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Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging

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Abstract

Objectives

To evaluate the effects of signal intensity differences between the b0 image and diffusion tensor imaging (DTI) in the image registration process.

Methods

To correct signal intensity differences between the b0 image and DTI data, a simple image intensity compensation (SIMIC) method, which is a b0 image re-calculation process from DTI data, was applied before the image registration. The re-calculated b0 image (b0ext) from each diffusion direction was registered to the b0 image acquired through the MR scanning (b0nd) with two types of cost functions and their transformation matrices were acquired. These transformation matrices were then used to register the DTI data. For quantifications, the dice similarity coefficient (DSC) values, diffusion scalar matrix, and quantified fibre numbers and lengths were calculated.

Results

The combined SIMIC method with two cost functions showed the highest DSC value (0.802 ± 0.007). Regarding diffusion scalar values and numbers and lengths of fibres from the corpus callosum, superior longitudinal fasciculus, and cortico-spinal tract, only using normalised cross correlation (NCC) showed a specific tendency toward lower values in the brain regions.

Conclusion

Image-based distortion correction with SIMIC for DTI data would help in image analysis by accounting for signal intensity differences as one additional option for DTI analysis.

Key points

• We evaluated the effects of signal intensity differences at DTI registration.

• The non-diffusion-weighted image re-calculation process from DTI data was applied.

• SIMIC can minimise the signal intensity differences at DTI registration.

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Abbreviations

CC:

Corpus callosum

CST:

Cortico-spinal tract

DSC:

Dice similarity coefficient

DTI:

Diffusion tensor imaging

EPI:

Echo planar imaging

FA:

Fractional anisotropy

FACT:

Fibre assignment with the continuous tracking

NMI:

Normalised mutual information

NCC:

Normalised cross correlation

RA:

Relative anisotropy

RD:

Radial diffusivity

ROI:

Region of interest

SIMIC:

Simple image intensity compensation

SLF:

Superior longitudinal fasciculus

SSIM:

Structural similarity

VR:

Volume ratio

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Funding

This study was supported by grants of Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education [NRF (www.nrf.re.kr): NRF- 2017R1A6A3A03012461 and NRF-2015R1C1A1A02036526] and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute [KHIDI (www.khidi.or.kr): HI14C1090], funded by the Ministry of Health & Welfare, Republic of Korea. This study was also supported by the 2017 University of Sydney Postdoctoral Fellowship Scheme (192237).

Author information

Author notes

  1. Dong-Hoon Lee and Do-Wan Lee contributed equally to this work.

Authors and Affiliations

  1. Faculty of Health Sciences and Brain & Mind Centre, The University of Sydney, Sydney, New South Wales, Australia

    Dong-Hoon Lee & David Henry

  2. Center for Bioimaging of New Drug Development, and MR Core Lab., Asan Institute for Life Sciences, Asan Medical Center, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 138-736, Republic of Korea

    Do-Wan Lee & Dong-Cheol Woo

  3. Department of Radiation Oncology, Ajou University School of Medicine, Suwon, Gyeonggi, Republic of Korea

    Hae-Jin Park

  4. Department of Radiological Science, College of Health Science, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon, 220-710, Republic of Korea

    Bong-Soo Han

  5. Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

    Dong-Cheol Woo

Authors
  1. Dong-Hoon Lee
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  2. Do-Wan Lee
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Corresponding authors

Correspondence to Bong-Soo Han or Dong-Cheol Woo.

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Guarantor

The scientific guarantor of this publication is Dr. Dong-Hoon Lee.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• experimental

• performed at one institution

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Lee, DH., Lee, DW., Henry, D. et al. Minimisation of Signal Intensity Differences in Distortion Correction Approaches of Brain Magnetic Resonance Diffusion Tensor Imaging. Eur Radiol 28, 4314–4323 (2018). https://doi.org/10.1007/s00330-018-5382-6

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  • DOI: https://doi.org/10.1007/s00330-018-5382-6

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