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Article Synopsis
  • Traditional Diffusion Tensor Imaging (DTI) approaches struggle with issues like crossing fibers and lesions, which limit the accuracy of tractography results.
  • A new tractometry pipeline introduces multi-tensor fixel-based metrics, utilizing a robust method called Multi-Resolution Discrete Search (MRDS) to improve sensitivity and noise resistance.
  • Evaluation results show that this method excels in detecting white matter anomalies in patients with conditions like multiple sclerosis, outperforming traditional single-tensor methods.
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Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely , that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography.

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This special issue of Magnetic Resonance in Medical Sciences is dedicated to "Advanced Techniques for MR Neuroimaging," featuring nine review articles authored by leading experts. The reviews cover advancements in reproducible research practices, diffusion tensor imaging along the perivascular space, myelin imaging using magnetic susceptibility source separation, spinal cord quantitative MRI analysis, tractometry of visual white matter pathways, deep learning-based image enhancement, arterial spin labeling, the potential of radiomics, and MRI-based quantification of brain oxygen metabolism. These articles provide a comprehensive update on cutting-edge technologies and their applications in clinical and research settings, highlighting their impact on improving diagnostic accuracy and understanding of neurological disorders.

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