Tricuspid mass-curious case of Li-Fraumeni syndrome: A case report.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a rare autosomal dominant cancer-predisposing syndrome, which can manifest as a polymorphic spectrum of malignancies. LFS is associated with an early onset in life, with the majority of cases occurring prior to the age of 46. Notwithstanding the infrequency of primary cardiac tumors, it behooves clinicians to remain vigilant in considering the differential diagnosis of such tumors in LFS patients who present with a cardiac mass. This is due to the markedly elevated risk for malignancy in this particular population, far surpassing that of the general populace. CASE SUMMARY: Herein, we present a case of a 30-year-old female with LFS who was found to have a tricuspid valve leaflet mass. CONCLUSION: This case exemplifies valuable learning points in the diagnostic approach for this exceptionally rare patient population.

Artificial Intelligence to derive aligned strain in cine CMR to detect patients with myocardial fibrosis: an open and scrutinizable approach.

Cine Cardiac Magnetic Resonance (CMR) is the gold standard for cardiac function evaluation, incorporating ejection fraction (EF) and strain as vital indicators of abnormal deformation. Rare pathologies like Duchenne muscular dystrophies (DMD) are monitored with repeated late gadolinium-enhanced (LGE) CMR for identification of myocardial fibrosis. However, it is judicious to reduce repeated gadolinium exposure and rather employ strain analysis from cine CMR. This solution is limited so far since full strain curves are not comparable between individual cardiac cycles and current practice mainly neglects diastolic deformation patterns. Our novel Deep Learning-based approach derives strain values aligned by key frames throughout the cardiac cycle. In a reproducibility scenario (57+82 patients), our results reveal five times more significant differences (22 vs. 4) between patients with scar and without, enhancing scar detection by +30%, improving detection of patients with preserved EF by +61%, with an overall sensitivity/specificity of 82/81%.

Le Cœur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot.

BACKGROUND: Maladaptive remodelling mechanisms occur in patients with repaired tetralogy of Fallot (rToF) resulting in a cycle of metabolic and structural changes. Biventricular shape analysis may indicate mechanisms associated with adverse events independent of pulmonary regurgitant volume index (PRVI). We aimed to determine novel remodelling patterns associated with adverse events in patients with rToF using shape and function analysis. METHODS: Biventricular shape and function were studied in 192 patients with rToF (median time from TOF repair to baseline evaluation 13.5 years). Linear discriminant analysis (LDA) and principal component analysis (PCA) were used to identify shape differences between patients with and without adverse events. Adverse events included death, arrhythmias, and cardiac arrest with median follow-up of 10 years. RESULTS: LDA and PCA showed that shape characteristics pertaining to adverse events included a more circular left ventricle (LV) (decreased eccentricity), dilated (increased sphericity) LV base, increased right ventricular (RV) apical sphericity, and decreased RV basal sphericity. Multivariate LDA showed that the optimal discriminative model included only RV apical ejection fraction and one PCA mode associated with a more circular and dilated LV base (AUC = 0.77). PRVI did not add value, and shape changes associated with increased PRVI were not predictive of adverse outcomes. CONCLUSION: Pathological remodelling patterns in patients with rToF are significantly associated with adverse events, independent of PRVI. Mechanisms related to incident events include LV basal dilation with a reduced RV apical ejection fraction.

Feasibility and safety of quantitative adenosine stress perfusion cardiac magnetic resonance imaging in pediatric heart transplant patients with and without coronary allograft vasculopathy.

BACKGROUND: Pediatric heart transplant patients require cardiac catheterization to monitor for coronary allograft vasculopathy. Cardiac catheterization has no safe and consistent method for measuring microvascular disease. Stress perfusion cardiac magnetic resonance imaging (MRI) assessing microvascular disease has been performed in adults. OBJECTIVE: To investigate the feasibility and safety of performing cardiac MRI with quantitative adenosine stress perfusion testing in pediatric heart transplant patients with and without coronary allograft vasculopathy. MATERIALS AND METHODS: All pediatric heart transplant patients with coronary vasculopathy at our institution were asked to participate. Age- and gender-matched pediatric heart transplant patients without vasculopathy were recruited for comparison. Patients underwent cardiac MRI with adenosine stress perfusion testing. RESULTS: Sixteen pediatric heart transplant patients, ages 6-22 years, underwent testing. Nine patients had vasculopathy by angiography. No heart block or other complications occurred during the study. The myocardial perfusion reserve for patients with vasculopathy showed no significant difference with comparison patients (median: 1.43 vs. 1.48; P=0.49). Values for both groups were lower than expected values based on previous adult studies. The patients were also analyzed for time after transplant and the number of rejection episodes. Patients within 6 years of transplantation had a nonsignificant trend toward a higher myocardial perfusion reserve (median: 1.57) versus patients with older transplants (median: 1.47; P=0.46). Intra- and interobserver reproducibility were 97% and 92%, respectively. CONCLUSION: Myocardial perfusion reserve is a safe and feasible method for estimating myocardial perfusion in pediatric heart transplant patients. There is no reliable way to monitor microvascular disease in pediatric patients. This method shows potential and deserves investigation in a larger cohort.

Unsupervised Domain Adaptation From Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks.

Anisotropic multi-slice Cardiac Magnetic Resonance (CMR) Images are conventionally acquired in patient-specific short-axis (SAX) orientation. In specific cardiovascular diseases that affect right ventricular (RV) morphology, acquisitions in standard axial (AX) orientation are preferred by some investigators, due to potential superiority in RV volume measurement for treatment planning. Unfortunately, due to the rare occurrence of these diseases, data in this domain is scarce. Recent research in deep learning-based methods mainly focused on SAX CMR images and they had proven to be very successful. In this work, we show that there is a considerable domain shift between AX and SAX images, and therefore, direct application of existing models yield sub-optimal results on AX samples. We propose a novel unsupervised domain adaptation approach, which uses task-related probabilities in an attention mechanism. Beyond that, cycle consistency is imposed on the learned patient-individual 3D rigid transformation to improve stability when automatically re-sampling the AX images to SAX orientations. The network was trained on 122 registered 3D AX-SAX CMR volume pairs from a multi-centric patient cohort. A mean 3D Dice of 0.86 ± 0.06 for the left ventricle, 0.65 ± 0.08 for the myocardium, and 0.77 ± 0.10 for the right ventricle could be achieved. This is an improvement of 25% in Dice for RV in comparison to direct application on axial slices. To conclude, our pre-trained task module has neither seen CMR images nor labels from the target domain, but is able to segment them after the domain gap is reduced. Code: https://github.com/Cardio-AI/3d-mri-domain-adaptation.