score calculator (“Olivieri et al”) with robust prediction in younger, smaller children may reclassify right and left ventricular end diastolic volumes and mass (RVEDV, LVEDV, LVM) compared to the traditional calculator (“Buechel et al”). Methods: A retrospective cohort of subjects less than 12 years of age who underwent clinical CMR imaging on a 1.5T scanner (n=96; median age 5.5 years (IQR 3.7-7.6 years); 42% female) was studied. Z scores were calculated using both novel and traditional models for RVEDV, LVEDV and LVM. Subjects were categorized into the agreement group (both calculators agree) or disagreement groups, where novel calculator reclassified to normal (z&lt; ± 2) or abnormal (z&gt; ±2). Reclassified subject characteristics were compared with ANOVA and t-test. Results: Novel and traditional z scores agreed for 77%, 58% and 62% of cases for RVEDV, LVEDV and LVM, respectively. Amongst disagreements, subjects reclassified from abnormal to normal by the novel calculator had significantly lower age, BSA and RV size (Table 1). Reclassified subjects showed no association with specific diagnoses. Conclusion: The novel z score calculator reclassifies younger, smaller children away from severe z scores into more normal z scores. Ventricular volume assessment is highly relevant to critical decision-making in the first years of life in borderline lesions.

Impact of Field Strength in Clinical Cardiac Magnetic Resonance Imaging.

Cardiac magnetic resonance imaging (MRI) is widely applied for the noninvasive assessment of cardiac structure and function, and for tissue characterization. For more than 2 decades, 1.5 T has been considered the field strength of choice for cardiac MRI. Although the number of 3-T systems significantly increased in the past 10 years and numerous new developments were made, challenges seem to remain that hamper a widespread clinical use of 3-T MR systems for cardiac applications. As the number of clinical cardiac applications is increasing, with each having their own benefits at both field strengths, no "holy grail" field strength exists for cardiac MRI that one should ideally use. This review describes the physical differences between 1.5 and 3 T, as well as the effect of these differences on major (routine) cardiac MRI applications, including functional imaging, edema imaging, late gadolinium enhancement, first-pass stress perfusion, myocardial mapping, and phase contrast flow imaging. For each application, the advantages and limitations at both 1.5 and 3 T are discussed. Solutions and alternatives are provided to overcome potential limitations. Finally, we briefly elaborate on the potential use of alternative field strengths (ie, below 1.5 T and above 3 T) for cardiac MRI and conclude with field strength recommendations for the future of cardiac MRI.

Inference of ventricular activation properties from non-invasive electrocardiography

The realisation of precision cardiology requires novel techniques for the non-invasive characterisation of individual patients’ cardiac function to inform therapeutic and diagnostic decision-making. Both electrocardiography and imaging are used for the clinical diagnosis of cardiac disease. The integration of multi-modal datasets through advanced computational methods could enable the development of the cardiac ‘digital twin’, a comprehensive virtual tool that mechanistically reveals a patient's heart condition from clinical data and simulates treatment outcomes. The adoption of cardiac digital twins requires the non-invasive efficient personalisation of the electrophysiological properties in cardiac models. This study develops new computational techniques to estimate key ventricular activation properties for individual subjects by exploiting the synergy between non-invasive electrocardiography, cardiac magnetic resonance (CMR) imaging and modelling and simulation. More precisely, we present an efficient sequential Monte Carlo approximate Bayesian computation-based inference method, integrated with Eikonal simulations and torso-biventricular models constructed based on clinical CMR imaging. The method also includes a novel strategy to treat combined continuous (conduction speeds) and discrete (earliest activation sites) parameter spaces and an efficient dynamic time warping-based ECG comparison algorithm. We demonstrate results from our inference method on a cohort of twenty virtual subjects with cardiac ventricular myocardial-mass volumes ranging from 74 cm3 to 171 cm3 and considering low versus high resolution for the endocardial discretisation (which determines possible locations of the earliest activation sites). Results show that our method can successfully infer the ventricular activation properties in sinus rhythm from non-invasive epicardial activation time maps and ECG recordings, achieving higher accuracy for the endocardial speed and sheet (transmural) speed than for the fibre or sheet-normal directed speeds.

Quantitative Clinical Cardiac Magnetic Resonance Imaging.

