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Positron emission tomography (PET) and magnetic resonance imaging (MRI) have both been used for decades in cardiovascular imaging. Since 2010, hybrid PET/MRI using sequential and integrated scanner platforms has been available, with hybrid cardiac PET/MR imaging protocols increasingly incorporated into clinical workflows. Given the range of complementary information provided by each method, the use of hybrid PET/MRI may be justified and beneficial in particular clinical settings for the evaluation of different disease entities. In the present joint position statement, we critically review the role and value of integrated PET/MRI in cardiovascular imaging, provide a technical overview of cardiac PET/MRI and practical advice related to the cardiac PET/MRI workflow, identify cardiovascular applications that can potentially benefit from hybrid PET/MRI, and describe the needs for future development and research. In order to encourage its wide dissemination, this article is freely accessible on the European Radiology and European Journal of Hybrid Imaging web sites.Key Points• Studies and case-reports indicate that PET/MRI is a feasible and robust technology.• Promising fields of application include a variety of cardiac conditions.• Larger studies are required to demonstrate its incremental and cost-effective value.• The translation of novel radiopharmaceuticals and MR-sequences will provide exciting new opportunities.

Cardiac cine magnetic resonance imaging (MRI) is a widely used technique for the noninvasive assessment of cardiac functions. Deep neural networks have achieved considerable progress in overcoming various challenges in cine MRI analysis. However, deep learning models cannot be used for classification because limited cine MRI data are available. To overcome this problem, features from cine image settings are derived by handcrafting and addition of other clinical features to the classical machine learning approach for ensuring the model fits the MRI device settings and image parameters required in the analysis. In this study, a novel method was proposed for classifying heart disease (cardiomyopathy patient groups) using only segmented output maps. In the encoder–decoder network, the fully convolutional EfficientNetB5-UNet was modified to perform the semantic segmentation of the MRI image slice. A two-dimensional thickness algorithm was used to combine the segmentation outputs for the 2D representation of images of the end-diastole (ED) and end-systole (ES) cardiac volumes. The thickness images were subsequently used for classification by using a few-shot model with an adaptive subspace classifier. Model performance was verified by applying the model to the 2017 MICCAI Medical Image Computing and Computer-Assisted Intervention dataset. High segmentation performance was achieved as follows: the average Dice coefficients of segmentation were 96.24% (ED) and 89.92% (ES) for the left ventricle (LV); the values for the right ventricle (RV) were 92.90% (ED) and 86.92% (ES). The values for myocardium were 88.90% (ED) and 90.48% (ES). An accuracy score of 92% was achieved in the classification of various cardiomyopathy groups without clinical features. A novel rapid analysis approach was proposed for heart disease diagnosis, especially for cardiomyopathy conditions using cine MRI based on segmented output maps.

Postmortem imaging is increasingly used in forensic practice in cases of natural deaths related to cardiovascular diseases, which represent the most common causes of death in developed countries. While radiological examination is generally considered to be a good complement for conventional autopsy, it was thought to have limited application in cardiovascular pathology. At present, multidetector computed tomography (MDCT), CT angiography, and cardiac magnetic resonance imaging (MRI) are used in postmortem radiological investigation of cardiovascular pathologies. This review presents the actual state of postmortem imaging for cardiovascular pathologies in cases of sudden cardiac death (SCD), taking into consideration both the advantages and limitations. The radiological evaluation of ischemic heart disease (IHD), the most frequent cause of SCD in the general population of industrialized countries, includes the examination of the coronary arteries and myocardium. Postmortem CT angiography (PMCTA) is very useful for the detection of stenoses and occlusions of coronary arteries but less so for the identification of ischemic myocardium. MRI is the method of choice for the radiological investigation of the myocardium in clinical practice, but its accessibility and application are still limited in postmortem practice. There are very few reports implicating postmortem radiology in the investigation of other causes of SCD, such as cardiomyopathies, coronary artery abnormalities, and valvular pathologies. Cardiomyopathies representing the most frequent cause of SCD in young athletes cannot be diagnosed by echocardiography, the most widely available technique in clinical practice for the functional evaluation of the heart and the detection of cardiomyopathies. PMCTA and MRI have the potential to detect advanced stages of diseases when morphological substrate is present, but these methods have yet to be sufficiently validated for postmortem cases. Genetically determined channelopathies cannot be detected radiologically. This review underlines the need to establish the role of postmortem radiology in the diagnosis of SCD.

