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Study On Microstructure Of White Matter In Patients With Postpartum Depression Based On Tract-based Spatial Statistics Magnetic Resonance Diffusion Tensor Imaging

Posted on:2021-01-17Degree:MasterType:Thesis
Country:ChinaCandidate:J H HuangFull Text:PDF
GTID:2504306533959339Subject:Medical imaging and nuclear medicine
Abstract/Summary:
Background and purpose:Postpartum depression(PPD)is the most common psychological and mental disorder in the postpartum period.Studies have shown that genetic,neurobiochemical and socio-psychological factors have a significant impact on the occurrence of PPD.Typical symptoms include depression,loss of interest and pleasure and energy fatigue,accompanied by anxiety and psychotic symptoms.Serious cases can cause suicidal tendency.11% to18% of postpartum women have postpartum depression symptoms,and the peak period of postpartum depression is within 3 months and 6 months after delivery.At present,the diagnosis of PPD is mainly conducted in the doctor-patient conversation,in which doctors understand the maternal psychological status,mental and physical examination,and depression scale screening,with strong subjective factors and lack of objective laboratory and imaging evaluation indicators.In recent years,functional MRI has been widely used in the field of neuropsychiatric diseases,which provides imaging evidence for exploring the changes of brain structure and function and the neuropathological mechanism of various diseases.Diffusion tensor imaging(DTI)is a non-invasive examination method which can effectively observe and track the direction and integrity of white matter fiber tracts in vivo.it can detect the possible location and pathogenesis of white matter fiber bundles through abnormal changes,and provide an effective bridge for the study of the relationship between phenomenology and biology of mental or behavioral abnormalities.Purpose of this study:(1)The diffusion tensor imaging(DTI)data of postpartum depression(PPD)patients and healthy pregnant women were processed by trace-based spatial statistics(TBSS)technique,so as to discover the changes of the white matter microstructure in postpartum depression patients and explore the possible neuropathologic mechanism.(2)to explore the relationship white matter structure damage index between and clinical scale in patients with PPD.(3)Whether PPD and depression have similar neuropathological mechanism and changes of neural circuit structure.Methods:According to the diagnostic criteria of postpartum depression in the5 th edition of American Diagnostic and Statistical Manual of Mental Disorders,33 postpartum depression patients(PPD group)were selected,EPDS≥9.28 healthy pregnant women matched with age,education and postpartum time(control group)were selected,EPDS≤3.Routine brain MRI,T1 WI structural images and DTI scans were performed in the two groups with German SIEMENS 3.0T Verio MRI device,and TBSS technique in FSL was used to process DTI data.Multiple comparison correction was performed by the method of threshold-free cluster enhancement.The scores of fractional anisotropy of white matter fiber tracts with significant differences between the PPD group and the control group were compared with those of the Edinburgh Postpartum Depression scale score was analyzed by Spearson correlation analysis.P<0.05 indicated that the difference was statistically significant.Results:The FA values of right forceps minor /anterior thalamic radiation /anterior cingulate gyrus and right uncinate fasciculus in PPD group were lower than those in control group(TFCE,P<0.05),there was no correlation between EPDS score and white matter fiber bundle with statistically significant difference.Conclusions:The TBSS technique of magnetic resonance DTI can detect the microstructure changes of white matter in patients with PPD.PPD may have neuropathological mechanism similar to depression patients and damage in the neural circuits of emotion regulation composed of prefrontal cortex,limbic cortex and subcortical cortex.
Keywords/Search Tags:Postpartum depression, diffusion tensor imaging, trace-based spatial statistics, Magnetic Resonance Imaging
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