Cardiovascular magnetic resonance parametric techniques to characterize myocardial effects of anthracycline therapy in adults with normal left ventricular ejection fraction: a systematic review and meta-analysis.

BACKGROUND: The cardiotoxic effects of anthracyclines therapy are well recognized, both in the short and long term. Echocardiography allows monitoring of cancer patients treated with this class of drugs by serial assessment of left ventricle ejection fraction (LVEF) as a surrogate of systolic function. However, changes in myocardial function may occur late in the process when cardiac damage is already established. Novel cardiac magnetic resonance (CMR) parametric techniques, like native T1 mapping and extra-cellular volume (ECV), may detect subclinical myocardial damage in these patients, recognizing early signs of cardiotoxicity before development of overt cancer therapy-related cardiac dysfunction (CTRCD) and prompting tailored therapeutic and follow-up strategies to improve outcome. METHODS AND RESULTS: We conducted a systematic review and a meta-analysis to investigate the difference in CMR derived native T1 relaxation time and ECV values, respectively, in anthracyclines-treated cancer patients with preserved EF versus healthy controls. PubMed, Embase, Web of Science and Cochrane Central were searched for relevant studies. A total of 6 studies were retrieved from 1057 publications, of which, four studies with 547 patients were included in the systematic review on T1 mapping and five studies with 481 patients were included in the meta-analysis on ECV. Three out of the four included studies in the systematic review showed higher T1 mapping values in anthracyclines treated patients compared to healthy controls. The meta-analysis demonstrated no statistically significant difference in ECV values between the two groups in the main analysis (Hedges´s g =3.20, 95% CI -0.72-7.12, p =0.11, I2 =99%), while ECV was significantly higher in the anthracyclines-treated group when sensitivity analysis was performed. CONCLUSIONS: Higher T1 mapping and ECV values in patients exposed to anthracyclines could represent early biomarkers of CTRCD, able to detect subclinical myocardial changes present before the development of overt myocardial dysfunction. Our results highlight the need for further studies to investigate the correlation between anthracyclines-based chemotherapy and changes in CMR mapping parameters that may guide future tailored follow-up strategies in this group of patients.

CT Coronary Angiography: Technical Approach and Atherosclerotic Plaque Characterization.

Coronary computed tomography angiography (CCTA) currently represents a robust imaging technique for the detection, quantification and characterization of coronary atherosclerosis. However, CCTA remains a challenging task requiring both high spatial and temporal resolution to provide motion-free images of the coronary arteries. Several CCTA features, such as low attenuation, positive remodeling, spotty calcification, napkin-ring and high pericoronary fat attenuation index have been proved as associated to high-risk plaques. This review aims to explore the role of CCTA in the characterization of high-risk atherosclerotic plaque and the recent advancements in CCTA technologies with a focus on radiomics plaque analysis.

Advanced CMR Techniques in Anderson-Fabry Disease: State of the Art.

Anderson-Fabry disease (AFD) is a rare multisystem X-linked lysosomal storage disorder caused by α-galactosidase A enzyme deficiency. Long-term cardiac involvement in AFD results in left ventricular hypertrophy and myocardial fibrosis, inducing several complications, mainly arrhythmias, valvular dysfunction, and coronary artery disease. Cardiac magnetic resonance (CMR) represents the predominant noninvasive imaging modality for the assessment of cardiac involvement in the AFD, being able to comprehensively assess cardiac regional anatomy, ventricular function as well as to provide tissue characterization. This review aims to explore the role of the most advanced CMR techniques, such as myocardial strain, T1 and T2 mapping, perfusion and hybrid imaging, as diagnostic and prognostic biomarkers.

Artificial intelligence and radiomics in magnetic resonance imaging of rectal cancer: a review.

Rectal cancer (RC) is one of the most common tumours worldwide in both males and females, with significant morbidity and mortality rates, and it accounts for approximately one-third of colorectal cancers (CRCs). Magnetic resonance imaging (MRI) has been demonstrated to be accurate in evaluating the tumour location and stage, mucin content, invasion depth, lymph node (LN) metastasis, extramural vascular invasion (EMVI), and involvement of the mesorectal fascia (MRF). However, these features alone remain insufficient to precisely guide treatment decisions. Therefore, new imaging biomarkers are necessary to define tumour characteristics for staging and restaging patients with RC. During the last decades, RC evaluation via MRI-based radiomics and artificial intelligence (AI) tools has been a research hotspot. The aim of this review was to summarise the achievement of MRI-based radiomics and AI for the evaluation of staging, response to therapy, genotyping, prediction of high-risk factors, and prognosis in the field of RC. Moreover, future challenges and limitations of these tools that need to be solved to favour the transition from academic research to the clinical setting will be discussed.

