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

Author:

Cau Riccardo1ORCID,Pisu Francesco1ORCID,Suri Jasjit S.2,Mannelli Lorenzo3ORCID,Scaglione Mariano4,Masala Salvatore4,Saba Luca1ORCID

Affiliation:

1. Department of Radiology, University Hospital of Cagliari, 09042 Monserrato, Italy

2. Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USA

3. IRCCS SYNLAB SDN S.p.A., 80143 Naples, Italy

4. Department of Radiology, University Hospital of Sassari, 07100 Sassari, Italy

Abstract

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.

Publisher

MDPI AG

Subject

Clinical Biochemistry

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