Cardiac magnetic resonance imaging (MRI) represents the established reference standard method for the assessment of cardiac function and non-invasive evaluation of myocardial tissue in a variety of clinical questions, wherein quantification of cardiac parameters gains growing diagnostic and differential-diagnostic importance. This review aims to summarize established and newly emerging quantitative parameters, which are assessed in routine cardiac MRI. Interrelations and interdependencies between metrics are explained, and common factors affecting quantitative results are discussed. The review is based on a PubMed literature research using the search terms "cardiac magnetic resonance" and "quantification", "recommendations", "quantitative evaluation/assessment", "reference method", "reference/normal values", "pitfalls" or "artifacts" published between 2000-2019. Quantitative functional, phase contrast, and perfusion imaging, as well as relaxation time mapping techniques give opportunity for assessment of a large number of quantitative cardiac MRI parameters in clinical routine. Application of these techniques allows for characterization of function, morphology and perfusion of the heart beyond visual analysis of images, either in primary evaluation and comparison to normal values or in patients' follow-up and treatment monitoring. However, with implementation of quantitative parameters in clinical routine, standardization is of particular importance as different acquisition and evaluation strategies and algorithms may substantially influence results, though not always immediately apparent. · Clinical cardiac MRI provides numerous functional and morphological quantitative parameters.. · Quantitative cardiac MRI enables assessment of diffuse and global myocardial alterations.. · Standardized data acquisition/evaluation is the prerequisite for diagnostic use of quantitative cardiac MRI parameters.. · Reiter U, Reiter C, Kräuter C et al. Quantitative Clinical Cardiac Magnetic Resonance Imaging. Fortschr Röntgenstr 2020; 192: 246 - 256.

Evaluation of Modified Look-Locker Inversion Recovery and Arrhythmia-Insensitive Rapid Cardiac T1 Mapping Pulse Sequences in Cardiomyopathy Patients.

The aim of this study was to compare the performance of arrhythmia-insensitive rapid (AIR) and modified Look-Locker inversion recovery (MOLLI) T1 mapping in patients with cardiomyopathies. In 58 patients referred for clinical cardiac magnetic resonance imaging at 1.5 T, we compared MOLLI and AIR native and postcontrast T1 measurements. Two readers independently analyzed myocardial and blood T1 values. Agreement between techniques, interreader agreement per technique, and intrascan agreement per technique were evaluated. The MOLLI and AIR T1 values were strongly correlated (r = 0.98); however, statistically significantly different T1 values were derived (bias 80 milliseconds, pooled data, P < 0.01). Both techniques demonstrated high repeatability (MOLLI, r = 1.00 and coefficient of repeatability [CR] = 72 milliseconds; AIR, r = 0.99 and CR = 184.2 milliseconds) and produced high interreader agreement (MOLLI, r = 1.00 and CR = 51.7 milliseconds; AIR, r = 0.99 and CR = 183.5 milliseconds). Arrhythmia-insensitive rapid and MOLLI sequences produced significantly different T1 values in a diverse patient cohort.

Visualization and appearance of artifacts of leadless pacemaker systems in cardiac MRI : An experimental ex vivo study.

SummaryBackgroundLeadless pacemaker systems are an important upcoming device in clinical rhythmology. Currently two different products are available with the Micra system (Medtronic) being the most used in the clinical setting to date. The possibility to perform magnetic resonance imaging (MRI) is an important feature of modern pacemaker devices. Even though the Micra system is suitable for MRI, little is yet known about its impact on artifacts within the images.ObjectiveThe aim of our ex vivo study was to perform cardiac MRI to quantify the artifacts and to evaluate if artifacts limit or inhibit the assessment of the surrounding myocardium.MethodsAfter ex vivo implantation of the leadless pacemaker (LP) in a porcine model, hearts were filled with saline solution and fixed on wooden sticks on a plastic container. The model was examined at 1.5 T and at 3 T using conventional sequences and T2 mapping sequences. In addition, conventional X‑rays and computed tomography (CT) scans were performed.ResultsCorrect implantation of the LP could be performed in all hearts. In almost all MRI sequences the right ventricle and the septal region surrounding the (LP) were altered by an artifact and therefore would sustain limited assessment; however, the rest of the myocardium remained free of artifacts and evaluable for common radiologic diagnoses. A characteristic shamrock-shaped artifact was generated which appeared to be even more intense in magnitude and brightness when using 3 T compared to 1.5 T.ConclusionThe use of the Micra system in cardiac MRI appeared to be feasible. In our opinion, it will still be possible to make important clinical cardiac MRI diagnoses (the detection of major ischemic areas or inflammatory processes) in patients using the Micra system. We suggest the use of 1.5 T as the preferred method in clinical practice.