Application of AI in cardiovascular multimodality imaging.

Technical advances in artificial intelligence (AI) in cardiac imaging are rapidly improving the reproducibility of this approach and the possibility to reduce time necessary to generate a report. In cardiac computed tomography angiography (CCTA) the main application of AI in clinical practice is focused on detection of stenosis, characterization of coronary plaques, and detection of myocardial ischemia. In cardiac magnetic resonance (CMR) the application of AI is focused on post-processing and particularly on the segmentation of cardiac chambers during late gadolinium enhancement. In echocardiography, the application of AI is focused on segmentation of cardiac chambers and is helpful for valvular function and wall motion abnormalities. The common thread represented by all of these techniques aims to shorten the time of interpretation without loss of information compared to the standard approach. In this review we provide an overview of AI applications in multimodality cardiac imaging.

Dual-Energy CT of the Heart: A Review.

Dual-energy computed tomography (DECT) represents an emerging imaging technique which consists of the acquisition of two separate datasets utilizing two different X-ray spectra energies. Several cardiac DECT applications have been assessed, such as virtual monoenergetic images, virtual non-contrast reconstructions, and iodine myocardial perfusion maps, which are demonstrated to improve diagnostic accuracy and image quality while reducing both radiation and contrast media administration. This review will summarize the technical basis of DECT and review the principal cardiac applications currently adopted in clinical practice, exploring possible future applications.

Multimodality Imaging in Ischemic Chronic Cardiomyopathy.

Ischemic chronic cardiomyopathy (ICC) is still one of the most common cardiac diseases leading to the development of myocardial ischemia, infarction, or heart failure. The application of several imaging modalities can provide information regarding coronary anatomy, coronary artery disease, myocardial ischemia and tissue characterization. In particular, coronary computed tomography angiography (CCTA) can provide information regarding coronary plaque stenosis, its composition, and the possible evaluation of myocardial ischemia using fractional flow reserve CT or CT perfusion. Cardiac magnetic resonance (CMR) can be used to evaluate cardiac function as well as the presence of ischemia. In addition, CMR can be used to characterize the myocardial tissue of hibernated or infarcted myocardium. Echocardiography is the most widely used technique to achieve information regarding function and myocardial wall motion abnormalities during myocardial ischemia. Nuclear medicine can be used to evaluate perfusion in both qualitative and quantitative assessment. In this review we aim to provide an overview regarding the different noninvasive imaging techniques for the evaluation of ICC, providing information ranging from the anatomical assessment of coronary artery arteries to the assessment of ischemic myocardium and myocardial infarction. In particular this review is going to show the different noninvasive approaches based on the specific clinical history of patients with ICC.

Cardiovascular magnetic resonance of cardiac tumors and masses.

Cardiac masses diagnosis and treatment are a true challenge, although they are infrequently encountered in clinical practice. They encompass a broad set of lesions that include neoplastic (primary and secondary), non-neoplastic masses and pseudomasses. The clinical presentation of cardiac tumors is highly variable and depends on several factors such as size, location, relation with other structures and mobility. The presumptive diagnosis is made based on a preliminary non-invasive diagnostic work-up due to technical difficulties and risks associated with biopsy, which is still the diagnostic gold standard. The findings should always be interpreted in the clinical context to avoid misdiagnosis, particularly in specific conditions (e.g., infective endocarditis or thrombi). The modern multi-modality imaging techniques has a key role not only for the initial assessment and differential diagnosis but also for management and surveillance of the cardiac masses. Cardiovascular magnetic resonance (CMR) allows an optimal non-invasive localization of the lesion, providing multiplanar information on its relation to surrounding structures. Moreover, with the additional feature of tissue characterization, CMR can be highly effective to distinguish pseudomasses from masses, as well as benign from malignant lesions, with further differential diagnosis of the latter. Although histopathological assessment is important to make a definitive diagnosis, CMR plays a key role in the diagnosis of suspected cardiac masses with a great impact on patient management. This literature review aims to provide a comprehensive overview of cardiac masses, from clinical and imaging protocol to pathological findings.

Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.

BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium enhancement sequences (2D-SSLGE). The aim of the study is to assess the feasibility and comparison of 2D-MSLGE reconstructed with artificial intelligence reconstruction deep learning noise reduction (NR) algorithm compared to standard 2D-SSLGE in consecutive patients with ischemic cardiomyopathy (ICM). METHODS: Fifty-seven patients with known ICM referred for a clinically indicated CMR were enrolled in this study. 2D-MSLGE were reconstructed using a growing level of NR (0%,25%,50%,75%and 100%). Subjective image quality, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were evaluated in each dataset and compared to standard 2D-SSLGE. Moreover, diagnostic accuracy, LGE mass and scan time were compared between 2D-MSLGE with NR and 2D-SSLGE. RESULTS: The application of NR reconstruction ≥50% to 2D-MSLGE provided better subjective image quality, CNR and SNR compared to 2D-SSLGE (p < 0.01). The best compromise in terms of subjective and objective image quality was observed for values of 2D-MSLGE 75%, while no differences were found in terms of LGE quantification between 2D-MSLGE versus 2D-SSLGE, regardless the NR applied. The sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 2D-MSLGE NR 75% were 87.77%,96.27%,96.13%,88.16% and 94.22%, respectively. Time of acquisition of 2D-MSLGE was significantly shorter compared to 2D-SSLGE (p < 0.01). CONCLUSION: When compared to standard 2D-SSLGE, the application of NR reconstruction to 2D-MSLGE provides superior image quality with similar diagnostic accuracy.

Challenges and opportunities to delivering cardiac imaging training: a national survey by the Italian college of cardiac radiology.

BACKGROUND: Delivering consistent levels of training in cardiac imaging to radiologist is of pivotal importance because of the increasing clinical indications to coronary computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR). Our study sought to capture the heterogeneity of cardiac imaging training programs and to explore residents' vision on cardiac imaging both in the present and in the future. METHODS: Two web-based surveys were created. The first was administered to all chief residents from the 42 University Hospitals within Italy, aiming to explore the local educational offer in cardiac imaging. The second was administered via social media to all Italian residents, including questions about their overall vision regarding cardiac imaging. RESULTS: 42/42 University Hospitals responded to the first survey and 235 residents to the second. There was at least a 64-slice CT scanner and a 1.5 T MR scanner per center. In the majority of sites, the weekly routine consisted of more than 10 CCTA and more than 5 CMR. Approximately, half of the centers used advanced CCTA and CMR techniques. The majority of the interviewed resident (94%) perceived cardiac imaging training to be moderately to very important, while requirement for external educational resources was advocated in 25% of the cases. CONCLUSION: Our survey highlighted a significant awareness of radiology residents regarding the importance of cardiac imaging in their training curriculum. All centers met the technical requirements for cardiac imaging, limiting its use to basic applications in around half of cases. Implementation of an educational network might be the key for supporting the growth of this subspecialty field.

MRI index lesion radiomics and machine learning for detection of extraprostatic extension of disease: a multicenter study.

OBJECTIVES: To build a machine learning (ML) model to detect extraprostatic extension (EPE) of prostate cancer (PCa), based on radiomics features extracted from prostate MRI index lesions. METHODS: Consecutive MRI exams of patients undergoing radical prostatectomy for PCa were retrospectively collected from three institutions. Axial T2-weighted and apparent diffusion coefficient map images were annotated to obtain index lesion volumes of interest for radiomics feature extraction. Data from one institution was used for training, feature selection (using reproducibility, variance and pairwise correlation analyses, and a correlation-based subset evaluator), and tuning of a support vector machine (SVM) algorithm, with stratified 10-fold cross-validation. The model was tested on the two remaining institutions' data and compared with a baseline reference and expert radiologist assessment of EPE. RESULTS: In total, 193 patients were included. From an initial dataset of 2436 features, 2287 were excluded due to either poor stability, low variance, or high collinearity. Among the remaining, 14 features were used to train the ML model, which reached an overall accuracy of 83% in the training set. In the two external test sets, the SVM achieved an accuracy of 79% and 74% respectively, not statistically different from that of the radiologist (81-83%, p = 0.39-1) and outperforming the baseline reference (p = 0.001-0.02). CONCLUSIONS: A ML model solely based on radiomics features demonstrated high accuracy for EPE detection and good generalizability in a multicenter setting. Paired to qualitative EPE assessment, this approach could aid radiologists in this challenging task. KEY POINTS: • Predicting the presence of EPE in prostate cancer patients is a challenging task for radiologists. • A support vector machine algorithm achieved high diagnostic accuracy for EPE detection, with good generalizability when tested on multiple external datasets. • The performance of the algorithm was not significantly different from that of an experienced radiologist.

