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Objective:To explore the efficiency of MR psychoradiology examination in screening and classification of psychiatric disorders as well as its potential clinical application.Methods:Retrospective study was conducted for 144 patients with MR psychoradiology examination, who were diagnosed mental disorders based on International Statistical Classification of Diseases and Related Health Problems Tenth Revision (ICD-10) from September 2018 to July 2020 in West China Hospital of Sichuan University. As our previous studies, imaging diagnostic models were constructed based on gray matter volume (GMV) analysis for four kinds of psychiatric disorders, including depression, anxiety disorder, bipolar disorder and schizophrenia. For 120 patients with psychiatric disorders, the GMV change pattern of brain regions was detected and subtyped by MR psychoradiology examination with 50% similarity threshold of the above imaging diagnostic models. The diagnostic efficiency of MR psychoradiology examination was evaluated with references of clinical diagnose. For 24 patients with dementia, brain atrophy was additionally measured by conventional MR examination and MR psychoradiology examination respectively.Results:The sensitivity, specificity, Youden index and accuracy of MR psychoradiology in identifying the four psychiatric disorders were 86.6% (84/97), 69.6% (16/23), 0.56 and 83.3% (100/120), including depression [77.8% (28/36), 69.0% (58/84), 0.47, 71.7% (86/120)], schizophrenia [58.8% (10/17), 91.3% (94/103), 0.50, 86.7% (104/120)], bipolar disorder [42.1% (8/19), 96.0% (97/101), 0.38, 87.5% (105/120)] and anxiety disorder [24.0% (6/25), 100% (95/95), 0.24, 84.2% (101/120)]. As for 24 patients with dementia, 58.3% (14/24) were detected with brain atrophy by conventional MR examination, while 91.7% (22/24) were detected by MR psychoradiology examination.Conclusions:MR psychoradiology can detect the subtle brain structural abnormalities of patients with mental disorders. Although it can′t be used as an independent biomarker for disease diagnosis till now, it is of great help in improving the accuracy and objectivity of diagnosis.
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Objective:To investigate the prognostic value of platelet volume indices (PVIs), neutrophil/lymphocyte ratio (NLR) and the combination of these parameters for the neurological function of acute ischemic stroke (AIS) patients after intravenous thrombolysis.Methods:From January 2016 to January 2019, the data of 147 AIS patients with intravenous thrombolysis in the Emergency Department of Peking University People's Hospital who met the diagnostic criteria of AIS were retrospectively analyzed. The patients were divided into two groups according to modified rank in scale (MRS) score: MRS≤2 and MRS≥3. The general information, past medical history and laboratory examination results of each group were compared. Logistic regression analysis was used to analyze the risk factors of poor prognosis of neurological function in AIS patients with thrombolysis.Results:NLR ( OR=1.045, 95% CI: 1.032-2.350, P=0.032), mean platelet volume (MPV) ( OR=4.212, 95% CI:1.074-16.513, P=0.039), MPV×NLR/PLT ( OR=5.711, 95% CI: 1.342-24.298, P=0.018), platelet distribution width (PDW) ( OR=1.015, 95% CI: 1.001-2.372, P=0.032), and NIHSS score ( OR=1.266, 95% CI: 1.111-1.443, P<0.01) were related with poor prognosis neurological function of AIS patients with intravenous thrombolysis. Conclusions:MPV, NLR, MPV×NLR/PLT PDW and NIHSS scores are the risk factors for poor prognosis of neurological function in AIS patients with thrombolysis. MPV×NLR/PLT can predict the neurological severity of AIS after 3 months.
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Objective:To investigate the relationship between neutrophil to lymphocyte ratio (NLR) and the severity of acute ischemic stroke (AIS) and the prognosis of patients undergoing intravenous thrombolysis (IVT).Methods:From January 2016 to January 2019, 147 AIS patients with intravenous thrombolysis in the Emergency Department of Peking University People's Hospital who met the diagnostic criteria of AIS were studied retrospectively. According to the NLR value, 147 patients were divided into the NLR 2 or less group ( n=37) or less, 2 < NLR < 3 group ( n=31), and the NLR≥3 group ( n=79). General data, medical history, laboratory examination results, NIHSS score and mRS score of patients in each group were compared. Logistic regression analysis was used to analyze the relationship between NLR and severity of acute ischemic stroke patients and clinical prognosis with thrombolysis. Results:NLR was associated with AIS stroke severity ( OR=2.044, 95% CI: 1.011-8.566, P=0.006). NLR was associated with poor prognosis of AIS neurological function with thrombolysis ( OR=3.744, 95% CI: 0.997-4.713, P=0.003). However, NLR was not associated with AIS death after thrombolysis ( OR=0.591, 95% CI: 0.750-1.933, P=0.442). Conclusions:NLR was associated with the severity of stroke in AIS patients and the prognosis of poor neurological function with thrombolysis.
