Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?

被引:18
作者
Cau, Riccardo [1 ]
Pisu, Francesco [1 ]
Suri, Jasjit S. [2 ]
Mannelli, Lorenzo [3 ]
Scaglione, Mariano [4 ]
Masala, Salvatore [4 ]
Saba, Luca [1 ]
机构
[1] Univ Hosp Cagliari, Dept Radiol, I-09042 Monserrato, Italy
[2] AtheroPoint, Stroke Monitoring & Diagnost Div, Roseville, CA 95661 USA
[3] IRCCS SYNLAB SDN SpA, I-80143 Naples, Italy
[4] Univ Hosp Sassari, Dept Radiol, I-07100 Sassari, Italy
关键词
cardiovascular imaging; non-contrast images; AI; CMR; LATE GADOLINIUM ENHANCEMENT; CHRONIC MYOCARDIAL-INFARCTION; TEXTURE ANALYSIS; PROGNOSTIC VALUE; PREDICTION MODELS; CARDIOMYOPATHY; DIAGNOSIS; OUTCOMES; DISEASE; MRI;
D O I
10.3390/diagnostics13122061
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development.
引用
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页数:17
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