Cardiovascular magnetic resonance in myocardial infarction with non-obstructive coronary arteries patients: A review.

The diagnosis of myocardial infarction with non-obstructive coronary arteries (MINOCA) necessitates documentation of an acute myocardial infarction (AMI), non-obstructive coronary arteries, using invasive coronary angiography or coronary computed tomography angiography and no clinically overt cause for AMI. Historically patients with MINOCA represent a clinical dilemma with subsequent uncertain clinical management. Differential diagnosis is crucial to choose the best therapeutic option for ischemic and non-ischemic MINOCA patients. Cardiovascular magnetic resonance (CMR) is able to analyze cardiac structure and function simultaneously and provides tissue characterization. Moreover, CMR could identify the cause of MINOCA in nearly two-third of patients providing valuable information for clinical decision making. Finally, it allows stratification of patients with worse outcomes which resulted in therapeutic changes in almost half of the patients. In this review we discuss the features of CMR in MINOCA; from exam protocols to imaging findings.

Image Quality and Reliability of a Novel Dark-Blood Late Gadolinium Enhancement Sequence in Ischemic Cardiomyopathy.

PURPOSE: The aim of this study was to assess the reliability of a 2D dark-blood phase-sensitive late gadolinium enhancement sequence (2D-DBPSLGE) compared with 2D phase-sensitive inversion recovery late gadolinium enhancement sequence (2D-BBPSLGE) in patients with ischemic cardiomyopathy (ICM). MATERIALS AND METHODS: A total of 73 patients with a clinical history of ICM were prospectively enrolled. The following endpoints were evaluated: (a) comparison of image quality between 2D-BBPSLGE and 2D-DBPSLGE for differentiation between blood pool-late gadolinium enhancement (LGE), remote myocardium-LGE, and blood pool-remote myocardium; (b) diagnostic accuracy of 2D-DBPSLGE compared with gold standard 2D-BBPSLGE for the evaluation of infarcted segments; (c) diagnostic accuracy of 2D-DBPSLGE for the evaluation of microvascular obstruction (MVO); (d) comparison of transmurality index between 2D-BBPSLGE and 2D-DBPSLGE; (e) comparison of papillary muscle hyperenhancement between 2D-BBPSLGE and 2D-DBPSLGE; inter-reader agreement for depiction of hyperenhanced segments in both LGE sequences. Data were analyzed using paired t test, Wilcoxon test, and McNemar test, and η coefficient and intercorrelation coefficient (ICC). RESULTS: Image quality was superior for 2D-DBPSLGE for differentiation of blood pool-LGE (P<0.001). 2D-DBPSLGE, compared with 2D-BBPSLGE, showed a sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of 96.93%, 99.89%, 99.71%, 98.78, and 99.04%, respectively. Concerning MVO detection, 2D-DBPSLGE showed a sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of 66.67%, 100.00%, 100.00%, 80.95%, and 86.21%, respectively. 2D-DBPSLGE underestimated the transmurality (P=0.007) and identified papillary muscle hyperenhancement (P<0.001). Both LGE sequences showed comparable interobserver agreement for the evaluation of infarcted areas (2D-BBPSLGE: ICC 0.99;2D-DBPSLGE: ICC 0.99). CONCLUSIONS: Compared with 2D-BBPSLGE, 2D-DBPSLGE sequences provide better differentiation between LGE and blood-pool, while underestimating LGE trasmurality and the presence of MVO.

The cardiac conundrum: a systematic review and bibliometric analysis of authorship in cardiac magnetic resonance imaging studies.