Myocarditis is a rare manifestation of tuberculosis, often associated with high morbidity and mortality. Cardiac magnetic resonance imaging (MRI) is a critical imaging tool for assessing infiltrative myocardial conditions. We describe the case of an adult patient from a tuberculosis-endemic region who presented with sudden-onset symptomatic arrhythmias. Cardiac MRI findings included heterogeneous signal intensity in the left ventricular myocardium, altered myocardial nulling time, and a patchy \"zebroid-like\" pattern of late gadolinium enhancement. Additionally, necrotic supraclavicular and retroperitoneal lymphadenopathy were observed. Fine-needle aspiration cytology of the affected lymph node revealed epithelioid inflammatory granulomas. The patient was diagnosed with disseminated tuberculosis and tubercular myocarditis. Following the initiation of a standard anti-tubercular regimen, significant clinical improvement was noted at the 2-month follow-up.

BackgroundAortic stenosis (AS) accounts for substantial global morbidity and premature mortality even in moderate AS (Mod-AS). Whilst myocardial remodeling response is considered critical in the adverse prognosis of Mod-AS, the precise mechanisms remain poorly understood. We aimed to prospectively assess myocardial remodeling, perfusion and energetics differences in Mod-AS and severe AS (Severe-AS).MethodsFifty-two Severe-AS and 25 Mod-AS patients and 18 demographically-matched controls underwent cardiovascular magnetic resonance and phosphorus-magnetic resonance spectroscopy to define left ventricular (LV) mass and function, global longitudinal shortening (GLS), rest and adenosine-stress myocardial blood flow (MBF), myocardial perfusion reserve (MPR), layer-specific perfusion metrics (subendocardial [Endo], subepicardial [Epi] MBF and MPR, and Endo-Epi-MBF ratio [Endo/Epi]), myocardial scar on late gadolinium enhancement (LGE) imaging, and myocardial energetics (phosphocreatine:ATP ratio [PCr/ATP]).ResultsCompared to controls, with increasing AS severity, there was progressive increase in LV concentricity (LV-mass/LV-end-diastolic-volume)(controls:0.58[0.54,0.62], Mod-AS:0.74[0.64,0.84], Severe-AS:0.89[0.83,0.95]g/mL;P<0.0001), and stepwise decline in GLS (controls:19.9[17.6,22.2], Mod-AS:17.7[16.6,18.8], Severe-AS:13.4[12.5,14.4]%; P<0.0001) with significant differences between Mod-AS and Severe-AS in all three comparisons. Both stress MBF(controls:2.1[1.9,2.3],Mod-AS:1.9[1.6,2.2],Severe-AS:1.3[1.2,1.5]ml/min/g; P<0.0001) and MPR(controls:3.3[2.8,3.6],Mod-AS:2.8[2.4,3.2], Severe-AS:1.9[1.8,2.1]; P<0.0001) were only significantly reduced in Severe-AS compared to controls, with significant differences also detected between Mod-AS and Severe-AS. However, stress-endo-MBF (controls:2.0[1.8,2.3], Mod-AS:1.7[1.5,2.0], Severe-AS:1.2[1.1,1.3]ml/min/g; P<0.0001), stress-Endo/Epi(controls:1.00[0.93,1.07],Mod-AS:0.87[0.80,0.94],Severe-AS:0.81[0.75,0.82];P<0.0001), rest-Endo/Epi (controls:1.12[1.10,1.14], Mod-AS:1.06[1.03,1.09], Severe-AS:1.03[1.02,1.06]; P<0.0001) and endo-MPR (controls:3.2[2.7,3.6],Mod-AS:2.5[2.1,2.9],Severe-AS:1.7[1.5,1.8]; P<0.0001) were all significantly reduced in both Mod-AS and Severe-AS. Compared to controls, both AS groups showed significantly lower PCr/ATP (controls:2.2[2.0,2.3],Mod-AS:1.8[1.6,2.0],Severe-AS:1.7[1.6,1.8]; P<0.0001). Only the Severe-AS group had evidence of non-ischemic myocardial scar on LGE (2.9[0.0,6.2]%), which was detected in 65%(n=34) of patients. AS severity (peak aortic valve velocity) correlated with stress-MBF (r=-0.45, P=0.0003), MPR (r=-0.44, P=0.0005) and GLS (r=-0.47, P=0.0001).ConclusionsModerate and severe-AS are associated with cardiac concentric hypertrophy, reductions in myocardial energetics, and subendocardial hypoperfusion. Patients with Severe-AS exhibit a more marked phenotype with worse LV hypertrophy, contractile dysfunction and myocardial scarring compared to Mod-AS patients.Conflict of InterestNil

