Application Value Of Neurite Orientation Dispersion And Density Imaging In Motor Cortex Of Cerebrum With Parkinson’s Disease

Objective:Using Neurite orientation dispersion and density imaging(NODDI)to measure and analyse the motor cortex in patients with Parkinson’s disease(PD),and to explore the clinical value of NODDI in the diagnosis and treatment of PD patients.Materials and methods:1.A total of 23 patients with clinically diagnosed PD called PD group.All of them have been satisfied of the UK brain bank diagnostic criteria for PD;On the side,selected20 healthy people with age and gender matching with former as Normal Control group(NC)randomly.2.PD patients were divided into Tremor Dominant PD group(TD)and Postural Instability Gait Difficulty PD group(PIGD)according to Movement Disorder Society-Sponsored Revision Unified Parkinson’s Disease Rating Scale(MDS-UPDRS).3.All of the PD patients would need to accomplish the Hoehn-Yahr(H-Y)stages and score of MDS-UPDRS(Part III),aim to analyse the severity of disease.4.All of subjects were examined head by 3.0T MRI,and complete NODDI scan.The original imaging of NODDI using DWINeuro App for post-processing: maps of b0,intracellular volume fraction(Vic),isotropic volume fraction(Viso),and orientation dispersion index(ODI)were generated.Regions of interest(ROIs)were drawn in the primary motor cortex(MC),premotor cortex(PMC)and supplementary motor area(SMA),by using the b0 image as a reference.We applied these ROIs to the Vic,Viso,and ODI maps of the same slice,and measured the values in bilateral MC,PMC,and SMA respectively.5.SPSS 20.0 wasused to analyze the results and datas.All of the sample data were in accordance with the normal distribution,counting datas such as gender information were compared by Chi-square test,and measurement datas were compared by t-test.The measured value analysis at every measuring position from PD group and NC group were compared by Analysis of Variance(ANOVA),and the measured datas of PIGD group and TD group were compared by t-test.The correlation analysis between measured value and correlative scores would use the Pearson’s correlation analysis.Receiver operating characteristic curve(ROC curve)was used to calculate the sensitivity and specificity of NODDI in the diagnosis of PD,and Youden index was used to determine the critical value when the area under the ROC curve(AUC)was more than 0.7.Result:1.Clinical datas analysis: there was no statistically significant difference between the three groups in gender and age(P > 0.05).There was no statistically significant difference between PIGD group and TD group in course of disease,H-Y stage and score of MDS-UPDRS(Part III)(P > 0.05).2.Compared with Normal Control group,the Vic value of bilateral MC in PD group were significantly decreased(P < 0.05);the Viso value of bilateral PMC and SMA in PD group were increased(P < 0.05);the ODI value of bilateral MC and SMA in PD group were increased(P < 0.05).3.The ODI of bilateral MC,contralateral PMC and contralateral SMA in PIGD group were significantly increased compared with TD group(P < 0.05).4.Pearson correlation analysis was carried out between values of different measuring parts of PD group and the course of disease,H-Y stage and score of MDS-UPDRS(Part III).The results showed that there was a moderate positive correlation between the ODI of ipsilateral PMC and H-Y stage.5.Thearea under the ROC curve(AUC)of ODI of contralateral MC for diagnose PD were 81%,sensitivity 74%,specificity 80%.The AUC of Vic of contralateral PMC for diagnose PD were 92%,sensitivity 91%,specificity 85%.The AUC of Vic of contralateral SMA for diagnose PD were 78%,sensitivity 57%,specificity 100%.Conclusion:1.NODDI can reflect the loss of projection nerve fibers and the reduction and degeneration of neurites in cerebral motor cortex of patients with Parkinson’s disease.2.Compared with TD group,the loss of neurites in cerebral motor cortex in PIGD group is more serious.3.The ODI and Vic,contralateral to the most clinically affected side,showed the higher power to diagnose PD.NODDI technology can be more sensitive to the subtle changes of brain tissue structure,so as to provide help for the diagnosis and treatment of PD.