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.

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.

Assessment of acute myocarditis by cardiac magnetic resonance imaging: Comparison of qualitative and quantitative analysis methods.

BACKGROUND: To compare cardiac magnetic resonance (CMR) qualitative and quantitative analysis methods for the noninvasive assessment of myocardial inflammation in patients with suspected acute myocarditis (AM). METHODS: A total of 61 patients with suspected AM underwent coronary angiography and CMR. Qualitative analysis was performed applying Lake-Louise Criteria (LLC), followed by quantitative analysis based on the evaluation of edema ratio (ER) and global relative enhancement (RE). Diagnostic performance was assessed for each method by measuring the area under the curves (AUC) of the receiver operating characteristic analyses. The final diagnosis of AM was based on symptoms and signs suggestive of cardiac disease, evidence of myocardial injury as defined by electrocardiogram changes, elevated troponin I, exclusion of coronary artery disease by coronary angiography, and clinical and echocardiographic follow-up at 3 months after admission to the chest pain unit. RESULTS: In all patients, coronary angiography did not show significant coronary artery stenosis. Troponin I levels and creatine kinase were higher in patients with AM compared to those without (both P < .001). There were no significant differences among LLC, T2-weighted short inversion time inversion recovery (STIR) sequences, early (EGE), and late (LGE) gadolinium-enhancement sequences for diagnosis of AM. The AUC for qualitative (T2-weighted STIR 0.92, EGE 0.87 and LGE 0.88) and quantitative (ER 0.89 and global RE 0.80) analyses were also similar. CONCLUSIONS: Qualitative and quantitative CMR analysis methods show similar diagnostic accuracy for the diagnosis of AM. These findings suggest that a simplified approach using a shortened CMR protocol including only T2-weighted STIR sequences might be useful to rule out AM in patients with acute coronary syndrome and normal coronary angiography.

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

BACKGROUND: Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. PURPOSE/HYPOTHESIS: To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. STUDY TYPE: Retrospective, observational study. POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL: Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. FIELD STRENGTH/SEQUENCE: Unenhanced T1 -weighted in-phase (IP) and out-of-phase (OP) as well as T2 -weighted (T2 -w) MR images acquired at 3T. ASSESSMENT: Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. STATISTICAL TESTS: The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. RESULTS: A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. DATA CONCLUSION: Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Cardiac sympathetic neuronal damage precedes myocardial fibrosis in patients with Anderson-Fabry disease.

PURPOSE: Cardiac sympathetic denervation may be detectable in patients with Anderson-Fabry disease (AFD), suggesting its usefulness for early detection of the disease. However, the relationship between sympathetic neuronal damage measured by 123I-metaiodobenzylguanidine (MIBG) imaging with myocardial fibrosis on cardiac magnetic resonance (CMR) is still unclear. METHODS: Cardiac sympathetic innervation was assessed by 123I-MIBG single-photon emission computed tomography (SPECT) in 25 patients with genetically proved AFD. Within one month from MIBG imaging, all patients underwent contrast-enhanced CMR. MIBG defect size and fibrosis size on CMR were measured for the left ventricle (LV) and expressed as %LV. RESULTS: Patients were divided into three groups according to MIBG and CMR findings: (1) matched normal, without MIBG defects and without fibrosis on CMR (n = 10); (2) unmatched, with MIBG defect but without fibrosis (n = 5); and (3) matched abnormal, with MIBG defect and fibrosis (n = 10). The three groups did not differ with respect to age, gender, α-galactosidase, proteinuria, glomerular filtration rate, and troponin I, while New York Heart Association class (p = 0.008), LV hypertrophy (p = 0.05), and enzyme replacement therapy (p = 0.02) were different among groups. Although in patients with matched abnormal findings, there was a significant correlation between MIBG defect size and area of fibrosis at CMR (r2 = 0.98, p < 0.001), MIBG defect size was larger than fibrosis size (26 ± 23 vs. 18 ± 13%LV, p = 0.02). CONCLUSION: Sympathetic neuronal damage is frequent in AFD patients, and it may precede myocardial damage, such as fibrosis. Thus, 123I-MIBG imaging can be considered a challenging technique for early detection of cardiac involvement in AFD.

Integrated Imaging Characterization of Adrenal Adenoma: False-Positive Metaiodobenzylguanidine (MIBG) Findings of Adrenal Scintigraphy.

BACKGROUND: Evaluation of a patient with melanoma in whom an adrenal mass was detected on CT and MR during follow-up and further characterized with PET-CT and MIBG scintigraphy. CASE REPORT: In this case report, we describe a patient with melanoma in whom an adrenal mass was detected on CT and MRI during post-surgical follow-up and was further characterized with radionuclide studies consisting of PET-CT and MIBG scintigraphy. Although the results of imaging studies suggested that the mass was a pheochromocytoma, a cortical adrenal adenoma was histologically proven. CONCLUSIONS: Integrated structural and functional imaging is recommended to characterize adrenal tumors; however, mistakes may occur and therefore careful imaging evaluation is required.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.