Synthetic late gadolinium enhancement cardiac magnetic resonance for diagnosing myocardial scar

Objectives. Late gadolinium enhancement (LGE) is the in vivo reference standard for assessing focal myocardial fibrosis. Post-contrast T1-mapping by Modified Look-Locker Inversion recovery (MOLLI) can be used to generate synthetic late gadolinium enhancement (SynLGE) images with an image contrast similar to conventional LGE images. We hypothesized that SynLGE has an accuracy that approaches conventional LGE for diagnosing focal myocardial fibrosis. Methods. Consecutive patients (n = 109, mean ± SD age 50 ± 16 years, 63% male) referred for clinical cardiac magnetic resonance imaging underwent LGE and post-contrast MOLLI starting 10–15 and 20–25 minutes post contrast, respectively. A cardiac short-axis stack and three long-axis views were acquired for SynLGE and LGE. SynLGE were generated from post-contrast T1-maps. Only LGE and SynLGE images were analyzed by two blinded observers for agreement regarding localization and origin of focal myocardial fibrosis on a per-patient basis. Results. Consensus identified focal fibrosis by LGE in 44/109 (40%) patients. Compared to LGE, SynLGE yielded a diagnostic sensitivity of 34/44 (77%), specificity of 64/65 (98%), positive predictive value of 34/35 (97%), negative predictive value of 64/74 (86%), and an overall accuracy of 98/109 (90%). In cases where SynLGE missed focal fibrosis (n = 10), these were either small non-ischemic focal fibrosis (n = 8) or infarction in a thin myocardial wall (n = 2). In one case, SynLGE identified midmural non-ischemic focal fibrosis not identified by LGE. Discussion. Overall, SynLGE showed good agreement with LGE. SynLGE derived from post-contrast T1-maps may provide the complementary ability to increase confidence in assessment of LGE images for focal myocardial fibrosis.

Non-invasive detection of adeno-associated viral gene transfer using a genetically encoded CEST-MRI reporter gene in the murine heart

Research into gene therapy for heart failure has gained renewed interest as a result of improved safety and availability of adeno-associated viral vectors (AAV). While magnetic resonance imaging (MRI) is standard for functional assessment of gene therapy outcomes, quantitation of gene transfer/expression relies upon tissue biopsy, fluorescence or nuclear imaging. Imaging of gene expression through the use of genetically encoded chemical exchange saturation transfer (CEST)-MRI reporter genes could be combined with clinical cardiac MRI methods to comprehensively probe therapeutic gene expression and subsequent outcomes. The CEST-MRI reporter gene Lysine Rich Protein (LRP) was cloned into an AAV9 vector and either administered systemically via tail vein injection or directly injected into the left ventricular free wall of mice. Longitudinal in vivo CEST-MRI performed at days 15 and 45 after direct injection or at 1, 60 and 90 days after systemic injection revealed robust CEST contrast in myocardium that was later confirmed to express LRP by immunostaining. Ventricular structure and function were not impacted by expression of LRP in either study arm. The ability to quantify and link therapeutic gene expression to functional outcomes can provide rich data for further development of gene therapy for heart failure.

Isotropic Reconstruction of MR Images Using 3D Patch-Based Self-Similarity Learning.

Isotropic three-dimensional (3D) acquisition is a challenging task in magnetic resonance imaging (MRI). Particularly in cardiac MRI, due to hardware and time limitations, current 3D acquisitions are limited by low-resolution, especially in the through-plane direction, leading to poor image quality in that dimension. To overcome this problem, super-resolution (SR) techniques have been proposed to reconstruct a single isotropic 3D volume from multiple anisotropic acquisitions. Previously, local regularization techniques such as total variation have been applied to limit noise amplification while preserving sharp edges and small features in the images. In this paper, inspired by the recent progress in patch-based reconstruction, we propose a novel isotropic 3D reconstruction scheme that integrates non-local and self-similarity information from 3D patch neighborhoods. By grouping 3D patches with similar structures, we enforce the natural sparsity of MR images, which can be expressed by a low-rank structure, leading to robust image reconstruction with high signal-to-noise ratio efficiency. An Augmented Lagrangian formulation of the problem is proposed to efficiently decompose the optimization into a low-rank volume denoising and a SR reconstruction. Experimental results in simulations, brain imaging and clinical cardiac MRI, demonstrate that the proposed joint SR and self-similarity learning framework outperforms current state-of-the-art methods. The proposed reconstruction of isotropic 3D volumes may be particularly useful for cardiac applications, such as myocardial infarction scar assessment by late gadolinium enhancement MRI.

