Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review.

JOURNAL OF THORACIC IMAGING(2018)

引用 61|浏览7
暂无评分
摘要
Coronary computed tomographic angiography (CCTA) has evolved as a rapid and highly sensitive method for the exclusion of obstructive coronary artery disease. Unfortunately, as it pertains to moderate and severe lesions, the ability to discriminate between those that are hemodynamically significant and those that are nonobstructive is lacking. Consequently, this deficiency can result in a significant number of unnecessary referrals for invasive angiography that yields nonobstructive results. Fractional flow reserve (FFR), which assesses the hemodynamic significance of a specific lesion, when performed during invasive angiography, results in improved patient outcomes compared with visual stenosis assessment alone. Through the application of computational analytic methods to CT-derived anatomic coronary models, noninvasive calculation of FFR has become possible. This allows for the improved ability to differentiate between nonobstructive coronary lesions and those that are truly hemodynamically significant. Currently, HeartFlow FFRCT is the only FDA-approved and commercially available CCTA-derived FFR (CT-FFR) platform. By reducing the number of invasive procedures performed for nonobstructive disease, CT-derived FFR has the ability to lower health care expenditures and become the true gatekeeper to invasive angiography.
更多
查看译文
关键词
fractional flow reserve,coronary computed tomographic angiography,invasive coronary angiography,computational fluid dynamics,artificial intelligence,machine learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要