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Aims: Our aim was to validate patient-specific software integrating baseline anatomy and biomechanical properties of both the aortic root and valve for the prediction of valve morphology and aortic leaflet calcium displacement after TAVI.Methods and results: Finite element computer modelling was performed in 39 patients treated with a Medtronic CoreValve System (MCS; n=33) or an Edwards SAPIEN XT (ESV; n=6). Quantitative axial frame morphology at inflow (MCS, ESV) and nadir, coaptation and commissures (MCS) was compared between multislice computed tomography (MSCT) post TAVI and a computer model as well as displacement of the aortic leaflet calcifications, quantified by the distance between the coronary ostium and the closest calcium nodule. Bland-Altman analysis revealed a strong correlation between the observed (MSCT) and predicted frame dimensions, although small differences were detected for, e.g., Dmin at the inflow (mean±SD MSCT vs. model: 21.6±2.4 mm vs. 22.0±2.4 mm; difference±SD: -0.4±1.3 mm, p<0.05) and Dmax (25.6±2.7 mm vs. 26.2±2.7 mm; difference±SD: -0.6±1.0 mm, p<0.01). The observed and predicted calcium displacements were highly correlated for the left and right coronary ostia (R 2 =0.67 and R 2 =0.71, respectively p<0.001).Conclusions: Dedicated software allows accurate prediction of frame morphology and calcium displacement after valve implantation, which may help to improve outcome. KEYWORDS• aortic stenosis • computer modelling • transcatheter aortic valve implantation (TAVI)

a b s t r a c t a r t i c l e i n f oBackground: Transcatheter Aortic Valve Implantation (TAVI) is now considered an indispensable treatment strategy in high operative risk patients with severe, symptomatic aortic stenosis. However, conduction disturbances and the need for Permanent Pacemaker (PPM) implantation after TAVI with the CoreValve prosthesis still remain frequent. Methods and results: We aimed to evaluate the implantation depth, the incidence and predictors of new conduction disturbances, and the need for PPM implantation within the first month after TAVI, using the new Accutrak CoreValve delivery system (ACV), compared to the previous generation CoreValve (non-ACV). In 5 experienced TAVI-centers, a total of 120 consecutive non-ACV and 112 consecutive ACV patients were included (n = 232). The mean depth of valve implantation (DVI) was 8.4 ± 4.0 mm in the non-ACV group and 7.1 ± 4.0 mm in the ACV group (p = 0.034). The combined incidence of new PPM implantation and new LBBB was 71.2% in the non-ACV group compared to 50.5% in the ACV group (p = 0.014). DVI (p = 0.002), first degree AV block (p = 0.018) and RBBB (p b 0.001) were independent predictors of PPM implantation. DVI (p b 0.001) and pre-existing first degree AV-block (p = 0.021) were identified as significant predictors of new LBBB. Conclusion: DVI is an independent predictor of TAVI-related conduction disturbances and can be reduced by using the newer CoreValve Accutrak delivery system, resulting in a significantly lower incidence of new LBBB and new PPM implantation.

Aims The aim of this study was to determine if computed tomography (CT) psoas muscular attenuation measurements may predict all-cause mortality in patients undergoing TAVI.Methods Ninety-four consecutive patients undergoing TAVI were analysed. The CT axial slice at the level of the fourth lumbar vertebra was selected. The psoas muscle areas were manually contoured. The circumferential surface area (CSA) of both psoas muscles was determined by selecting the voxels with attenuation values, ranging from 0 to 100 Hounsfield Units (HU). The mean CT attenuation coefficient of the psoas muscle (Psoas mean HU) was measured. The muscle was subdivided into a low-density muscle (LDM) (0-29 HU) and high-density muscle (HDM) (30-100 HU) portion. The HDM/LDM ratio was calculated. We searched for a correlation between HDM/LDM, CSA LDM (%), Psoas mean HU and all-cause mortality. ResultsThe mean age was 81.2 W 7.5 years. Thirty patients had adverse outcome (all-cause mortality). Compared with patients with the lowest CSA LDM (%), patients in the third and second tertiles had an increased hazard ratio for mortality (2.871; 95% confidence interval 0.880-9.371 and 5.044; 95% confidence interval 1. 641-15.795, respectively) in a multivariable model with EuroSCORE II, Barthel frailty index and CSA LDM (%) (P U 0.231, 0.097 and 0.019, respectively). HDM/LDM and Psoas mean HU (as continuous variable) were also independent predictors of all-cause mortality (P U 0.019, P U 0.013, respectively) Conclusion CSA LDM (%), Psoas mean HU and HDM/LDM are independent and incremental predictors of all-cause mortality in patients undergoing TAVI.

Elevated RDW is a significant predictor for adverse events and increased 1-year mortality after TAVI. Adding RDW to the classical STS score could be a valuable strategy to improve preoperative risk assessment in potential TAVI candidates.