PURPOSE: We aimed to assess the role of radiologists, cardiologists, and other medical and non-medical figures in cardiac magnetic resonance imaging (MRI) research in the last 34 years, focusing on first and last authorship, number of published studies, and journal impact factors (IF). METHODS: Articles in the field of cardiac MRI were considered in this systematic review and retrospective bibliometric analysis. For included studies, the first and last authors were categorized as cardiologists, radiologists/nuclear medicine physicians, medical doctors (MD) with specialties in both cardiology and radiology/nuclear medicine, and other MD and non-MD. Differences in the number of papers published overall and by year and institution location for the first and last author category were assessed. Mean IF differences between author categories were also investigated. RESULTS: A total of 2053 articles were included in the final analysis. For the first authors (n = 2011), 52% were cardiologists, 22% radiologists/nuclear medicine physicians, 16% other MD, 10% other non-MD, and 1% both cardiologists and radiologists/nuclear medicine physicians. Similarly, the last authors (n = 2029) resulted 54% cardiologists, 22% radiologists/nuclear medicine physicians, 15% other MD, 8% other non-MD, and 2% both cardiologists and radiologists/nuclear medicine physicians. No significant differences due to institution location in the first and last authorship proportions were found. Average journal IF was significantly higher for cardiologist first and last authors when compared to that of radiologists/nuclear medicine physicians (both p < 0.0001). CONCLUSION: Over 50% of studies in the field of cardiac MRI published in the last 34 years are conducted by cardiologists.

Reliability of single breath hold three-dimensional cine kat-ARC for the assessment of biventricular dimensions and function.

PURPOSE: To assess the accuracy and reproducibility of 3D-cine k-adaptative-t-autocalibrating reconstruction for cartesian sampling (3D cine kat-ARC) for quantification of biventricular volumes, ejection fraction and LV mass in clinical practice. METHOD: 74 patients underwent cardiac magnetic resonance for clinical indications. In the whole population 3D cine kat-ARC and 2D cine bSSFP images were acquired on short axis view. Subsequently, the population was divided in three subgroups (dilated, hypetrophic, other phenotypes). Two experienced observers performed analysis of volumes, biventricular function and left ventricular mass in the overall population and subgroups using an off-line workstation. Statistical analysis was performed using Student's t-test, linear regression and Bland-Altman plot, correlation coefficient η2 and the intraclass correlation coefficient (ICC). A cut-off value of p < 0.05 was considered statistically significant. RESULTS: Biventricular volumes, function and left ventricular mass evaluated with 3D cine kat-ARC sequences did not show any significant difference compared to 2D bSSFP sequences in the overall population (p > 0.05). Bland-Altman analysis showed limited bias and narrow limits of the agreement for all measurements in overall population. Subgroup analysis showed a statistically significant difference (p = 0.04) for left ventricular ejection fraction (LVEF) in patients with a dilated phenotype; showing a minimum overestimation tendency for 3D cine kat ARC (2D cine bSSFP LVEF = 46.44 ± 15.83% vs 3D cine kat-ARC LVEF = 48.36 ± 16.50 %). CONCLUSIONS: 3D cine kat-ARC 3D sequences allow an accurate evaluation of biventricular volumes and function in a single breath hold.

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA.

BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary computed tomography angiography (CCTA) in the correct Coronary Artery Disease Reporting and Data System (CAD-RADS) category. METHODS: Two hundred eighty eight patients who underwent clinically indicated CCTA were included in this single-center retrospective study. The CCTAs were stratified by CAD-RADS scores by expert readers and considered as reference standard. A deep CNN was designed and tested on the CCTA dataset and compared to on-site reading. The deep CNN analyzed the diagnostic accuracy of the following three Models based on CAD-RADS classification: Model A (CAD-RADS 0 vs CAD-RADS 1-2 vs CAD-RADS 3,4,5), Model 1 (CAD-RADS 0 vs CAD-RADS>0), Model 2 (CAD-RADS 0-2 vs CAD-RADS 3-5). Time of analysis for both physicians and CNN were recorded. RESULTS: Model A showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 47%, 74%, 77%, 46% and 60%, respectively. Model 1 showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 66%, 91%, 92%, 63%, 86%, respectively. Conversely, Model 2 demonstrated the following sensitivity, specificity, negative predictive value, positive predictive value and accuracy: 82%, 58%, 74%, 69%, 71%, respectively. Time of analysis was significantly lower using CNN as compared to on-site reading (530.5 ± 179.1 vs 104.3 ± 1.4 sec, p=0.01) CONCLUSIONS: Deep CNN yielded accurate automated classification of patients with CAD-RADS.

Aberrant right coronary artery in a grown up congenital cardiac patient, successfully treated 46 years earlier with a double Starr-Edwards silastic ball valve replacement: a case report.

