Background <p>Cardiac magnetic resonance (CMR) imaging is a robust, non-invasive tool in cardiovascular diagnostics but remains underutilized due to the high costs and infrastructure demands associated with high-field (HF) MRI systems. Low-field (LF) MRI systems (&lt; 1.5&#xa0;T) offer a promising alternative, with advantages in cost, safety, and sustainability, but their economic viability and clinical applicability in CMR have not been comprehensively reviewed.</p> Purpose <p>This review aimed to evaluate the potential of LF CMR in reducing the financial, operational, and environmental burdens of cardiac imaging while supporting equitable access to care.</p> Methods <p>A narrative synthesis was conducted, analyzing published data on acquisition, installation, operational, and maintenance costs of LF versus HF MRI systems. Technical challenges and solutions related to image quality, scan duration, and clinical performance were also discussed. Emphasis was placed on energy efficiency, helium usage, and sustainability metrics in the context of healthcare carbon footprints.</p> Results <p>Low-field MRI systems demonstrate significant cost advantages, including up to 50% reduction in acquisition costs and 70% in installation expenses compared to HF systems. Technological advancements such as improved RF coils, AI-based denoising, and compressed sensing now enable diagnostic-quality CMR at low fields. Energy consumption is markedly reduced in LF systems, contributing to improved environmental sustainability. Furthermore, the adoption of LF systems may facilitate MRI accessibility in rural and resource-limited settings, potentially addressing global disparities in cardiovascular imaging.</p> Conclusion <p>LF CMR represents a viable and scalable solution to expand the reach of advanced cardiac imaging. By reducing financial and environmental barriers, LF CMR supports a more sustainable and equitable future for cardiovascular diagnostics.</p>

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Low-field cardiac magnetic resonance: advancing cost savings, sustainability, and health equity

  • Amirali Aali,
  • Niloufar Rahnavard,
  • Arcadia Trvalik,
  • Haile Kassahun,
  • Muhammad Umair

摘要

Background

Cardiac magnetic resonance (CMR) imaging is a robust, non-invasive tool in cardiovascular diagnostics but remains underutilized due to the high costs and infrastructure demands associated with high-field (HF) MRI systems. Low-field (LF) MRI systems (< 1.5 T) offer a promising alternative, with advantages in cost, safety, and sustainability, but their economic viability and clinical applicability in CMR have not been comprehensively reviewed.

Purpose

This review aimed to evaluate the potential of LF CMR in reducing the financial, operational, and environmental burdens of cardiac imaging while supporting equitable access to care.

Methods

A narrative synthesis was conducted, analyzing published data on acquisition, installation, operational, and maintenance costs of LF versus HF MRI systems. Technical challenges and solutions related to image quality, scan duration, and clinical performance were also discussed. Emphasis was placed on energy efficiency, helium usage, and sustainability metrics in the context of healthcare carbon footprints.

Results

Low-field MRI systems demonstrate significant cost advantages, including up to 50% reduction in acquisition costs and 70% in installation expenses compared to HF systems. Technological advancements such as improved RF coils, AI-based denoising, and compressed sensing now enable diagnostic-quality CMR at low fields. Energy consumption is markedly reduced in LF systems, contributing to improved environmental sustainability. Furthermore, the adoption of LF systems may facilitate MRI accessibility in rural and resource-limited settings, potentially addressing global disparities in cardiovascular imaging.

Conclusion

LF CMR represents a viable and scalable solution to expand the reach of advanced cardiac imaging. By reducing financial and environmental barriers, LF CMR supports a more sustainable and equitable future for cardiovascular diagnostics.