冠動脈音響マップにおける病変のコード化と局在化：科学的根拠、試験デザイン、および人工知能アルゴリズムプロトコル

In coronary artery disease (CAD), the initiation, progression, and regression of atherosclerosis remain incompletely understood, limiting the effectiveness of specific diagnostic and personalized medicine management strategies based on current imaging and assessment methods. In this scientific rationale and study design analysis, the framework conceptualizes the cardiovascular system as an integrated hydraulic network of pumps and pipes, advancing a shift from static imaging of luminal stenosis toward dynamic assessment of coronary flow. Grounded in fluid mechanics and acoustic principles, this analysis establishes a scientific rationale for an angiographic investigation of hemodynamic disturbances that compromise endothelial integrity in coronary arteries. The first section examines injury arising from repetitive flexion and extension of coronary segments driven by left ventricular contraction, most prominent at the transition from diastole to systole. The second section evaluates the hypothetical effects of thickened boundary layers and intimal injury caused by oxygen deprivation along the proximal portion of the outer curvature of side branches. The third section explores the hypothetical role of recirculating flow in accelerating lesion development at these sites. The fourth section presents an acoustic-based diagnostic framework for assessing the hypothetical impact of retrograde pressure-wave propagation associated with water-hammer phenomena. Collectively, these mechanisms establish the systematic codification and spatial delineation of coronary lesions as represented on the coronary acoustic map. Building on these insights, the present analysis proposes a clinical trial framework integrating AI-driven algorithmic protocols to rigorously assess the diagnostic performance and predictive accuracy of the coronary acoustic map.