BACKGROUND: The Starr-Edwards ball valve prosthesis was successfully introduced in 1961-62 and largely used for aortic and mitral valve replacement. Even if Starr-Edwards valves have been widely replaced in clinical practice by other mechanical valves, they define a standard concerning long-term durability. CASE PRESENTATION: We describe the case of a 55-year-old man referred to our Department to perform a cardiac computed tomography (CCT), to better evaluate a severe dilation of ascending aorta discovered at echocardiography. The patient had been surgically treated 46 years earlier to correct a supra-cristal type ventricular septal defect. Both mitral and aortic valves were replaced, respectively due to bacterial mitral endocarditis and a fibrous sub-valvular aortic stenosis. In addition, the right coronary artery (RCA) was found to arise from the left coronary sinus. CONCLUSION: We report the longest lasting durability (46 years) of aortic and mitral Starr-Edwards valves successfully implanted in a patient simultaneously carrying a malignant anomalous origin of RCA.

Left Ventricular Mass in Hypertrophic Cardiomyopathy Assessed by 2D-Echocardiography: Validation with Magnetic Resonance Imaging.

We aim to validate echocardiographic left ventricular (LV) mass (echoLVM) in sixty-one patients with hypertrophic cardiomyopathy (HCM), using cardiac magnetic resonance measures (cmrLVM) as gold standard. cmrLVM was calculated using LV short-axis images, from base to apex, whereas echoLVM by LV epicardial minus LV endocardial volumes in 4 and 2 chamber views, using Simpson disk summation; trabeculae and papillary muscle were excluded in both cmrLVM and echoLVM. cmrLVM and echoLVM were not different by paired t test (145 ± 66 vs 147 ± 61; p = 0.240), and their correlation was good (r = 0.977; p < 0.0001). Intraclass correlation demonstrated reliability of echoLVM with cmrLVM (ρ = 0.987; Cls = 0.978-0.992; p < 0.0001). LV end-diastolic volume was higher by CMR than that by echo (137 ± 33 vs 85 ± 28 mL, p < 0.0001), resulting in a lower mass/volume ratio (1.1 ± 0.4 vs 1.8 ± 0.8, p < 0.0001). EchoLVM may be determined in patients with HCM. However, mass/volume ratio is higher by echocardiography than that by CMR.

Diagnostic Accuracy of Single-shot 2-Dimensional Multisegment Late Gadolinium Enhancement in Ischemic and Nonischemic Cardiomyopathy.

PURPOSE: The aim of this study was to assess the reliability of single-shot 2-dimensional multislice late gadolinium enhancement (2D-MSLGE) compared with gold standard single-slice 2D inversion recovery segmented gradient echo (2D-SSLGE). MATERIALS AND METHODS: Sixty-seven patients prospectively underwent clinically indicated cardiac magnetic resonance (CMR) imaging and were enrolled. The image quality was assessed using a 4-point scale. Segments positive for LGE were classified as ischemic or nonischemic for 2D-MSLGE and 2D-SSLGE. Interobserver and intraobserver variability was assessed for both sequences by 2 readers. The endpoints were as follows: (a) detection of myocardial segments involved by LGE and (b) classification of LGE as ischemic and nonischemic pattern. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy value were calculated for the 2 endpoints. RESULTS: 2D-MSLGE and 2D-SSLGE were successfully performed in all patients with comparable image quality (1.56±0.59 vs. 1.54±0.58, P=0.84). For the overall population, 2D-MSLGE correctly identified 1093 of 1139 myocardial segments positive for LGE (96%; 95% confidence interval [CI]: 95%-97%), as compared with 2D-SSLGE. Similarly, 2D-MSLGE correctly identified 1128 of 1139 (99%; 95% CI: 98%-99%) and 1108 of 1139 (97%; 95% CI: 96%-98%) of nonischemic and ischemic LGE patterns.Interobserver and intraobserver variability for quantification of LGE using 2D-MSLGE was 0.98 and 0.99, respectively. The acquisition time was shorter for 2D-MSLGE as compared with 2D-SSLGE (2.0±0.5 vs. 6.0±2.0 min, P: 0.01). CONCLUSIONS: As compared with 2D-SSLGE, 2D-MSLGE is a reliable tool in both ischemic and nonischemic cardiac disease; it is associated with shorter scan times without the need for prolonged breath holding and may be beneficial for those with dysrhythmia.