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• Mineralized tissue MRI techniques are promising for bone morphology and fracture detection but remain less accurate than computed tomography for subtle bone details. • Although mineralized tissue MR images resemble CT images, they are subjected to various types of artifacts and should not be interpreted like conventional CT images. • T1-weighted three-dimensional gradient echo sequences appear as robust and widely available solutions for mineralized tissue MRI providing high-quality images with a good signal-to-noise ratio. • Although they convey limited signal-to-noise ratio, ultra-short and zero echo time MRI sequences are the best ones for detecting calcification within tendons and ligaments. • Artificial intelligence-generated synthetic CT offers high-quality images with great potential, but comparison with the other mineralized tissue MRI techniques are needed. Magnetic resonance imaging (MRI) techniques that enhance the visualization of mineralized tissues (hereafter referred to as MT-MRI) are increasingly being incorporated into clinical practice, particularly in musculoskeletal imaging. These techniques aim to mimic the contrast provided by computed tomography (CT), while taking advantage of MRI's superior soft tissue contrast and lack of ionizing radiation. However, the variety of MT-MRI techniques, including three-dimensional gradient-echo, ultra-short and zero-echo time, susceptibility-weighted imaging, and artificial intelligence-generated synthetic CT, each offer different technical characteristics, advantages, and limitations. Understanding these differences is critical to optimizing clinical application. This review provides a comprehensive overview of the most commonly used MT-MRI techniques, categorizing them based on their technical principles and clinical utility. The advantages and disadvantages of each approach, including their performance in bone morphology assessment, fracture detection, arthropathy-related findings, and soft tissue calcification evaluation are discussed. Additionally, technical limitations and artifacts that may affect image quality and diagnostic accuracy, such as susceptibility effects, signal-to-noise ratio issues, and motion artifacts are addressed. Despite promising developments, MT-MRI remains inferior to conventional CT for evaluating subtle bone abnormalities and soft tissue calcification due to spatial resolution limitations. However, advances in deep learning and hardware innovations, such as artificial intelligence-generated synthetic CT and ultrahigh-field MRI, may bridge this gap in the future.
Teixeira et al. (Thu,) studied this question.