Keywords
MRI
AI
Compressed Sense
How to Cite
Abstract
The implementation of Artificial Intelligence (AI) in Magnetic Resonance Imaging (MRI) represents a significant innovation in the healthcare sector, with potential benefits in terms of both efficiency and diagnostic quality. This study analyzed a Health Technology Assessment (HTA) model to evaluate the impact of AI on 1.5 T and 3 T MRI scanners, focusing on the reduction of examination acquisition times. The results show a cost-benefit ratio that justifies the investment due to a quick economic return and an increase in departmental productivity. The rise in MRI exams performed contributes to the objectives of Radiology units and hospital management to reduce waiting lists. Furthermore, AI enhances image quality, reducing artifacts and noise, providing superior diagnostic support, and allowing for a broader patient base, as faster exams are better tolerated by less compliant patients. Our model thus highlights the numerous advantages of adopting AI in MRI, emphasizing its relevance to the regional and national healthcare system, and its ability to meet the objectives of the Italian National Plan 2024-2026 for improving healthcare services.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2024 by the authors. This article is an open access article distributed by JAHC.
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