Poster No:
463
Submission Type:
Abstract Submission
Authors:
Che-Yu Hsu1, Vincent Chin-Hung Chen2,3, Yuan-Hsiung Tsai4,3, Yi-hsiang You1, Jun-Cheng Weng1
Institutions:
1Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan, 2Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan, 3School of Medicine, Chang Gung University, Taoyuan, Taiwan, 4Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan
First Author:
Che-Yu Hsu
Department of Medical Imaging and Radiological Sciences, Chang Gung University
Taoyuan, Taiwan
Co-Author(s):
Vincent Chin-Hung Chen
Department of Psychiatry, Chang Gung Memorial Hospital|School of Medicine, Chang Gung University
Chiayi, Taiwan|Taoyuan, Taiwan
Yuan-Hsiung Tsai
Department of Diagnostic Radiology, Chang Gung Memorial Hospital|School of Medicine, Chang Gung University
Chiayi, Taiwan|Taoyuan, Taiwan
Yi-hsiang You
Department of Medical Imaging and Radiological Sciences, Chang Gung University
Taoyuan, Taiwan
Jun-Cheng Weng
Department of Medical Imaging and Radiological Sciences, Chang Gung University
Taoyuan, Taiwan
Introduction:
Depression is a major global mental health challenge and is strongly associated with suicide. Traditional diagnostic tools such as self-reporting often lack accuracy due to bias (Disner et al., 2011). MRI provides an objective way to study the structure of the brain, revealing differences in areas such as the prefrontal cortex and hippocampus in patients with depression and suicidal ideation (Simon et al., 2023). This study aims to fill the research gap by analyzing longitudinal MRI data to identify brain changes over one year in four groups (healthy, depressed, suicidal ideation, and improving). The goal is to improve clinical accuracy through image-based labeling and to support early intervention in high-risk individuals
Methods:
This study recruited 86 participants, divided into a healthy control group (HC) (26), a depression group without suicidal thoughts (NS) (29), a depression group with suicidal thoughts (SI) (18), and a suicide group. Thought improvement group (IM) (13). Participants underwent clinical assessment, psychometric testing, and 3T MRI scans at time point 1 and time point 2. Participants with a history of other psychiatric disorders, alcohol abuse, or neurological disorders were excluded.
Four clinical assessments were conducted, involving the Hamilton Depression Rating Scale (HAM-D), Hospital Anxiety and Depression Scale (HADS), Beck Scale for Suicide Ideation (BSS), and Ruminative Responses Scale (RRS). These scales were utilized to evaluate potential symptoms of anxiety and depression.
In this study, voxel-based morphometry (VBM) and vertex shape analysis were used to process the MRI images to compare the structural differences of the brain; VBM analysis included image correction, standardization, segmentation of gray and white matter, and smoothing; and vertex analysis used FSL to segment and measure the shape of 15 brain regions. Statistical analyses included ANCOVA examination time and group interactions, and regression analyses were performed to examine the association between neuropsychological tests and brain volume changes, with significance at corrected p < 0.05.
Results:
The present study investigated the association between structural changes in different brain regions and depression and suicidal ideation in four groups: HC, NS, SI, and IM. Repeated measures of ANCOVA showed significant changes in the cingulate gyrus, the white matter of the corpus callosum, parietal lobe, hippocampal gyrus, inferior frontal gyrus, superior temporal gyrus, and insular lobe. The volume changes in the posterior central gyrus of the NS and SI groups may be related to the emergence of suicidal ideation, while the recovery of the hippocampal gyrus, frontal lobe, and brainstem of the IM group reflects the enhancement of the emotion regulation function (Drevets et al., 2008). Scales such as the HAM-D and the HADS-A indicate that the changes in these brain regions are closely related to emotion regulation, self-reflection, and visual processing functions (Xie et al., 2018). However, the single-center recruitment, one-year longitudinal design, and treatment differences are limitations of the study, and the sample size should be enlarged, the follow-up period should be extended, and the analysis of treatment interventions should be refined in the future.
Conclusions:
In the present study, we utilized VBM of MRI to observe the longitudinal changes in the brain structure of HC, NS, SI, and IM groups, and the significantly affected areas included cingulate loops, thalamus, hippocampal loops, and insula, which are closely related to emotion regulation and suicidal ideation. Combined with psychological scales (HAM-D, HADS-A, BSS, RRS), the study reveals the association between structural changes in the brain and clinical symptoms, which highlights the importance of MRI in the early detection of mental disorders and personalized diagnosis and treatment.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Higher Cognitive Functions:
Higher Cognitive Functions Other
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Affective Disorders
Cognition
Cortex
Emotions
MRI
Psychiatric Disorders
Treatment
White Matter
Other - longitudinal study
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Structural MRI
Other, Please specify
-
clinical assessments
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
Other, Please list
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VBM, SPM
Provide references using APA citation style.
Disner, S. G., Beevers, C. G., Haigh, E. A., & Beck, A. T. (2011). Neural mechanisms of the cognitive model of depression. Nature Reviews Neuroscience, 12(8), 467-477.
Drevets, W. C., Price, J. L., & Furey, M. L. (2008). Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain structure and function, 213, 93-118.
Simon, G. E., Richards, J. E., & Whiteside, U. (2023). Reframing the key questions regarding screening for suicide risk. JAMA, 329(23), 2026-2027.
Xie, W., Li, H., Zou, Y., Sun, X., & Shi, C. (2018). A suicidal mind tends to maintain less negative information in visual working memory. Psychiatry Research, 262, 549-557.
No