Percutaneous transluminal septal myocardial ablation for hypertrophic obstructive cardiomyopathy through non-left anterior descending septal perforators.
Yoichi ImoriHitoshi TakanoMitsunobu KitamuraRie AoyamaHideto SangenOnodera KentaJunya MatsudaYoshiaki KubotaYukichi TokitaTakeshi YamamotoKuniya AsaiMorimasa TakayamaWataru ShimizuPublished in: Heart and vessels (2019)
Percutaneous transluminal septal myocardial ablation (PTSMA) has become a significant treatment for symptomatic patients with hypertrophic obstructive cardiomyopathy (HOCM) despite maximal medical therapy. The target septal arteries usually arise from the left anterior descending artery (LAD). However, when septal perforators do not originate from the LAD, non-LAD septal perforators should be included as candidate-target septal branches that feed the hypertrophic septal myocardium, causing left ventricular outflow tract (LVOT) obstruction. Data pertaining to the procedure remain limited. We aimed to investigate PTSMA through the non-LAD septal perforators in patients with HOCM. In this case series review, we evaluated the baseline characteristics, echocardiographic features, and angiographic features, as well as symptoms and pressure gradient before and after PTSMA through the non-LAD septal perforators. Among 202 consecutive patients who underwent PTSMA for HOCM with LVOT obstruction, 21 had non-LAD septal branches that fed the hypertrophic septal myocardium and received alcohol ablation. Non-LAD septal perforators could be used as an alternative route for PTSMA in patients who experienced ineffective ablation of the septal branch that arises from the LAD. This unique procedure may improve response rates and overall outcomes of patients with HOCM.
Keyphrases
- hypertrophic cardiomyopathy
- left ventricular
- heart failure
- stem cells
- healthcare
- type diabetes
- chronic kidney disease
- mitral valve
- heart rate
- metabolic syndrome
- ejection fraction
- adipose tissue
- physical activity
- blood pressure
- mesenchymal stem cells
- prognostic factors
- acute myocardial infarction
- newly diagnosed
- artificial intelligence
- deep learning
- depressive symptoms
- skeletal muscle
- ultrasound guided
- blood flow
- resistance training