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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Phys. | doi: 10.3389/fphy.2019.00160

Apparent diffusion coefficient assessment of brain development in normal fetuses and ventriculomegaly

  • 1Centro Fermi - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Italy
  • 2Histology and Medical Embryology Unit, Department of Anatomical, Histological, Medical-legal and Locomotor Sciences, Sapienza University of Rome, Italy
  • 3Department of Radiological Sciences, Oncology and Anatomo Pathology, Faculty of Medicine and Dentistry, Sapienza University of Rome, Italy
  • 4Institute of Complex Systems, Italian National Research Council (CNR), Italy
  • 5Department of Anatomical, Histological, Medico-legal and Locomotor Sciences, Faculty of Pharmacy and Medicine, Sapienza University of Rome, Italy

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The
ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19-38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values=50,200,700s/mm^2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with
a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC
between normal and VM cases and between second and third trimester in different brain regions.
Correlation between ADC and GA was assessed with linear and quadratic regression analysis.
Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC
measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains
(p<0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p<0.02). ADC values in centrum semiovale, thalamus, cerebellum and
pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA
was found in basal ganglia and occipital white matter of normal brains and in frontal white matter
of VM (p<0.02). ADC values in all fetal brain regions were lower than those reported in literature
where DWI with b=0 was performed. Conversely, they were in agreement with the results of other
authors who measured perfusion and diffusion contributions separately.
By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable
scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities
associated with VM.

Keywords: Fetal MRI, Brain Development, DWI (diffusion weighted imaging), ADC (apparent diffusion coefficient), Ventriculomegaly

Received: 30 Apr 2019; Accepted: 30 Sep 2019.

Copyright: © 2019 Di Trani, Manganaro, Antonelli, Guerreri, De Feo, Catalano and Capuani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Miss. Maria Giovanna Di Trani, Centro Fermi - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, 00184, Lazio, Italy, mgiovanna.ditrani@gmail.com