Synopsis

Apparent diffusion coefficient (ADC) is known as a quantitative biomarker of prenatal brain maturation. Fast macromolecular proton fraction (MPF) mapping is an emerging method for quantitative assessment of myelination that was recently adapted to fetal MRI. This study compared spatiotemporal trajectories of MPF and ADC changes in the brain anatomic structures of 42 fetuses in utero. MPF and ADC demonstrated qualitatively similar but quantitatively different spatiotemporal patterns. MPF appeared more sensitive to changes in the brain structures with known prenatal onset of myelination.

INTRODUCTION

METHODS

Participants: The study population included 55 pregnant females referred to fetal MRI for clinical indications. Data from 42 fetuses (mean gestational age (GA)±standard deviation (SD): 27.7±6.0 weeks, range 20-38 weeks)) with normal brain MRI were included in subsequent analysis.

MRI Protocol: MRI acquisition was performed on a 1.5 Tesla Philips Achieva clinical scanner. An MPF mapping protocol was implemented as described previously^5,6 based on a 3D spoiled gradient-echo sequence with the following scans: magnetization-transfer-weighted (TR=32 ms, flip angle (FA)=8°); reference with the same parameters and without off-resonance saturation; T₁-weighted (TR=20 ms, FA=20°); and proton-density-weighted (TR=20 ms, FA=4°). All images were acquired with multi-shot echo-planar imaging (EPI) readout (EPI factor 9); TE=6.3 ms; voxel size 1.49×1.50×5.0 mm³ (interpolated to 0.78×0.78×2.50 mm³); and two signal averages.The block of MPF mapping sequences with the total duration about one minute was repeated from two to four times to mitigate motion problems. After exclusion of motion-corrupted datasets, images were averaged during post-processing as detailed earlier.⁵ For ADC mapping, a 2D single-shot diffusion-weighted EPI sequence was used with the following parameters: TR/TE = 2940/64 ms; three diffusion directions; b-values of 0, 125, 251, 376, and 501 s/mm²; in-plane resolution 2.01×2.36 mm² (interpolated to 1.21×1.21 mm²); twelve 5 mm slices; two signal averages; and scan time 79 s.

Image processing and analysis: MPF maps were reconstructed using the single-point algorithm.⁷ ADC maps were generated by the scanner’s software. Two operators measured ADC and MPF in the medulla, pons, cerebellum, thalamus, and frontal, occipital, and temporal cerebral white matter (WM). The scheme of the regions-of-interest placement is illustrated in Fig. 1.

Statistical analysis: Inter-observer agreement was assessed by the within-subject coefficient of variation (CV) and intraclass correlation coefficient (ICC) for each anatomic region. Mixed repeated-measures ANOVA was used to compare MPF and ADC between brain structures (within-subject factor) and pregnancy trimesters (between-subject factor). Pairwise differences were assessed by Tukey post-hoc test. Associations between ADC, MPF, and GA were tested using the Pearson correlation coefficient (r). Correlation coefficients were compared using Hotelling-Williams test. Significance was defined as P<0.05.

RESULTS

Inter-observer agreement in MPF and ADC measurements was good-to-excellent with ICC ranging between 0.71-0.97 and CV of 4-9%. ANOVA identified highly significant effects of the brain structure (F=74.2, P<0.0001 for ADC; F=216.0, P<0.0001 for MPF), pregnancy trimester (F=11.1, P=0.002 for ADC; F= 41.1, P<0.0001 for MPF) and their interaction (F=7.7, P<0.0001 for ADC; F= 42.0, P<0.0001).

Mean MPF and ADC across trimesters and structures are summarized in Fig. 2. From 2nd to 3rd trimester, MPF significantly increased in the medulla, pons, thalamus, and cerebellum. ADC significantly decreased in the thalamus and cerebellum. Both MPF and ADC showed an apparent pattern of divergence between brain structures in the 3rd trimester compared to the 2nd one (Fig. 2). Within this pattern, MPF demonstrated more pairwise distinctions, which appeared statistically significant (Fig. 2). ADC and MPF in 2nd trimester were significantly different between the two groups, one of which included brainstem structures (medulla and pons) with higher MPF and lower ADC and another contained the thalamus, cerebellum, and cerebral WM with lower MPF and higher ADC. Additionally, MPF in the thalamus was intermediate between the above groups, being significantly different from both. In the 3rd trimester, cerebral WM showed significantly lower MPF and higher ADC than any other structure. Notably, the difference in MPF between the medulla and pons became significant in the 3rd trimester with the largest value in the medulla.

MPF (r range 0.83-0.89, P<0.001) and ADC (r range -0.43--0.75, P≤0.004) significantly correlated with GA and each other (r range -0.32--0.60, P≤0.04) in the medulla, pons, thalamus, and cerebellum (Fig. 3). No significant correlations and distinctions between regions and trimesters were observed for cerebral WM. Correlations with GA were significantly stronger for MPF compared to ADC in the medulla, pons, and cerebellum (P<0.003). Structure-averaged MPF and ADC values strongly correlated (r=0.95, P<0.001) (Fig. 4).

CONCLUSIONS

Acknowledgements

References

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