We tested the hypothesis that bidimensional measurements of right ventricular (RV) function obtained by cardiac magnetic resonance imaging (CMR) in patients with pulmonary arterial hypertension (PAH) are faster than volumetric measures and highly reproducible, with comparable ability to predict patient survival. CMR-derived tricuspid annular plane systolic excursion (TAPSE), RV fractional shortening (RVFS), RV fractional area change (RVFAC), standard functional and volumetric measures, and ventricular mass index (VMI) were compared with right heart catheterization data. CMR analysis time was recorded. Receiver operating characteristic curves, Kaplan-Meier, Cox proportional hazard (CPH), and Bland-Altman test were used for analysis. Forty-nine subjects with PAH and 18 control subjects were included. TAPSE, RVFS, RVFAC, RV ejection fraction, and VMI correlated significantly with pulmonary vascular resistance and mean pulmonary artery pressure (all P < 0.05). Patients were followed up for a mean (± standard deviation) of 2.5 ± 1.6 years. Kaplan-Meier curves showed that death was strongly associated with TAPSE <18 mm, RVFS <16.7%, and RVFAC <18.8%. In CPH models with TAPSE as dichotomized at 18 mm, TAPSE was significantly associated with risk of death in both unadjusted and adjusted models (hazard ratio, 4.8; 95% confidence interval, 2.0–11.3; P = 0.005 for TAPSE <18 mm). There was high intra- and interobserver agreement. Bidimensional measurements were faster (1.5 ± 0.3 min) than volumetric measures (25 ± 6 min). In conclusion, TAPSE, RVFS, and RVFAC measures are efficient measures of RV function by CMR that demonstrate significant correlation with invasive measures of PAH severity. In patients with PAH, TAPSE, RVFS, and RVFAC have high intra- and interobserver reproducibility and are more rapidly obtained than volumetric measures. TAPSE <18 mm by CMR was strongly and independently associated with survival in PAH.

Measurements of cardiac size and function drive clinical decisions. Left ventricle (LV) metrics can be derived from cardiac MR images by delineating the blood pool and myocardium, by either drawing a rounded contour to approximate the compacted myocardial border, or by delineating the papillary muscles and trabeculae (trabecular segmentation). There is no consensus as to which is best, particularly in the emergent AI era. We developed machine-learning (ML) approaches for both and compared them for clinically important metrics (error rate, precision, and prognosis). Separate ML models were developed for rounded and trabecular segmentation, using U-net models trained on 1,923 subjects (mixed pathology, multiple scanners, multiple centres). Blood and myocardial volumes for each segmentation method were compared on 4,118 healthy UK biobank subjects. Model segmentation quality was evaluated subjectively on a real-world clinical dataset of 1,594 consecutive CMR scans, with all scans included regardless of image quality and artefacts. Scan-rescan precision was measured on a multi-centre, multi-disease dataset of 109 subjects scanned twice and compared to human performance. Finally, prognostication ability was evaluated on 1,215 clinical patients, using a primary outcome of all-cause mortality and hospitalisation with heart failure. Error rates (where a human disagreed by >1ml) were the same, occurring in 0.6% of images and 3.6% (1 in 28) of patients. In health, the mean EF was 4% higher for trabecular vs rounded segmentation. On test-retest data, there was no difference between rounded and trabecular ML models for precision, apart from end-diastolic and end systolic volume, which was better for rounded segmentations. ML rounded and trabecular precision exceeded clinician performance for EF. There were marginal differences in prognostication between rounded and trabecular models. We developed an automated method for annotating papillary muscles and trabeculae from cardiac MR images with low error rates. We found higher precision than clinicians in ejection fraction. There was similar precision and prognostication to an ML rounded model with similarly low error rates. Findings support the feasibility of automated trabecular segmentation in clinical care and clinical trials. [Display omitted]

