Atrioventricular nodal reentry tachycardia treatment using CARTO 3 V7 activation mapping: a new era of slow pathway radiofrequency ablation is under coming.

Background: Slow pathway (SP) ablation is the cornerstone for atrioventricular nodal reentry tachycardia (AVNRT) treatment, and a low-voltage bridge offers a good target during mapping using low x-ray exposure. We aimed to assess a new tool to identify SP by activation mapping using the last CARTO3® version, i.e., CARTO PRIME® V7 (Biosense Webster, Diamond Bar, CA, USA). Methods and results: Right atrial septum and triangle of Koch 3D-activation map were obtained from intracardiac contact mapping during low x-ray CARTO 3® procedure. In 60 patients (mean age 60.3 ± 14.7, 61% females) undergoing ablation for AVNRT, an automatic activation map using a DECANAV® mapping catheter and CARTO® Confidense™, Coherent, and FAM DX software modules were obtained. The SP was identified in all patients as the latest atrioventricular node activation area; RF catheter ablation (RFCA) in that region elicited junctional beats. The mean procedural time was 150.3 ± 48.3 min, the mean fluoroscopy time exposure was 2.9 ± 2 min, the mean dose-area product (DAP) was 16.5 ± 2.7 cGy/cm2. The mean number of RF applications was 3.9 ± 2, the mean ablation index was 428.6 ± 96.6, and the mean contact force was 8 ± 2.8 g. There were no adverse event during the procedure, and no AVNRT recurrences occurred during a mean follow-up of 14.3 ± 8.3 months. Conclusion: Ablation of the SP by automatic mapping using Confidense™, Coherent, and FAM DX software modules is an innovative, safe, and effective approach to AVNRT ablation. The CARTO3® V7 system shows on a 3D map the latest AV node activation area during sinus rhythm allowing low fluoroscopy time and highly effective RFCA.

A simple framework to generate 3D patient-specific model of coronary artery bifurcation from single-plane angiographic images.

Although computer-based simulations, such as structural finite element analysis, have proven their usefulness to support procedural planning of coronary stenting, the link between the clinical practice and these engineering techniques is still limited to research test-cases. A key point to further promote such an interaction is to generate in a fast and effective manner the computational grids from the medical images. Hence, the present study proposes a simple framework to generate 3D meshes of coronary bifurcations from a pair of planar angiographic images obtained by X-ray angiography, which is the gold standard technique for the diagnosis of coronary artery stenosis.