Anatomical and Technical Predictors of Three-dimensional Mitral Valve Area Reduction after Transcatheter Edge-to-Edge Repair.

BACKGROUND: Among current transcatheter therapies for the treatment of mitral regurgitation, the MitraClipTM (MC, Abbott Vascular, Illinois, USA) system is the most commonly used. MC implantation is usually contraindicated in patients with a mitral valve area (MVA) < 4.0cm2 . However, little is known about the real impact of MC implantation on MVA. Our goal was to investigate the factors influencing MVA reduction and derive the minimal MVA required to prevent the development of a clinically significant mitral stenosis (MVA < 1.5cm2 ) in different clinical scenarios.

METHODS: Using 3D datasets, the annulus and leaflet anatomy, and MVA before clip implantation (MVABC ) were assessed. After each MC implant (NTR or XTR), the relative MVA reduction and the absolute residual MVA were measured and their predictors evaluated.

RESULTS: The present analysis included 116 patients. A MC XTR was the first device implanted in 50% of the subjects, and 53% were treated with a single implant. MVA reduction following one XTR was 57±7% vs. 52±8% after one NTR (p=0.001). A lower MVA reduction was observed when the MC was placed commissural/central versus paracentral (50±8 vs. 57±7%, p<0.0001). After a second device, the additional MVA reduction was higher when creating a triple- than a double-orifice morphology (34±11 vs. 25±9%, p=0.001). MVA after one MC correlated with MVABC , as well as with the clip type and position (r=0.91, p<0.0001). MVABC , orifice morphology, and first device position predicted MVA after two implants (r=0.82, p<0.0001). Based on the mathematical relationship between these parameters, the minimal MVABC needed in eight different clinical scenarios was summarized in a decision algorithm: the values ranged from 3.5 to 4.7cm2 for one and 4.5 to 6.3cm2 for two MC strategies.

CONCLUSION: The minimal native MVA preventing clinically relevant MS after transcatheter edge-to-edge repair is predicted by the number and location of clip(s), orifice morphology, and device type. Based on these parameters an algorithm has been derived to optimize patient selection and pre-procedural planning.