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Aims: Standard manual analysis of IVUS to study the impact of anti-atherosclerotic therapies on the coronary vessel wall is done by a core laboratory (CL), the ground truth (GT). Automatic segmentation of IVUS with a machine learning (ML) algorithm has the potential to replace manual readings with an unbiased and reproducible method. The aim is to determine if results from a CL can be replicated with ML methods., Methods: This is a post-hoc, comparative analysis of the IBIS-4 (Integrated Biomarkers and Imaging Study-4) study (NCT00962416). The GT baseline and 13-month follow-up measurements of lumen and vessel area and percent atheroma volume (PAV) after statin induction were repeated by the ML algorithm., Results: The primary endpoint was change in PAV. PAV as measured by GT was 43.95 % at baseline and 43.02 % at follow-up with a change of -0.90 % (p = 0.007) while the ML algorithm measured 43.69 % and 42.41 % for baseline and follow-up, respectively, with a change of -1.28 % (p < 0.001). Along the most diseased 10 mm segments, GT-PAV was 52.31 % at baseline and 49.42 % at follow-up, with a change of -2.94 % (p < 0.001). The same segments measured by the ML algorithm resulted in PAV of 51.55 % at baseline and 47.81 % at follow-up with a change of -3.74 % (p < 0.001)., Conclusions: PAV, the most used endpoint in clinical trials, analyzed by the CL is closely replicated by the ML algorithm. ML automatic segmentation of lumen, vessel and plaque effectively reproduces GT and may be used in future clinical trials as the standard., Competing Interests: Declaration of competing interest Héctor M. García-García reports the following Institutional grant support: Biotronik, Boston Scientific, Medtronic, Abbott, Neovasc, Shockwave, Phillips and Corflow; Speaker's fee from Boston Scientific and Amgen. Lorenz Räber reports institutional grant support: Abbott, Biotronik, Boston Scientific, Sanofi, Regeneron, Infraredx and consultation fees by Abbott, Amgen, AstraZeneca, Occlutec, Medtronic, Sanofi, Vifor. Marco Roffi reports institutional research grants from Terumo, Biotronik, Medtronic and Cordis/Cardinal Health., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Previous studies have analyzed the efficacy of near-infrared spectroscopy-derived lipid core burden index (LCBI) in quantifying and identifying high-risk plaques and patients at increased risk of future major adverse cardiac outcomes/major adverse cardiovascular and cerebrovascular events. A maxLCBI 4mm of 400 or greater seems to be an effective threshold for classifying at-risk plaques. This meta-analysis provides a more precise odds ratio with a narrow standard deviation that can be used to guide future studies., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The purpose of this paper is to propose and qualify a novel funding mechanism for international neurosurgical nonprofits. The article first identifies and explains neurosurgeons' means for practicing in the developing world through a literature review. After this examination of the current funding methods for surgical care in low-income regions, the work transitions to an explanation of the applications and limitations of a new resource: the internal wealth of a developing country. This wealth may be leveraged by way of a for-profit hospital to create sustainable and domestic funding for nonprofit neurosurgical training. The applicability of the proposed mechanism extends beyond the field of neurosurgery to nonprofits in any health-related discipline. Factors influencing the viability of this mechanism (including local disease burden, economic trajectory, and political stability) are examined to create a baseline set of conditions for success., (Copyright © 2016 Elsevier Inc. All rights reserved.)