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Diffusion Phantom Study of Fiber Crossings at Varied Angles Reconstructed with ODF-Fingerprinting

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Computational Diffusion MRI (CDMRI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14328))

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Abstract

White matter fiber reconstructions based on seeking local maxima of Orientation Distribution Functions (ODFs) typically fail to identify fibers crossing at narrow angles below \(45^\circ \). ODF-Fingerprinting (ODF-FP) replaces the ODF maxima localization mechanism with pattern matching, allowing the use of all information stored in ODFs. In this work, we study the ability of ODF-FP to reconstruct fibers crossing at varied angles spanning \(10^\circ \)–\(90^\circ \) in physical diffusion phantoms composed of textile tubes with 0.8 \(\upmu \)m diameter, approaching the anatomical scale of axons. Our results show that ODF-FP is able to correctly identify \(80\pm 8\%\) of the crossing fibers regardless of the crossing angle and provide the highest average reconstruction accuracy.

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Notes

  1. 1.

    We put “white matter” in quotation marks to emphasize that our synthetic fibers served as simplified models of WM tissue. Also note that the studied diffusion phantoms did not contain structures representing gray matter or corticospinal fluid, hence the omission of their respective contributions to the diffusion-weighted signal.

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Acknowledgements

This project was supported in part by the National Institutes of Health (NIH, R01 EB028774 and R01 NS082436) under the rubric of the Center for Advanced Imaging Innovation and Research (CAI2R, https://www.cai2r.net), a NIBIB Biomedical Technology Resource Center (NIH P41 EB017183).

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Authors and Affiliations

  1. Center for Advanced Imaging Innovation and Research (CAI²R), Department of Radiology, NYU Langone Health, New York, NY, USA

    Patryk Filipiak, Timothy M. Shepherd & Steven H. Baete

  2. Psychology Software Tools, Inc., Pittsburgh, PA, USA

    Lee Basler & Anthony Zuccolotto

  3. Department of Neurosurgery, Perlmutter Cancer Center, Neuroscience Institute, Kimmel Center for Stem Cell Biology, NYU Langone Health, New York, NY, USA

    Dimitris G. Placantonakis

  4. University of Pittsburgh, Pittsburgh, PA, USA

    Walter Schneider

  5. Radiological Sciences Laboratory and Molecular Imaging Program at Stanford, Department of Radiology, Stanford University, Stanford, CA, USA

    Fernando E. Boada

Authors
  1. Patryk Filipiak
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  2. Timothy M. Shepherd
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  3. Lee Basler
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  4. Anthony Zuccolotto
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  5. Dimitris G. Placantonakis
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  6. Walter Schneider
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  7. Fernando E. Boada
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  8. Steven H. Baete
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Corresponding author

Correspondence to Patryk Filipiak .

Editor information

Editors and Affiliations

  1. University of Illinois at Chicago, Chicago, IL, USA

    Muge Karaman

  2. Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia

    Remika Mito

  3. University College London, London, UK

    Elizabeth Powell

  4. Université de Sherbrooke, Sherbrooke, QC, Canada

    Francois Rheault

  5. Microsoft Research Cambridge, Milton, UK

    Stefan Winzeck

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Source Code Availability Statement

The Python code of ODF-FP implemented as an extension of the DIPY library is available at https://github.com/filipp02/dipy_odffp.

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Filipiak, P. et al. (2023). Diffusion Phantom Study of Fiber Crossings at Varied Angles Reconstructed with ODF-Fingerprinting. In: Karaman, M., Mito, R., Powell, E., Rheault, F., Winzeck, S. (eds) Computational Diffusion MRI. CDMRI 2023. Lecture Notes in Computer Science, vol 14328. Springer, Cham. https://doi.org/10.1007/978-3-031-47292-3_3

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  • DOI: https://doi.org/10.1007/978-3-031-47292-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47291-6

  • Online ISBN: 978-3-031-47292-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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