左心室喷射分数报告变量和人工智能辅助可重现性:一个多中心分析
Yinghui Le1, Jiali Zhou1, Shuna Yang1
1Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.
The Canadian journal of cardiology
|February 12, 2026
概括
人工智能 (AI) 显著提高了心脏MRI中左心室喷射率 (LVEF) 评估的效率和可重复性. 虽然存在个体变异,但人工智能是简化CMR量化的一个有价值的工具.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 在临床实践中越来越多地用于左心室喷射率 (LVEF) 评估.
- 人工智能辅助的LVEF评估的现实世界,多中心验证至关重要.
研究的目的:
- 评估人工智能辅助LVEF评估的可靠性和可重复性.
- 在多元化的多中心环境中,将人工智能辅助的LVEF评估与手动方法进行比较.
主要方法:
- 354个心脏MRI (CMR) 检查的回顾性多中心研究.
- 使用QMass 8.1.1.使用人工智能衍生的LVEF (R-LVEF) 与手动重新评估 (M-LVEF) 的比较.
- 手动和人工智能辅助模式的观察者间和观察者内部可重现性分析.
主要成果:
- 在R-LVEF和M-LVEF之间具有良好的至优良的一致性 (ICC≥0.86),一致性极限超过±5%.
- 人工智能辅助评估显著减少了LVEF计算时间.
- 与手动分析相比,使用人工智能辅助方法的可复制性优越 (观察者之间更高的ICC,观察者内部更高的可复制性).
结论:
- 人工智能辅助的LVEF评估在效率和可重复性方面显示出显著的优势.
- 尽管存在个体差异,但人工智能是促进CMR量化的一个有价值的工具.
- 人工智能增强了心脏MRI用于LVEF确定的临床实用性.
相关概念视频
Variability: Analysis
528
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
528
Intelligence
8.8K
The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
8.8K
Random Variables
17.9K
A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
17.9K
Measures of Intelligence
8.6K
Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
8.6K
Graphs of Equations in Two Variables
273
An equation with two variables, typically written in the form y = f(x) or Ax + By = C, describes a relationship between quantities represented by x and y. Each solution to such an equation is an ordered pair (x, y) that satisfies the equation when substituted. These pairs can be represented graphically to understand the variables' relationship visually.A common technique for constructing the graph of a two-variable equation is to create a value table. Begin by choosing several values for the...
273
Variables Affecting Phosphorescence and Fluorescence
1.5K
Fluorescence and phosphorescence are essential phenomena in fields like analytical chemistry, biological imaging, and materials science, where they detect molecular properties and visualize cellular structures. Understanding the variables that influence these luminescent behaviors is crucial for maximizing accuracy and efficiency in their applications. These variables can broadly be grouped into chemical structure, solvent properties, and external conditions, each playing a distinct role in...
1.5K


