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单相和双相抑郁症患者膝下前扣带回皮质的高场成像

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression.

作者信息

Buchholz Frederik, Meffert Martin, Bazin Pierre-Louis, Trampel Robert, Turner Robert, Schönknecht Peter

机构信息

Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany.

Full Brain Picture Analytics, Leiden, Netherlands.

出版信息

Front Psychiatry. 2024 Oct 11;15:1462919. doi: 10.3389/fpsyt.2024.1462919. eCollection 2024.

Abstract

BACKGROUND

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders.

METHOD

In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects.

RESULTS

Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively.

CONCLUSION

To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

摘要

背景

膝下前扣带回皮质(sgACC)作为前扣带回皮质和边缘系统的一部分,在情绪调节中起着关键作用。先前对sgACC的结构和功能脑成像研究显示,重度抑郁症(MDD)和双相情感障碍(BD)患者的灰质(GM)体积和血氧水平依赖信号(BOLD)发生了改变,这表明情感障碍具有潜在的生物标志物特征。

方法

在本研究中,我们调查了3个不同患者组的sgACC灰质体积:40例MDD患者,其中20例接受药物治疗(MDDm),20例未接受药物治疗(MDDu),以及21例接受药物治疗的BD患者,并将他们与23名健康志愿者进行比较。我们使用高分辨率7T磁共振成像(MRI)检查GM体积变化,该成像产生了自旋晶格弛豫时间(T1)的定量图谱。T1图谱在灰质和白质之间提供了高对比度,并且在7T时,可以在合理的扫描时间内获取具有亚毫米分辨率的体素。我们基于先前体积研究中得出的精细地标开发了一种半自动分割方案,使用定量T1图谱作为GM、WM和脑脊液(CSF)组织自动组织分割的原始输入数据。然后将sgACC感兴趣区(ROI)叠加在这些组织概率图谱上,并由两名独立的评估者(F.B.,M.M.)按照我们的半自动分割方案进行手动追踪。对每个半球的10例脑扫描子集计算评估者间信度,结果显示左sgACC的组内相关系数(ICC)r = 0.96,右sgACC的r = 0.84。总之,我们开发了一种可重复且可靠的半自动分割方案来测量sgACC中的灰质体积。基于先前对sgACC形态计量学研究的荟萃分析结果,我们假设MDD患者与健康受试者相比,其sgACC灰质体积会更低。

结果

事后分析显示,药物治疗组(MDDm)和未药物治疗组(MDDu)的左半球膝下体积均小于健康对照组(分别为p = 0.001,p = 0.008)。对于右半球,未药物治疗组(MDDu)和BD组的膝下体积分别显著低于健康对照组(p < 0.001,p = 0.004)。

结论

据我们所知,这是第一项使用高分辨率7T MRI获得的T1图谱对MDD和BD患者与健康对照组进行比较的形态计量MRI研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf3e/11502385/8ccbf80d0753/fpsyt-15-1462919-g001.jpg

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