Association between exposure to childhood maltreatment and brain structure in adults: a DTI study
Poster No:
2183
Submission Type:
Abstract Submission
Authors:
Yanxuan Du1, Huiyuan Huang2, Yao Xiao1, Liwei Tan1, Weiding Wang1, Taihan Chen1, Xinrui Li1, Ruiwang Huang1
Institutions:
1School of Psychology, Key Laboratory of Brain, South China Normal University, Guangzhou, Guangdong, 2School of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong
First Author:
Yanxuan Du
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Co-Author(s):
Huiyuan Huang
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong
School of Public Health and Management, Guangzhou University of Chinese Medicine
Guangzhou, Guangdong
Yao Xiao
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Liwei Tan
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Weiding Wang
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Taihan Chen
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Xinrui Li
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Ruiwang Huang
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Introduction:
Childhood maltreatment represents a strong psychological stressor which can lead to development of later psychopathology as well as a heightened risk of health and social problems[1-2]. Previous studies have utilized voxel-wise and ROI-wise mean diffusivity to detect brain white matter (WM) abnormalities in individuals of childhood maltreatment[3-4]. However, these methods may be not sensitive to represent the diffusivity in a long-range WM fiber tract distributions within a voxel and to reveal the WM microstructure changes due to diseases[5-6]. The automated fiber quantification (AFQ) [7] method provides a more sensitive and specific tool for detecting developmental and clinical changes, and identifying the precise locations of such changes within fiber tracts, making it appropriately suited for exploring WM abnormalities in cases of childhood maltreatment.
Methods:
Participants
We enrolled 43 healthy adult individuals, including 21 with childhood maltreatment (CM) and 22 healthy controls (HC). The participants were recruited from the campus of South China Normal University (SCNU). The study was approved by the Institutional Research Board of SCNU. Each participant gave the written informed consent prior to the study.
Data acquisition
All the MRI data were acquired on a 3T Siemens Trio MRI scanner with a 32-channel phased array head coil. The DTI data were obtained with the following parameters: TR = 9,800ms, TE = 85ms, FOV = 224×224mm2，matrix = 112×112, slice thickness = 2mm and without an interslice gap, 64 non-linear directions with b = 1,000s/ mm2 and one volume with b = 0, and 75 interleaved transversal slices. High-resolution brain images were obtained using the T1-weighted MP-RAGE 3D sequence: TR = 2,300ms, TE = 3.24ms, FOV = 256×256mm2, voxel size = 1mm3.
Data processing
The DTI and T1w data were preprocessed using FSL. The DTI preprocessing included the following steps: the b0 images extraction, the head motion estimation, eddy current correction, imaging segmentation, tensor fitting to obtain the voxel-wise eigenvalues, and the calculation of fractional anisotropy (FA). The T1w images were used for brain extraction and were averaged to align with the AC-PC plane. The preprocessed DTI images and T1w images were fed into the AFQ software. The AFQ procedure steps were summarized as follow: performance of the whole-brain tractography, segmentation of a whole brain fiber group into 20 fascicles groups, definition of the tract core and filtering out of stray fibers, and quantification of the diffusion measures at 100 equidistant nodes along each fiber tract.
A non-parametric permutation test (10,000 times) was used to detect between-group difference in FA along the tracts. Potential confounding variables (age and gender) were selected as covariates in the group comparison. Significance level was set at p < 0. 01[8-9] with a family-wise error (FWE) correction. Only the FA differences that included three or more adjacent nodes along a tract were reported[10].
We enrolled 43 healthy adult individuals, including 21 with childhood maltreatment (CM) and 22 healthy controls (HC). The participants were recruited from the campus of South China Normal University (SCNU). The study was approved by the Institutional Research Board of SCNU. Each participant gave the written informed consent prior to the study.
Data acquisition
All the MRI data were acquired on a 3T Siemens Trio MRI scanner with a 32-channel phased array head coil. The DTI data were obtained with the following parameters: TR = 9,800ms, TE = 85ms, FOV = 224×224mm2，matrix = 112×112, slice thickness = 2mm and without an interslice gap, 64 non-linear directions with b = 1,000s/ mm2 and one volume with b = 0, and 75 interleaved transversal slices. High-resolution brain images were obtained using the T1-weighted MP-RAGE 3D sequence: TR = 2,300ms, TE = 3.24ms, FOV = 256×256mm2, voxel size = 1mm3.
Data processing
The DTI and T1w data were preprocessed using FSL. The DTI preprocessing included the following steps: the b0 images extraction, the head motion estimation, eddy current correction, imaging segmentation, tensor fitting to obtain the voxel-wise eigenvalues, and the calculation of fractional anisotropy (FA). The T1w images were used for brain extraction and were averaged to align with the AC-PC plane. The preprocessed DTI images and T1w images were fed into the AFQ software. The AFQ procedure steps were summarized as follow: performance of the whole-brain tractography, segmentation of a whole brain fiber group into 20 fascicles groups, definition of the tract core and filtering out of stray fibers, and quantification of the diffusion measures at 100 equidistant nodes along each fiber tract.
A non-parametric permutation test (10,000 times) was used to detect between-group difference in FA along the tracts. Potential confounding variables (age and gender) were selected as covariates in the group comparison. Significance level was set at p < 0. 01[8-9] with a family-wise error (FWE) correction. Only the FA differences that included three or more adjacent nodes along a tract were reported[10].
Results:
Fig. 1 shows the node-wise comparison of 2 identified white matter fractional anisotropy profiles among the CM and the HC. The CM showed significantly lower mean FA than the HC in the right inferior fronto-occipital fasciculus (nodes 11-14) and the left uncinate fasciculus (nodes 69-73).
Conclusions:
The CM had a significant lower mean FA than the HC in the right inferior fronto-occipital fasciculus (IFOF_R, nodes 11-14) and the left uncinate fasciculus (UF_L, nodes 69-73). These results revealed the neurodevelopmental alterations associated with the progression of childhood maltreatment. The findings can provide new insights into the microstructural change of psychopathology.
Lifespan Development:
Early life, Adolescence, Aging 2
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity 1
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Tractography
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Childhood maltreatment
1|2Indicates the priority used for review
Provide references using author date format
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