Intrafamilial Phenotypical Variability Linked to PRKAG2 Mutation—Family Case Report and Review of the Literature

PRKAG2 syndrome (PS) is a rare, early-onset autosomal dominant phenocopy of sarcomeric hypertrophic cardiomyopathy (HCM), that mainly presents with ventricular pre-excitation, cardiac hypertrophy and progressive conduction system degeneration. Its natural course, treatment and prognosis are significantly different from sarcomeric HCM. The clinical phenotypes of PRKAG2 syndrome often overlap with HCM due to sarcomere protein mutations, causing this condition to be frequently misdiagnosed. The syndrome is caused by mutations in the gene encoding for the γ2 regulatory subunit (PRKAG2) of 5′ Adenosine Monophosphate-Activated Protein Kinase (AMPK), an enzyme that modulates glucose uptake and glycolysis. PRKAG2 mutations (OMIM#602743) are responsible for structural changes of AMPK, leading to an impaired myocyte glucidic uptake, and finally causing storage cardiomyopathy. We describe the clinical and investigative findings in a family with several affected members (NM_016203.4:c.905G>A or p.(Arg302Gln), heterozygous), highlighting the various phenotypes even in the same family, and the utility of genetic testing in diagnosing PS. The particularity of this family case is represented by the fact that the index patient was diagnosed at age 16 with cardiac hypertrophy and ventricular pre-excitation while his mother, by age 42, only had Wolff–Parkinson–White syndrome, without left ventricle hypertrophy. Both the grandmother and the great-grandmother underwent pacemaker implantation at a young age because of conduction abnormalities. Making the distinction between PS and sarcomeric HCM is actionable, given the early-onset of the disease, the numerous life-threatening consequences and the high rate of conduction disorders. In patients who exhibit cardiac hypertrophy coexisting with ventricular pre-excitation, genetic screening for PRKAG2 mutations should be considered

Echocardiography Assessment of Cardiac Function in Adults Living with HIV: A Speckle Tracking Study in the Era of Antiretroviral Therapy

Adults living with HIV (human immunodeficiency virus) infection (ALHIV) have high rates of cardiovascular events. New approaches are needed to detect subclinical cardiac dysfunction. We used conventional and speckle tracking echocardiography to investigate whether ALHIV display latent cardiac dysfunction. We analyzed 85 young subjects with HIV infection and free from cardiovascular risk factors (31 ± 4 years) and 80 matched healthy volunteers. We measured left ventricular (LV) layered global longitudinal strain, circumferential strain, peak longitudinal strain in the reservoir and contraction phases of the left atrium (LASr respectively LASct). In the HIV group, LV ejection fraction and s’ TDI (tissue doppler imaging) were slightly lower but still in the normal ranges. Layered longitudinal strain showed no significant difference, whereas circumferential global strain was significantly lower in the HIV group (−20.3 ± 3.9 vs. −22.3 ± 3.0, p < 0.001). LASr (34.3% ± 7.3% vs. 38.0% ± 6.9%, p < 0.001) was also lower in ALHIV and multivariate analysis showed that age (β = −0.737, p = 0.01) and infection duration (β = −0.221, p = 0.02) were independently associated with LASr. In the absence of cardiovascular risk factors, adults living with HIV display normal LV systolic function. Left atrial reservoir strain, is, however, decreased and suggests early diastolic dysfunction

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) - a study protocol for developing an automated intelligent decision support system for early fetal echocardiography

Abstract Background Congenital Heart Disease represents the most frequent fetal malformation. The lack of prenatal identification of congenital heart defects can have adverse consequences for the neonate, while a correct prenatal diagnosis of specific cardiac anomalies improves neonatal care neurologic and surgery outcomes. Sonographers perform prenatal diagnosis manually during the first or second-trimester scan, but the reported detection rates are low. This project’s primary objective is to develop an Intelligent Decision Support System that uses two-dimensional video files of cardiac sweeps obtained during the standard first-trimester fetal echocardiography (FE) to signal the presence/absence of previously learned key features. Methods The cross-sectional study will be divided into a training part of the machine learning approaches and the testing phase on previously unseen frames and eventually on actual video scans. Pregnant women in their 12–13 + 6 weeks of gestation admitted for routine first-trimester anomaly scan will be consecutively included in a two-year study, depending on the availability of the experienced sonographers in early fetal cardiac imaging involved in this research. The Data Science / IT department (DSIT) will process the key planes identified by the sonographers in the two- dimensional heart cine loop sweeps: four-chamber view, left and right ventricular outflow tracts, three vessels, and trachea view. The frames will be grouped into the classes representing the plane views, and then different state-of-the- art deep-learning (DL) pre-trained algorithms will be tested on the data set. The sonographers will validate all the intermediary findings at the frame level and the meaningfulness of the video labeling. Discussion FE is feasible and efficient during the first trimester. Still, the continuous training process is impaired by the lack of specialists or their limited availability. Therefore, in our study design, the sonographer benefits from a second opinion provided by the developed software, which may be very helpful, especially if a more experienced colleague is unavailable. In addition, the software may be implemented on the ultrasound device so that the process could take place during the live examination. Trial registration The study is registered under the name „Learning deep architectures for the Interpretation of Fetal Echocardiography (LIFE)”, project number 408PED/2020, project code PN-III-P2–2.1-PED-2019. Trial registration: ClinicalTrials.gov , unique identifying number NCT05090306, date of registration 30.10.2020