Investigation of anisotropic fishing line-based phantom as tool in quality control of diffusion tensor imaging

  • Edna Marina de SouzaEmail author
  • Eduardo Tavares Costa
  • Gabriela Castellano


This work proposes a low-cost, fishing line-based phantom for quality control of diffusion tensor imaging (DTI). The device was applied to investigate the relationship between DTI indexes (DTIi) and imaging acquisition parameters. A Dyneema® fishing line phantom was built with fiber bundles of different thicknesses. DTI acquisitions were performed in a 3T magnetic resonance imaging scanner using an 8-channel and a 32-channel head coil. For each coil, the following acquisition parameters were changed, one at a time: diffusion sensitivity factor (b value), echo time, sensitivity encoding, voxel size, number of signal averages, and number of diffusion gradient directions (NDGD). DTIi including fractional anisotropy, relative anisotropy (RA), linear anisotropy (CL), and planar anisotropy (CP) were calculated for each image; the data were analyzed using the coefficient of variation (CV) and distributions of DTIi values. The 32-channel head coil presented higher CV values for the DTIi RA, CL, and CP when voxel size was changed. Using the phantom, dependences between diffusion-related parameters (b value and NDGD) and DTIi were also observed; the majority of these were for the smaller thickness fiber bundles. The device proved to be useful for the verification of the DTI performance over time.


MRI DTI Phantom Quality control 



The authors would like to thank the staff at the Biomedical Engineering Center, School of Electrical and Computer Engineering (UNICAMP) for building the phantom, and the 3T MRI scanner of Clinics Hospital (UNICAMP) staff for assistance with scanner access.

Author contributions

Study conception and design: EMS, ETC, GC. Acquisition of data: EMS. Analysis and interpretation of data: EMS, GC. Drafting of manuscript: EMS, ETC, GC. Critical revision: ETC, GC. Approval of the final version: EMS, ETC, GC.


This work was supported by São Paulo Research Foundation (FAPESP, Brazil, Grant—2013/07559-3) through BRAINN (Brazilian Institute of Neuroscience and Neurotechnology), and by the National Council for Scientific and Technological Development (CNPQ, Brazil, Grant—310860/2014-8).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed.


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Copyright information

© Japanese Society of Radiological Technology and Japan Society of Medical Physics 2019

Authors and Affiliations

  1. 1.Biomedical Engineering CenterUniversity of Campinas (UNICAMP)CampinasBrazil
  2. 2.Biomedical Engineering Department, School of Electrical and Computer EngineeringUniversity of Campinas (UNICAMP)CampinasBrazil
  3. 3.Neurophysics Group, Gleb Wataghin Physics InstituteUniversity of Campinas (UNICAMP)CampinasBrazil
  4. 4.Brazilian Institute of Neuroscience and Neurotechnology (BRAINN)CampinasBrazil

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