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From images to insights: a neuroradiologist’s practical guide on white matter fiber tract anatomy and DTI patterns for pre-surgical planning

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Abstract

Introduction

Diffusion tensor imaging (DTI) is a valuable non-invasive imaging modality for mapping white matter tracts and assessing microstructural integrity, and can be used as a “biomarker” in diagnosis, differentiation, and therapeutic monitoring. Although it has gained clinical importance as a marker of neuropathology, limitations in its interpretation underscore the need for caution.

Methods

This review provides an overview of the principles and clinical applicability of DTI. We focus on major white matter fiber bundles, detailing their normal anatomy and pathological DTI patterns, with emphasis on tracts routinely requested in our neurosurgical department in the preoperative context (uncinate fasciculus, arcuate fasciculus, pyramidal pathway, optic radiation, and dentatorubrothalamic tract).

Results

We guide neuroradiologists and neurosurgeons in defining volumes of interest for mapping individual tracts and demonstrating their 3D reconstructions. The intricate trajectories of white matter tracts pose a challenge for accurate fiber orientation recording, with each bundle exhibiting specific characteristics. Tracts adjacent to brain lesions are categorized as displaced, edematous, infiltrated, or disrupted, illustrated with clinical cases of brain neoplasms. To improve structured reporting, we propose a checklist of topics for inclusion in imaging evaluations and MRI reports.

Conclusion

DTI is emerging as a powerful tool for assessing microstructural changes in brain disorders, despite some challenges in standardization and interpretation. This review serves an educational purpose by providing guidance for fiber monitoring and interpretation of pathological patterns observed in clinical cases, highlighting the importance and potential pitfalls of DTI in neuroradiology and surgical planning.

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Abbreviations

ADC:

Apparent Diffusion Coefficient

dMRI:

Diffusion Magnetic Resonance Imaging

DTI:

Diffusion Tensor Imaging

DWI:

Diffusion-Weighted Imaging

FA:

Fractional Anisotropy

IDH:

Isocitrate Dehydrogenase

MD:

Mean Diffusivity

MRI:

Magnetic Resonance Imaging

ROI/VOI:

Region/Volume-Of-Interest

WM:

White Matter

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Funding

Funding information is not applicable / No funding was received.

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Authors and Affiliations

  1. Department of Neuroradiology – Centro Hospitalar Universitário de Lisboa Central (CHULC), Rua José António Serrano, 1150-199, Lisbon, Portugal

    Inês S. Freire

  2. NOVA Medical School, Universidade Nova de Lisboa, Lisbon, Portugal

    Inês S. Freire

  3. Institute of Nuclear Sciences Applied to Health (ICNAS), Coimbra, Portugal

    Tânia S. Lopes, Sónia G. Afonso & Daniela J. Pereira

  4. Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Coimbra, Portugal

    Tânia S. Lopes, Sónia G. Afonso & Daniela J. Pereira

  5. Functional Unit of Neuroradiology – Centro Hospitalar e Universitário de Coimbra (CHUC), Coimbra, Portugal

    Daniela J. Pereira

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  1. Inês S. Freire
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  2. Tânia S. Lopes
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  3. Sónia G. Afonso
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  4. Daniela J. Pereira
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Contributions

IF and DJP conceptualize the article. IF performed the literature search. IF and DJP performed the data analysis. IF wrote the first draft. All authors critically revised the manuscript.

Corresponding author

Correspondence to Inês S. Freire.

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We declare that we have no conflict of interest.

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Nothing to declare.

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In line with the above, the study was exempt from ethical approval.

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This report does not contain any personal information that could lead to the identification of the patient(s). In addition, this is an observational study, so the patients’ informed consent was waived. All the images used are anonymized and do not allow the individuals to be identified.

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Freire, I.S., Lopes, T.S., Afonso, S.G. et al. From images to insights: a neuroradiologist’s practical guide on white matter fiber tract anatomy and DTI patterns for pre-surgical planning. Neuroradiology (2024). https://doi.org/10.1007/s00234-024-03362-7

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