The Hamburg City Health Study (HCHS) is a large, prospective, long-term, population-based cohort study and a unique research platform and network to obtain substantial knowledge about several important risk and prognostic factors in major chronic diseases. A random sample of 45,000 participants between 45 and 74 years of age from the general population of Hamburg, Germany, are taking part in an extensive baseline assessment at one dedicated study center. Participants undergo 13 validated and 5 novel examinations primarily targeting major organ system function and structures including extensive imaging examinations. The protocol includes validate self-reports via questionnaires regarding lifestyle and environmental conditions, dietary habits, physical condition and activity, sexual dysfunction, professional life, psychosocial context and burden, quality of life, digital media use, occupational, medical and family history as well as healthcare utilization. The assessment is completed by genomic and proteomic characterization. Beyond the identification of classical risk factors for major chronic diseases and survivorship, the core intention is to gather valid prevalence and incidence, and to develop complex models predicting health outcomes based on a multitude of examination data, imaging, biomarker, psychosocial and behavioral assessments. Participants at risk for coronary artery disease, atrial fibrillation, heart failure, stroke and dementia are invited for a visit to conduct an additional MRI examination of either heart or brain. Endpoint assessment of the overall sample will be completed through repeated follow-up examinations and surveys as well as related individual routine data from involved health and pension insurances. The study is targeting the complex relationship between biologic and psychosocial risk and resilience factors, chronic disease, health care use, survivorship and health as well as favorable and bad prognosis within a unique, large-scale long-term assessment with the perspective of further examinations after 6 years in a representative European metropolitan population.

IntroductionCardiovascular magnetic resonance (CMR) is recommended in both NICE and ESC guidelines in patients with new onset left ventricular systolic dysfunction (LVSD) to identify aetiology. In patients with LVSD, type 2 diabetes is associated with increased prevalence of silent myocardial infarction (MI). We aimed to investigate if silent MI in patients with LVSD are larger in diabetic compared to non-diabetic patients.MethodsClinical and CMR data from 156 patients who underwent cardiac MRI to determine the aetiology of left ventricular systolic dysfunction and were found to have evidence of a silent myocardial infarction were analysed. Patients were identified from two ongoing studies (National Research Ethics Committee numbers 17/YH/0300 and 21/PR/0318) Exclusion criteria were any history of chest pain, prior myocardial infarction, and previous revascularisation.Patients were categorised into normoglycaemia, pre-diabetic and diabetic groups according to previous diagnosis and HbA1c (diabetes HbA1c >47mmol/mol, prediabetes 42-47mmol/mol). Size of MI was quantified by scoring the number of affected segments according to the American Heart Association 16-segement model.ResultsOverall, there were 156 individuals, with 124 (79.4%) of these being male and a mean age of 66.6 years ± 10.45. Of our cohort 47 patients (30%) were defined as diabetic, 31 (20%) as pre-diabetic and 78 (50%) as normoglycaemic.Inferior and infero-lateral infarcts were most affected by silent infarction, and this was consistent between non, pre and diabetic patients, with segment 5 (basal inferolateral) being the most affected segment in both non-diabetics and diabetics (42.3% of non-diabetics and 46.8% of diabetics), and segment 15 (apical inferior) in pre-diabetics (48.5%).In normoglycaemic patients the mean number of infarcted segments was 3.91±2.84, compared to 4.84±3.31 in pre-diabetic patients and 4.09±2.63 in diabetics.DiscussionOur data did not reveal an association between infarct size and diabetes status in a population of patients who have had a silent myocardial infarct. Inferior and inferolateral segments were the most affected by silent myocardial infarcts, however, this was also not associated with diabetes status.Abstract 179 Table 1Clinical and CMR findings of patients of patients being investigated for LVSD according to glycaemic status Diabetes (n=47) Prediabetes (n=31) Normoglycaemic (n=78) P value Age 65.6±10.368±9.666.6±10.70.62 Male (%) 38 (80.1)28 (90.3)58 (74.4)0.29 Current Smoker (%) 17 (36.2)13 (41.9)11 (14.1)0.002 Hypertension (%) 29 (61.7)14 (45.2)34 (43.6)0.13 Hypercholesterolaemia (%) 17 (36.2)10 (32.3)21 (26.9)0.54 AF (%) 16 (34.0)5 (16.1)20 (25.6)0.21 LVEDV 243.5±62.2240.2±80.2236.2±92.90.89 LVEF 30.6±8.435.6±13.237.2±13.10.01 No of infarcted segments 4.1±2.64.8±3.33.9±2.80.31Abstract 179 Figure 1AHA 16 segment plots showing the distribution of silent myocardial infarction according to glycaemic statusConflict of InterestNil