RESUMEN
Background: Left ventricular noncompaction (LVNC) cardiomyopathy is a disorder that can be complicated by heart failure, arrhythmias, thromboembolism, and sudden cardiac death. The aim of this study is to clarify the genetic landscape of LVNC in a large cohort of well-phenotyped Russian patients with LVNC, including 48 families (n=214). Methods: All index patients underwent clinical examination and genetic analysis, as well as family members who agreed to participate in the clinical study and/or in the genetic testing. The genetic testing included next generation sequencing and genetic classification according to ACMG guidelines. Results: A total of 55 alleles of 54 pathogenic and likely pathogenic variants in 24 genes were identified, with the largest number in the MYH7 and TTN genes. A significant proportion of variants -8 of 54 (14.8%) -have not been described earlier in other populations and may be specific to LVNC patients in Russia. In LVNC patients, the presence of each subsequent variant is associated with increased odds of having more severe LVNC subtypes than isolated LVNC with preserved ejection fraction. The corresponding odds ratio is 2.77 (1.37 -7.37; p <0.001) per variant after adjustment for sex, age, and family. Conclusion: Overall, the genetic analysis of LVNC patients, accompanied by cardiomyopathy-related family history analysis, resulted in a high diagnostic yield of 89.6%. These results suggest that genetic screening should be applied to the diagnosis and prognosis of LVNC patients.
RESUMEN
OBJECTIVES: The objective of this work was to develop technology to create 'soft' patient-specific models of semilunar heart valves, the aortic valve in particular, suitable for training and simulation of surgical and endovascular interventions. METHODS: Data obtained during routine cardiac contrast-enhanced multislice computed tomography were used to create 3-dimensional models of the aortic root. Three-dimensional models were used to create soft silicone models of the aortic root made by casting silicone into a negative mould printed with stereolithography. A comparison between the constructed models and the size of the aortic root was performed. We quantified how much time was needed for production of each model. RESULTS: Four patient-specific soft models of the aortic root were produced. Data from patients of different ages and body surface areas were used as prototypes. All models had minimum size errors. During development of this technology, production time per model was reduced from 63 to 39 h. CONCLUSIONS: We have demonstrated the feasibility of making soft patient-specific 3-dimensional aortic root models using currently available technology. These models can be used both for training physicians in a variety of open surgical and endovascular interventions and for the study of complex aortic root geometry.
