Literature DB >> 28318404

Magnetization Transfer Imaging of Treatment-resistant Depression.

Zhiyun Jia1, Wei Peng1, Ziqi Chen1, Huaiqiang Sun1, Huawei Zhang1, Weihong Kuang1, Xiaoqi Huang1, Su Lui1, Qiyong Gong1.   

Abstract

Purpose To detect biophysical abnormalities in patients with postmedication treatment-resistant depression (TRD) with magnetization transfer imaging. Materials and Methods This study was approved by the local ethics committee, and written informed consent was obtained from all participants. Participants included 69 patients with major depressive disorder (MDD) (30 with TRD; 39 with non-TRD) and 41 healthy control subjects. Age and sex were examined with one-way analysis of variance and χ2 tests and were well matched among the three groups. Whole-brain voxel-based analysis was used to compare the magnetization transfer ratio (MTR) between the three groups. Regional MTR values were used to analyze the correlations with symptom severity and illness duration. Results MTR differences were identified in the bilateral precentral gyrus, left cerebellum posterior lobe, left middle occipital lobe, left precuneus, and left temporal lobe among the three groups. Relative to patients with non-TRD, those with TRD had significantly lower MTR in the task-positive network regions, including the bilateral precentral gyrus and left middle occipital lobe, and had lower MTR in the default mode network regions, including the left precuneus and left temporal lobe. Regional MTRs were not associated with symptom severity or illness duration. Conclusion These results suggest that treatment resistance in patients with MDD may be mediated by macromolecular abnormalities in the task-positive and default mode functional networks. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 29, 2017.

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Year:  2017        PMID: 28318404     DOI: 10.1148/radiol.2017160820

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


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