New programs for translating research to patient care: Lessons learned at the NIH Center for Accelerated Innovations at Cleveland Clinic.

The NIH Center for Accelerated Innovations at Cleveland Clinic (NCAI-CC) was funded by the National Heart Lung and Blood Institute (NHLBI) to support academic investigators in technology development and commercialization. NCAI-CC was one of three multi-institutional Centers established in the fall of 2013. The goal of each Center was to catalyze the growth of an ecosystem of commercialization within their affiliated institutions and regions by managing a program of funding and guiding translational project development and by delivering commercialization education programs to participating investigators.

Cyclic Variation of Spectral Parameters for the Differentiation of Atrial Myocardium Before and Immediately Following Radiofrequency Ablation.

Radiofrequency ablation (RFA) is a common treatment of atrial fibrillation. However, current treatment is associated with a greater than 20% recurrence rate, in part due to inadequate monitoring of tissue viability during ablation. Spectral parameters, in particular cyclic variation of integrated backscatter (CVIB), have shown promise as early indicators of myocardial recovery from ischemia.

The P387 thrombospondin-4 variant promotes accumulation of macrophages in atherosclerotic lesions.

Thrombospondin-4 (TSP4) is a pro-angiogenic protein that has been implicated in tissue remodeling and local vascular inflammation. TSP4 and, in particular, its SNP variant, P387 TSP4, have been associated with cardiovascular disease. Macrophages are central to initiation and resolution of inflammation and development of atherosclerotic lesions, but the effects of the P387 TSP4 on macrophages remain essentially unknown.

Artificial Intelligence in Intracoronary Imaging.

Purpose Of Review: This paper investigates present uses and future potential of artificial intelligence (AI) applied to intracoronary imaging technologies.

Recent Findings: Advances in data analytics and digitized medical imaging have enabled clinical application of AI to improve patient outcomes and reduce costs through better diagnosis and enhanced workflow. Applications of AI to IVUS and IVOCT have produced improvements in image segmentation, plaque analysis, and stent evaluation.

Spectral Analysis of Ultrasound Radiofrequency Backscatter for the Detection of Intercostal Blood Vessels.

Spectral analysis of ultrasound radiofrequency backscatter has the potential to identify intercostal blood vessels during ultrasound-guided placement of paravertebral nerve blocks and intercostal nerve blocks. Autoregressive models were used for spectral estimation, and bandwidth, autoregressive order and region-of-interest size were evaluated. Eight spectral parameters were calculated and used to create random forests.