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Background Patients with cancer are at an increased risk of thrombus formation, often identified on routine echocardiogram in the right atrium. The 2022 ESC Guidelines on Cardio-oncology emphasize cardiac magnetic resonance (CMR) as the gold standard for thrombus identification. Case summary We present a case series of seven patients who underwent CMR due to right atrial mass suspected to result from central venous catheter–related right atrial thrombus. In all cases, CMR enabled accurate diagnosis of a thrombus. It also allowed to assess complete or partial resolution of the thrombi following anticoagulation on follow-up studies. Discussion The presence of a central venous catheter is recognized as a risk factor for thrombus formation, particularly when inappropriately advanced into the right atrium. The integration of CMR into the diagnostic pathway enabled precise thrombus identification and guidance for treatment in this population with a complex balance between cancer-related thrombotic and haemorrhagic risks. [ABSTRACT FROM AUTHOR]

Aims  Eosinophilic heart disease (EHD) is a rare cardiac condition with a wide spectrum of phenotypes. The diagnostic and prognostic value of cardiac magnetic resonance (CMR) in EHD remains unknown. Methods and results  This was a retrospective analysis of 250 patients with eosinophilia referred for a CMR scan (period 2000–2020). CMR data sets and clinical/laboratory data were collected. Patients were followed up for a mean of 24 months (range 1–224) for the composite endpoint of death, acute coronary syndrome, hospitalization for acute heart failure, malignant ventricular arrhythmias, or the need for implantable cardiac defibrillator/pacemaker. The main objectives were to explore the diagnostic value of CMR in EHD; relationships between cardiac function, late gadolinium enhancement (LGE), and EHD phenotypes; and the prognostic value of fibrosis and oedema by CMR. The prevalence of findings compatible with EHD was 39% (patients with cardiac symptoms: 57% vs. screening: 20%, P  < 0.001). EHD phenotypes included subendocardial LGE (n  = 58), mid-wall/subepicardial LGE (n  = 26), pericarditis (n  = 5) or dilated cardiomyopathy (n  = 8). Myocardial oedema was present in 10% of patients. Intracardiac thrombi (7%) were associated with EHD phenotype (χ 2=47.3, P  = 1.3×10−8). LGE extent correlated with LVEDVi (rho = 0.268, P  = 5.3×10−5) and LVEF (rho=−0.415, P  = 8.6×10−11). A CMR scan positive for EHD [hazard ratio (HR) = 5.61, 95% confidence interval (CI): 1.82–17.89, P  = 0.0026] or a subendocardial LGE pattern (HR = 5.13, 95% CI: 1.29–20.38, P  = 0.020) were independently associated with the composite clinical endpoint. Conclusion  The diagnostic yield of CMR screening in patients with persistent eosinophilia, even if asymptomatic, is high. The extent of subendocardial fibrosis correlates with LV remodelling and independently predicts clinical outcomes in patients with eosinophilia. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present two registration algorithms for the spatio-temporal alignment of cardiac MR image sequences. Both algorithms have the ability to correct spatial misalignment between the images sequences caused by global and local shape differences. In addition, they have the ability to correct temporal misalignment caused by differences in the length of the cardiac cycles and by differences in the dynamic properties of the hearts. The algorithms use a 4D deformable transformation model which is separated into spatial and temporal components. The first registration algorithm optimizes the spatial and temporal transformation models simultaneously, while the second registration algorithm optimizes the temporal transformation component before optimizing the spatial component. For the evaluation of the spatio-temporal registration methods we have acquired 15 MR image sequences from healthy volunteers. The registration methods were quantitatively evaluated by measuring the overlap and surface distance of anatomical regions and qualitatively by visual inspection. The results demonstrate that a significant improvement in the alignment of the image sequences is achieved by the use of the deformable spatio-temporal transformation model. We demonstrate the use of the method for the construction of a probabilistic MR cardiac atlas representing the anatomy and function of a healthy heart. [Copyright &y& Elsevier]

In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is proposed. The algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. The EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate a priori information into the classification process. The probabilistic cardiac atlas has been constructed from the manual segmentations of 3D cardiac image sequences of 14 healthy volunteers. It provides space and time-varying probability maps for the left and right ventricles, the myocardium, and background structures such as the liver, stomach, lungs and skin. In addition to using the probabilistic cardiac atlas as a priori information, the segmentation algorithm incorporates spatial and temporal contextual information by using 4D Markov Random Fields. After the classification, the largest connected component of each structure is extracted using a global connectivity filter which improves the results significantly, especially for the myocardium. Validation against manual segmentations and computation of the correlation between manual and automatic segmentation on 249 3D volumes were calculated. We used the ''leave one out'' test where the image set to be segmented was not used in the construction of its corresponding atlas. Results show that the procedure can successfully segment the left ventricle (LV) (r=0.96), myocardium (r=0.92) and right ventricle (r=0.92). In addition, 4D images from 10 patients with hypertrophic cardiomyopathy were also manually and automatically segmented yielding a good correlation in the volumes of the LV (r=0.93) and myocardium (0.94) when the atlas constructed with volunteers is blurred. [Copyright &y& Elsevier]