Nine pillars of quantitative and AI-driven brain and spinal cord MRI

Brain and spinal cord magnetic resonance imaging is shifting from qualitative anatomy to quantitative metrics. This review covers nine pillars including deep learning reconstruction, oxygen metabolism, glymphatic imaging, tractometry, myelin mapping, and radiomics.

• The nine pillars include spinal cord imaging frameworks, arterial spin labeling standardization, susceptibility-based myelin mapping, and open science for reproducibility.
• AI supports reconstruction, acceleration, segmentation, quality control, parameter extraction, and multiparametric pattern recognition for diagnosis.
• Quantitative outputs encompass image-quality metrics, metabolic/perfusion parameters, tract diffusion indices, susceptibility components, and radiomic features.

Automated summary

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