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Brain volumetric measurements in children with ADHD:a comparative study between synthetic and conventional MRI
Yingqian Chen1, Shu Su1, Yan Dai1, Long Qian2, and Zhiyun Yang1
1First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, 2GE Healthcare, Beijing, China

Synopsis

The developmental mechanism underlying the brain development abnormalities in attention deficit hyperactivity disorder (ADHD) is still unclear. The currently developed synthetic MRI (SyMRI) offers a novel approach for brain segmentation and myelin volume estimation. Our study investigated the profiles of brain volumetric measurements in children with ADHD with both SyMRI and conventional T1 weighted(cT1w) MRI. And the results proved the global brain development retardation but normal whole brain myelination of children with ADHD. Besides, the high consistency of brain segmentation with cT1w image and SyMRI has also been proved, which indicate the clinical feasibility of SyMRI in children.

Introduction

Attention deficit hyperactivity disorder (ADHD) is the most common childhood-onset neurodevelopmental disorder that may continue through adolescence and adulthood.1 Many neurodevelopmental disorder diseases in childhood are associated with the development retardation of central nerve system, which manifests as the brain tissue volume change and myelination impairment.2 However, the developmental mechanism underlying these changes are still unclear. The currently developed synthetic MRI (SyMRI) offers a time-saving methods for brain segmentation and volume estimation. Moreover, the myelin volume can also be calculated by SyMRI .3 Our study aims to investigate the profiles of brain volumetric measurements in children with attention deficit hyperactivity disorder (ADHD), and the consistency of these brain volumetric measurements derived from the SyMRI and conventional T1 weighted MRI (cT1w MRI).

Methods

Brain SyMRI and cT1w images were prospectively collected for 38 pediatric patients with clinical diagnosis of ADHD and 38 age- and gender matched healthy children (HC) with age range of 6-13 years. Eight brain volumetric measurements, including gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF), non-WM/GM/CSF (NoN), Myelin (MYE), Myelin fraction (MYF), brain parenchyma volume (BPV) and intracranial volume (ICV) were automatically estimated from SyMRI data, and the four matching measurements (GMV, WMV, BPV, ICV) were extracted from cT1w images. The group differences of brain volumetric measurements derived from synthetic and cT1w MRI were performed respectively using analysis of covariance (ANCOVA) with age and gender as covariates. Person correlation analysis was applied to evaluate the association between synthetic and cT1w MRI derived measurements.

Results

As for the brain volumetric measurements extracted from SyMRI, significant decreased GMV (p<0.01), WMV (p<0.01), BPV (p < 0.05) and increased NON volume (p < 0.05) were found in ADHD group compared with HC; No group differences were found in ICV, CSF ( ADHD:177.3 mL±44.8 vs HC:157.7 mL ± 43.9, p > 0.05), myelin volume ( ADHD:140.3 mL±15.7 vs HC:143.1 mL±23.0, p > 0.05) and myelin fraction (ADHD:0.114±0.013 vs HC:0.110±0.013, p > 0.05). With regard to GMV, WMV, BPV and ICV estimated from cT1w images, the group differences between ADHD and HC were consistent with the results estimated from SyMRI. The GMV, WMV, BPV and ICV showed noticeable correlation between the two approaches (r values equal to 0.691、0.577、0.938、0.796 respectively, pīŧœ0.001).

Discussion

The reduction of GMV, WMV, BPV and BPF, increase of NON in children with ADHD were found in our study. Most of the findings are consistent with the previous studies that ADHD was thought to correlate with brain development retardation.1 The enlarged para-vessel spaces were observed in ADHD patients,4 which may partially contribute to the difference of NON. While the myelin volume, MYF and ICV did not found to have statistical significance between two group. Considered that most of the myelin is located in white matter, these results may indicate that the maldevelopment of glial cells, other than myelination, contribute to the alteration of white matter microstructure in the drug naïve children with ADHD. But more studies on the specific white matter composition change in ADHD patients are needed to prove the deduction. Among all the parameters can be measured by both methods, the measurements all showed to have good correlation between the T1-drive and SyMRI methods, especially the BPV and ICV. What’s more, both of the methods get the similar results when comparing the ADHD patient and healthy control. The SyMRI seems to have a comparative reliability both in the measurement and clinic. The reason that the volumetric output of gray matter and white matter with the two methods didn’t show the correlation as high as that in BPV and ICV may be cause by the different definitions of the brain component in these two software. Compared with the cT1W MRI, SyMRI can significantly reduce scan time of scanning as well as the postprocessing procedures and generate multiple image contrasts in a single MRI scan, which makes the assessment in clinic become a reality.5

Conclusion

Our study demonstrated the global brain development retardation but normal whole brain myelination in child with ADHD. And the results also proved the high consistency of brain segmentation with cT1w MRI and SyMRI in pediatric patients with ADHD and healthy children over 5 years old. The different definition of gray and white matter is the main reason accounting to the difference of measurements. The postprocessing of SyMRI is time-saving. And more measurements can be acquired with the use of SyMRI.

Acknowledgements

None.

References

1. Biederman J, Faraone SV. Attention-deficit hyperactivity disorder. Lancet 2005; 366(9481): 237-48.

2. Gui L, Loukas S, Lazeyras F, Huppi PS, Meskaldji DE, Borradori Tolsa C. Longitudinal study of neonatal brain tissue volumes in preterm infants and their ability to predict neurodevelopmental outcome. Neuroimage 2019; 185: 728-41.

3. Warntjes M, Engstrom M, Tisell A, Lundberg P. Modeling the Presence of Myelin and Edema in the Brain Based on Multi-Parametric Quantitative MRI. Front Neurol 2016; 7: 16.

4. Vilor-Tejedor N, Alemany S, Forns J, et al. Assessment of Susceptibility Risk Factors for ADHD in Imaging Genetic Studies. J Atten Disord 2019; 23(7): 671-81.

5. Warntjes JB, Leinhard OD, West J, Lundberg P. Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magn Reson Med 2008; 60(2): 320-9.

Figures

The comparison of the brain tissue and myelin volume between ADHD group and control group with the measurements acquired by SyMRI (*: p<0.05).

Proc. Intl. Soc. Mag. Reson. Med. 29 (2021)
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