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Quantitative synthetic MRI reveals grey matter abnormalities in children with drug-naïve attention-deficit/hyperactivity disorder

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Abstract

To investigate the quantitative profiles of brain grey matter (GM) in pediatric drug-naïve ADHD patients using synthetic magnetic resonance imaging (SyMRI). A total of 37 drug-naïve pediatric ADHD and 27 age- and gender-matched healthy controls (HC) were enrolled in this study. Each subject underwent both SyMRI and conventional 3D T1-FSPGR scans. Quantitative parameters, T1 and T2 maps, were extracted from the SyMRI data. Between-group quantitative maps were compared using a general linear model analysis. Pearson correlation analysis was conducted to assess the association between significantly altered MR indices and clinical measurements in ADHD. Compared with the HC group, altered T1 and T2 relaxometry times in the ADHD group were mainly distributed in GM regions of the cerebellum, attention and execution control network, default mode network, and limbic areas. Moreover, the T1 value of the right cerebellum 8 was negatively correlated with the attention concentration level in ADHD (R = 0.140, P = 0.0225). With regards to T2 map, the associations were observed between the attention level of ADHD patients and left fusiform gyrus (R = 0.251, P = 0.0016), and right cerebellum crus2 (R = 0.142, P = 0.0214). Altered T1, T2 values found in specific regions of GM, including cerebellum, attention and execution control network, default mode network, and limbic areas, may reveal widespread micromorphology changes, i.e., brain iron deficiency, low myelin content, and enlarged vascular interstitial space in ADHD patients. Thus, T1, T2 values might be promising imaging markers for future ADHD studies.

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Abbreviations

ADHD:

Attention-deficit/hyperactivity disorder

HC:

Healthy control

GM:

Grey matter

SyMRI:

Synthetic magnetic resonance imaging

DMN:

Default mode network

EAN:

Attention and execution control network

QSM:

Quantitative susceptibility mapping

VN:

Visual network

SMN:

Sensorimotor network

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Acknowledgements

We would like to thank the participants and their families, as well as the staff at the MRI at the First Affiliated Hospital of Sun Yat-sen University, for making this study possible.

Funding

This work was supported by the Natural Science Fund Youth Science Fund Project of China [Grant Number 82001439] and the Medical Scientific Research Foundation of Guangdong Province [Grant NumbersA2020327].

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Author notes

  1. Shu Su and Yingqian Chen contributed equally to this study

Authors and Affiliations

  1. Department of Radiology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People’s Republic of China

    Shu Su, Yingqian Chen, Yan Dai, Liping Lin, Qin Zhou, Mengsha Zou, Xianhong Xiang & Zhiyun Yang

  2. MR Research, GE Healthcare, Beijing, People’s Republic of China

    Long Qian

  3. Department of Pediatric, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People’s Republic of China

    Hongyu Zhang & Meina Liu

Authors
  1. Shu Su
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  2. Yingqian Chen
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  3. Yan Dai
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Contributions

Author contributions included: Conceptualization and study design, SS, YC; Methodology, SS, YD, LQ; Investigation, SS, LL, QZ, MZ, HZ, ML, XX; Formal Analysis, SS, LL; Writing—Original Draft, SS, YC; Writing—Review & Editing, SS, YC, ZY, LQ, QZ, MZ, HZ, ML, XX; Visualization, SS. and agreement to be accountable for the integrity and accuracy of all aspects of the work (All authors).

Corresponding authors

Correspondence to Xianhong Xiang or Zhiyun Yang.

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Conflict of interest

None. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the article's subject matter.

Ethics approval

This study was approved by the institutional review board of the First Affiliated Hospital of Sun Yat-sen University (No. [2019]328).

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

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Su, S., Chen, Y., Dai, Y. et al. Quantitative synthetic MRI reveals grey matter abnormalities in children with drug-naïve attention-deficit/hyperactivity disorder. Brain Imaging and Behavior 16, 406–414 (2022). https://doi.org/10.1007/s11682-021-00514-8

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  • DOI: https://doi.org/10.1007/s11682-021-00514-8

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