The Role of Clinical Cardiac Magnetic Resonance Imaging in China: Current Status and the Future

Cardiac magnetic resonance (CMR) imaging plays an important role in the diagnosis and management of cardiovascular diseases. The state-of-the-art CMR imaging has many advantages in cardiac imaging, including excellent spatial and temporal resolution, unrestricted imaging field, no exposure to ionizing radiation, excellent tissue contrast, and unique myocardial tissue characterization. Clinical CMR imaging is used during the cardiovascular diagnostic workup in the United States and some European countries. Use of CMR imaging is emerging in hospitals in China and has a promising future. This review briefly describes the real-world clinical application of CMR imaging in China and discuss obstacles for its future development.

Analysis of an automated background correction method for cardiovascular MR phase contrast imaging in children and young adults

Phase contrast magnetic resonance imaging (MRI) is a powerful tool for evaluating vessel blood flow. Inherent errors in acquisition, such as phase offset, eddy currents and gradient field effects, can cause significant inaccuracies in flow parameters. These errors can be rectified with the use of background correction software. To evaluate the performance of an automated phase contrast MRI background phase correction method in children and young adults undergoing cardiac MR imaging. We conducted a retrospective review of patients undergoing routine clinical cardiac MRI including phase contrast MRI for flow quantification in the aorta (Ao) and main pulmonary artery (MPA). When phase contrast MRI of the right and left pulmonary arteries was also performed, these data were included. We excluded patients with known shunts and metallic implants causing visible MRI artifact and those with more than mild to moderate aortic or pulmonary stenosis. Phase contrast MRI of the Ao, mid MPA, proximal right pulmonary artery (RPA) and left pulmonary artery (LPA) using 2-D gradient echo Fast Low Angle SHot (FLASH) imaging was acquired during normal respiration with retrospective cardiac gating. Standard phase image reconstruction and the automatic spatially dependent background-phase-corrected reconstruction were performed on each phase contrast MRI dataset. Non-background-corrected and background-phase-corrected net flow, forward flow, regurgitant volume, regurgitant fraction, and vessel cardiac output were recorded for each vessel. We compared standard non-background-corrected and background-phase-corrected mean flow values for the Ao and MPA. The ratio of pulmonary to systemic blood flow (Qp:Qs) was calculated for the standard non-background and background-phase-corrected data and these values were compared to each other and for proximity to 1. In a subset of patients who also underwent phase contrast MRI of the MPA, RPA, and LPA a comparison was made between standard non-background-corrected and background-phase-corrected mean combined flow in the branch pulmonary arteries and MPA flow. All comparisons were performed using the Wilcoxon sign rank test (α = 0.05). Eighty-five children and young adults (mean age 14 years; range 10 days to 32 years) met the criteria for inclusion. Background-phase-corrected mean flow values for the Ao and MPA were significantly lower than those for non-background-corrected standard Ao (P = 0.0004) and MPA flow values (P < 0.0001), respectively. However, no significant difference was seen between the standard non-background (P = 0.295) or background-phase-corrected (P = 0.0653) mean Ao and MPA flow values. Neither the mean standard non-background-corrected (P = 0.408) nor the background-phase-corrected (P = 0.0684) Qp:Qs was significantly different from 1. However in the 27 patients with standard non-background-corrected data, the difference between the Ao and MPA flow values was greater than 10%. There were 19 patients with background-phase-corrected data in which the difference between the Ao and MPA flow values was greater than 10%. In the subset of 43 patients who underwent MPA and branch pulmonary artery phase contrast MRI, the sum of the standard non-background-corrected mean RPA and LPA flow values was significantly different from the standard non-background-corrected mean MPA flow (P = 0.0337). The sum of the background-phase-corrected mean RPA and LPA flow values was not significantly different from the background-phase-corrected mean MPA flow value (P = 0.1328), suggesting improvement in pulmonary artery flow calculations using background-phase-correction. Our data suggest that background phase correction of phase contrast MRI data does not significantly change Qp:Qs quantification, and there are residual errors in expected Qp:Qs quantification despite background phase correction. However the use of background phase correction does improve quantification of MPA flow relative to combined RPA and LPA flow. Further work is needed to validate these findings in other patient populations, using other MRI units, and across vendors.