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Objective To explore the relationship between changes in cortical thickness and single nucleotide polymorphisms(SNPs) in the human leukocyte antigen(HLA) in a group of antipsychotic-naive schizophrenia (AN-SCZ) patients. Methods Twenty-five chronically ill AN-SCZ patients and 51 healthy controls (HCs) were recruited and studied from May 2014 to July 2016. All participants received 3.0 T MR head scans and blood collection to obtain high resolution T1WI images and detailed genetic data. Next, we extracted and averaged the values of cortical thickness from each brain region(n=68) for each participant by FreeSurfer and then used general linear models to explore the relationship of each SNP with cortical thickness in the AN-SCZ and HCs while including age, gender and duration of disease in the models as covariates. In the next step,we applied an independent-samples t-test with a threshold of 0.05 to explore whether the cortical thicknesses differed significantly between the AN-SCZ and HCs in the brain regions that were significantly associated with the SNPs in the MHC. Finally, we examined the correlation of clinical symptoms with cortical thickness in the above brain areas in the whole AN-SCZ group using Pearson correlation tests. Results Seven of the 11 SNPs within the HLA regions exhibited significant associations with the cortical thickness only in the AN-SCZ patients, including rs1635, rs1736913, rs2021722, rs204999, rs2523722, rs3131296 and rs9272105. Furthermore, the AN-SCZ patients also exhibited significant reductions in cortical thickness in the above brain regions, which included the left entorhinal cortex, the left pars triangularis cortex, the left rostral middle frontal cortex, the right lateral occipital cortex, the right medial orbitofrontal cortex, the gray matter surrounding the right calcarine gyrus, the right rostral middle frontal cortex, the right frontal pole and the caudal part of the right anterior cingulate. The left entorhinal region also exhibited a negative correlation with PANSS activation scores in the AN-SCZ(r=-0.601, P=0.03). Conclusion The present study provided evidence for the significant association of HLA risk variants with cortical thickness in AN-SCZ.
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Objective To measure the sternal angle corresponded to thoracic plane by three-dimensional reconstruction of spiral CT , and to explore the accurate positioning methods and the preoperative assessment of cervicothoracic junction lesions .Methods Selected 42 cases of normal bone mass , 48 cases with bone loss , and 60 cases of osteoporosis who were diagnosed by dual-energy X-ray absorptiometry , and measured the location of thoracic sternal angle corresponded to the thoracic spine and thoracic kyphosis angle through the volume recon -struction data of the 16-slice spiral CT chest examinations .Results The range of sternal angle corresponded to thoracic plane was measure-ment units ⅢtoⅥ.The measure unit Ⅳwas the most, accounting for about 55%.There was no statistical significance between the position of sternal angle corresponded to thoracic plane and the relationship of bone mass , which required further study .The position of sternal angle corresponded to thoracic plane was associated with the thoracic kyphosis angle .The larger the thoracic kyphosis angle , the lower the corre-sponding position was .Conclusion The thoracic segment corresponded to the sternal angle is not a constant or accurate plane , which is not properly concerned as an accurate positioning mark to the thoracic segment .The measurement of the thoracic sternal angle was corresponded to the thoracic spine location , and its co-relationship evaluation between the thoracic kyphosis angle was vital for the accurately positioning of cervico-thoracic junction area lesions , the pre-assessment methods of surgical treatment , approach selection , and different methods for ster-num and other such contents .This research was of important clinical significance .
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Objective Present study aimed to characterize the alteration of cortical thickness in first-episode, never-medicated, adult patients with major depressive disorder (MDD), and explore whether such deficits were related with their disease duration and clinical symptom severity. Methods Thirty-seven adult MDD patients were recruited from March 2013 to August 2015 as patient group, and 41 healthy volunteers were as control group. All the patients underwent three-dimensional spoiled gradient recalled (3D-SPGR) sequences, and the images were acquired. Constructions of the cortical surface were developed from 3D-SPGR images using FreeSurfer software, and the thickness of the entire cortex was measured according to the automated surface reconstruction, transformation, and high-resolution inter-subject alignment procedures. Finally, cortical thickness was compared between the two groups, and the relativity between clinical symptom severity, disease progression and clinical scores were analyzed using the General Linear Model (GLM). Results Our results revealed a significant increase in cortical thickness(P0.05). Conclusion Excluding the impact of treatment, our study showed that the cortical thickness change was mainly located in the prefrontal-limbic system in the in early course of MDD.
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Objective To evaluate the clinical value of whole-brain diffusion tensor imaging(DTI) in diagnosing patients with social anxiety disorder(SAD) using an automated method based on support vector machine(SVM) classification.Methods Whole brain DTI data were collected from 19 patients with SAD and 19 age-,gender-and education-matched healthy control(HC) subjects.Fractional anisotropy(FA) of whole brain was obtained by input all tensor images into Diffusion Toolkit software.Based upon the characteristics of brain FA,the pattern recognition of brain image data(PROBID) toolbox on the grounds of SVM algorithm was employed to classify the subjects,evaluate the diagnostic value of whole-brain FA data based SVM in diagnosing SAD patients and verify the robustness of the diagnostic results using permutation test with the threshold at P≤0.001.The weight vector score of each voxel was calculated according to the ratio between this voxel and whole brain in FA differences of the two groups.The white matter regions identified by setting the threshold to the top 30％ of the weight vector scores with at least 10 contiguous voxels were demonstrated by MRIcro software.Results Diagnostic accuracy of whole-brain FA based SVM in diagnosing SAD was 92.11％ (35/38) in which the specificity was 94.44％ (17/18),the sensitivity was 90.00％(18/20),the positive likelihood ratio was 17.01,the negative likelihood ratio was 0.11 and the diagnostic index was 184.22％.Permutation test suggested that the diagnostic results were significantly reliable.White matter regions showing major contributions favoring SAD over HC were located in the genu and splenium of the corpus callosum,the left uncinate fasciculus,the left inferior longitudinal fasciculus,the left inferior fronto-occipital fasciculus,bilateral frontal gyri and the left occipital lobe.Whereas,white matter in bilateral anterior cingula,the left middle cerebellar peduncle and the left inferior parietal lobule showed more contributions to diagnose HC than to diagnose SAD.Conclusions As whole brain FA data based on SVM showing a high accuracy in diagnosing SAD,brain DTI characteristics have the potential to be the specific indicators in the diagnosis of SAD.SVM might be used as a tool to verify the reliability of white matter abnormalities and provide regions of interest in DTI study of neurological and psychiatric diseases.
