Patient-Specific Quantitative In-Vivo Assessment of Human Mitral Valve Leaflet Strain Before and After MitraClip Repair.

PURPOSE: Mitral regurgitation (MR) is a highly prevalent and deadly cardiac disease characterized by improper mitral valve (MV) leaflet coaptation. Among the plethora of available treatment strategies, the MitraClip is an especially safe option, but optimizing its long-term efficacy remains an urgent challenge. METHODS: We applied our noninvasive image-based strain computation pipeline [1] to intraoperative transesophageal echocardiography datasets taken from ten patients undergoing MitraClip repair, spanning a range of MR etiologies and MitraClip configurations. We then analyzed MV leaflet strains before and after MitraClip implementation to develop a better understanding of (1) the pre-operative state of human regurgitant MV, and (2) the MitraClip's impact on the MV leaflet deformations. RESULTS: The MV pre-operative strain fields were highly variable, underscoring both the heterogeneity of the MR in the patient population and the need for patient-specific treatment approaches. Similarly, there were no consistent overall post-operative strain patterns, although the average A2 segment radial strain difference between pre- and post-operative states was consistently positive. In contrast, the post-operative strain fields were better correlated to their respective pre-operative strain fields than to the inter-patient post-operative strain fields. This quantitative result implies that the patient specific pre-operative state of the MV guides its post-operative deformation, which suggests that the post-operative state can be predicted using pre-operative data-derived modelling alone. CONCLUSIONS: The pre-operative MV leaflet strain patterns varied considerably across the range of MR disease states and after MitraClip repair. Despite large inter-patient heterogeneity, the post-operative deformation appears principally dictated by the pre-operative deformation state. This novel finding suggests that though the variation in MR functional state and MitraClip-induced deformation were substantial, the post-operative state can be predicted from the pre-operative data alone. This study suggests that, with use of larger patient cohort and corresponding long-term outcomes, quantitative predictive factors of MitraClip durability can be identified.

The Market Reacts Quickly: Changes in Paclitaxel Vascular Device Purchasing Within the Ascension Healthcare System.

BACKGROUND: A meta-analysis of trials in endovascular therapy suggested an increased mortality associated with treatment exposure to paclitaxel. Multiple publications and corrections of prior data were performed, and the United States Food and Drug Administration has issued multiple advisories regarding paclitaxel use. We analyzed how this controversy impacted device purchasing and related utilization patterns in the period immediately following publication of the meta-analysis. METHODS AND RESULTS: Ascension Healthcare System purchase data over a 14-month period were synthesized across centers for both paclitaxel and non-paclitaxel devices. A fixed-effects regression model and a binary regression model with facility-level controls were used to compare purchasing patterns before and after the meta-analysis. Purchase volumes of each paclitaxel device fell. Pooled purchase volumes of all paclitaxel devices decreased from a 14-month peak of 631 devices in October 2018 to a 14-month nadir of 359 devices in February 2019. An F-test comparing the pooled-month specific fixed effects for the months before vs after the publication of the meta-analysis has an F-statistic of 11.64, suggesting that average purchasing levels in the two periods are statistically different (P<.001). Utilization of non-paclitaxel devices did not decline. CONCLUSIONS: Purchase volumes of paclitaxel devices decreased immediately during the months following publication of the related meta-analysis. Total Ascension-wide paclitaxel device purchase volume in February 2019 demonstrated a 43.1% reduction from peak monthly purchase volume during the assessed period and a 32.5% reduction compared with November 2019, the last month preceding publication of the meta-analysis.