To assess the accuracy of different hardware and software settings for left ventricular (LV) volume quantification in children using real-time three-dimensional echocardiography (RT3DE). The impact of different matrix transducers (IE 33, X3-1 and VIVID 7, V3) and quantification software settings [TOMTEC; contour-finding activity (tCFA) values ranging from 30 to 70 U] on the accuracy of LV indices was tested in 24 healthy children/adolescents (median = 12.6 years) and 25 paediatric patients with Tetralogy-of-Fallot (TOF) (median = 7.3 years) with abnormally shaped ventricles. RT3DE was compared with cardiovascular magnetic resonance (CMR) volumetry as reference. Best agreement (Bland–Altman analysis) was achieved using a tCFA value of 30 U. Applying the V3 device, end-diastolic volume (EDV) and end-systolic volume (ESV) were underestimated by 14.8 ± 10.6% (mean ± SD) and 11.2 ± 16.3%, respectively ( r = 9.42, P < 0.001 and r = 0.937, P = 0.003); with the X3-1 system 24.2 ± 11.0 and 14.6 ± 15.2%, respectively ( r = 0.951, P < 0.001 and r = 0.912, P = 0.001). Negligible differences <1% ( P = n.s.) between both transducers were detected applying a tCFA value of 70 U but with significant underestimation (EDV: ∼35%, P < 0.001; ESV: ∼26%, P < 0.001) compared with CMR. EDV and ESV of TOF patients were underestimated by 3.2 ± 15.4 and 8.1 ± 22.6%, respectively. Intra- and interobserver variability was <4%. In contrast to recommendations of the manufacturer, data sets from both RT3DE transducers showed acceptable agreement to CMR for volumetric parameters only for low tCFA. Fine-tuning of software settings is mandatory to improve accuracy.

About 50% of patients with arrhythmogenic cardiomyopathy (ACM) carry a pathogenic or likely pathogenic mutation in the desmosomal genes. However, there is a significant number of patients without positive familial anamnesis. Therefore, the molecular reasons for ACM in these patients are frequently unknown and a genetic contribution might be underestimated. Here, we used a next-generation sequencing (NGS) approach and in addition single nucleotide polymor-phism (SNP) arrays for the genetic analysis of two independent index patients without familial medical history. Of note, this genetic strategy revealed a homozygous splice site mutation (DSG2–c.378+1G>T) in the first patient and a nonsense mutation (DSG2–p.L772X) in combination with a large deletion in DSG2 in the second one. In conclusion, a recessive inheritance pattern is likely for both cases, which might contribute to the hidden medical history in both families. This is the first report about these novel loss-of-function mutations in DSG2 that have not been previously identi-fied. Therefore, we suggest performing deep genetic analyses using NGS in combination with SNP arrays also for ACM index patients without obvious familial medical history. In the future, this finding might has relevance for the genetic counseling of similar cases.