First-in-Human Transapical Beating-Heart Septal Myectomy in Patients With Hypertrophic Obstructive Cardiomyopathy.

BACKGROUND: To simplify surgical septal reduction therapy for hypertrophic obstructive cardiomyopathy (HOCM), we developed a novel transapical beating-heart septal myectomy (TA-BSM) procedure. OBJECTIVES: In this study, we sought to evaluate the clinical utility of TA-BSM in a first-in-human trial. METHODS: Patients with HOCM were enrolled if they presented with drug-refractory disabling symptoms. TA-BSM was performed via minithoracotomy with the use of our beating-heart myectomy device under echocardiographic guidance, without the use of cardiopulmonary bypass. Repeated resections were performed to tailor the extent of the septal myectomy for sufficient abolishment of left ventricular outflow tract (LVOT) obstruction and mitral regurgitation (MR). The primary outcome measure was procedural success, defined by resting/provoked LVOT gradient <30/50 mm Hg and residual MR grade ≤1+ (of 4+) at 3-month follow-up. RESULTS: A total of 47 patients aged 12 to 77 years were enrolled. Of the 46 patients who were followed for 3 months, 42 achieved procedural success. The maximal LVOT gradient decreased from 86 mm Hg (IQR: 67-114 mm Hg) at baseline to 19 mm Hg (IQR: 14-28 mm Hg) at 3 months. MR grade was ≤1+ in 3 patients at baseline and in 45 patients at 3 months. One patient died on postoperative day 10 owing to device-unrelated reasons. Other major adverse events included 1 delayed ventricular septal perforation and 1 intraoperative left ventricular apical tear. CONCLUSIONS: TA-BSM is a safe and efficient minimally invasive procedure for septal reduction of heterogeneous HOCM. Compared with conventional septal myectomy, TA-BSM provides real-time evaluation to guide resection while reducing surgical trauma. (Transapical Beating-Heart Septal Myectomy in Patients With Hypertrophic Obstructive Cardiomyopathy; NCT05332691).

Predicting Left Ventricular Myocardial Fibrosis in Patients with Hypertrophic Cardiomyopathy by Speckle Tracking Automated Functional Imaging.

OBJECTIVE: The study was performed to explore the predictive value of multiple strain parameters for myocardial fibrosis in patients with hypertrophic cardiomyopathy (HCM) by using speckle tracking automated functional imaging (AFI). METHODS: A total of 61 patients diagnosed with HCM were finally enrolled in this study. All patients completed transthoracic echocardiography and cardiac magnetic resonance late gadolinium enhancement (LGE) within 1 month. Twenty age- and sex-matched healthy participants were included as the control group. Multiple parameters, including segmental longitudinal strain (LS), global longitudinal strain (GLS), post-systolic index and peak strain dispersion, were automatically analyzed by AFI. RESULTS: A total of 1458 myocardial segments were analyzed according to the left ventricular 18-segment model. Among the 1098 segments from HCM patients, segments with LGE had a lower absolute value of segmental LS than those without LGE (p < 0.05). The cutoff values of segmental LS for predicting positive LGE in the basal, intermediate and apical regions were -12.5%, -11.5% and -14.5%, respectively. GLS could predict significant myocardial fibrosis (≥2 positive LGE segments) at a cutoff value of -16.5% with a sensitivity of 80.9% and specificity of 76.5%. As an independent predictor of significant myocardial fibrosis, GLS was substantially associated with the severity of myocardial fibrosis and 5 years sudden cardiac death risk score in HCM patients. CONCLUSION: Speckle tracking AFI could efficiently identify left ventricular myocardial fibrosis in patients with HCM by multiple parameters. GLS predicted significant myocardial fibrosis at a cutoff value of -16.5%, which may indicate the adverse clinical outcomes in HCM patients.

Quantitative assessment of right ventricular size and function with multiple parameters from artificial intelligence-based three-dimensional echocardiography: A comparative study with cardiac magnetic resonance.

AIMS: This study aimed to explore the validation and the diagnostic value of multiple right ventricle (RV) volumes and functional parameters derived from a novel artificial intelligence (AI)-based three-dimensional echocardiography (3DE) algorithm compared to cardiac magnetic resonance (CMR). METHODS AND RESULTS: A total of 51 patients with a broad spectrum of clinical diagnoses were finally included in this study. AI-based RV 3DE was performed in a single-beat HeartModel mode within 24 hours after CMR. In the entire population, RV volumes and right ventricular ejection fraction (RVEF) measured by AI-based 3DE showed statistically significant correlations with the corresponding CMR analysis (p < 0.05 for all). However, the Bland-Altman plots indicated that these parameters were slightly underestimated by AI-based 3DE. Based on CMR derived RVEF < 45% as RV dysfunction, end-systolic volume (ESV), end-systolic volume index (ESVi), stroke volume (SV), and RVEF showed great diagnostic performance in identifying RV dysfunction, as well as some non-volumetric parameters, including tricuspid annular systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strains (LS) (p < 0.05 for all). The cutoff value was 43% for RVEF with a sensitivity of 94% and specificity of 67%. CONCLUSION: AI-based 3DE could provide rapid and accurate quantitation of the RV volumes and function with multiple parameters. Both volumetric and non-volumetric measurements derived from AI-based 3DE contributed to the identification of the RV dysfunction.