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4D iterative reconstruction of brain fMRI in the moving fetus

Athena Taymourtash, Hamza Kebiri, Sébastien Tourbier, Ernst Schwartz, Karl-Heinz Nenning, Roxane Licandro, Daniel Sobotka, Hélène Lajous, Priscille de Dumast, Meritxell Bach Cuadra, Georg Langs

TL;DR

A novel technique based on four dimensional iterative reconstruction of the scattered slices acquired during fetal fMRI is proposed, which indicates improvements of reconstruction quality compared to the conventional 3D interpolation approach.

Abstract

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses has limited clinical application since it causes substantial signal fluctuations which can systematically alter observed patterns of functional connectivity. Previous studies have focused on the accurate estimation of the motion parameters in case of large fetal head movement and used a 3D single step interpolation approach at each timepoint to recover motion-free fMRI images. This does not guarantee that the reconstructed image corresponds to the minimum error representation of fMRI time series given the acquired data. Here, we propose a novel technique based on four dimensional iterative reconstruction of the scattered slices acquired during fetal fMRI. The accuracy of the proposed method was quantitatively evaluated on a group of real clinical fMRI fetuses. The results indicate improvements of reconstruction quality compared to the conventional 3D interpolation approach.

4D iterative reconstruction of brain fMRI in the moving fetus

TL;DR

A novel technique based on four dimensional iterative reconstruction of the scattered slices acquired during fetal fMRI is proposed, which indicates improvements of reconstruction quality compared to the conventional 3D interpolation approach.

Abstract

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses has limited clinical application since it causes substantial signal fluctuations which can systematically alter observed patterns of functional connectivity. Previous studies have focused on the accurate estimation of the motion parameters in case of large fetal head movement and used a 3D single step interpolation approach at each timepoint to recover motion-free fMRI images. This does not guarantee that the reconstructed image corresponds to the minimum error representation of fMRI time series given the acquired data. Here, we propose a novel technique based on four dimensional iterative reconstruction of the scattered slices acquired during fetal fMRI. The accuracy of the proposed method was quantitatively evaluated on a group of real clinical fMRI fetuses. The results indicate improvements of reconstruction quality compared to the conventional 3D interpolation approach.
Paper Structure (7 sections, 4 equations, 3 figures, 1 table)

This paper contains 7 sections, 4 equations, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Method
  3. Implementation details
  4. Experimental Results
  5. Reconstruction accuracy
  6. Conclusion
  7. Acknowledgment

Figures (3)

  • Figure 1: Example of slice-wise head motion parameters estimated for one fetus with strong rotational motion using a symmetric block matching registration algorithm based on the normalized cross correlation including three rotations in degrees and three translations in millimeters.
  • Figure 2: Examples in the average volume (top row) and voxelwise standard deviation of the signal (bottom row) for two fetal subjects of S14 and S8 whit strong rotational parameters. The columns correspond to the original data, single step 3D linear interpolation, and the proposed 4D iterative reconstruction based on the maximum a-posteriori estimation minimizing a first order Tikhonov function.
  • Figure 3: boxplot analysis and statistics of the sharpness (left) and standard deviation of BOLD signal fluctuation (right) for 15 fetuses.