1.Study on multi-parametric texture analysis for quantifying brain magnetic susceptibility in patients with Parkinson's disease
Journal of Shanghai Jiaotong University(Medical Science) 2025;45(1):69-78
Objective·To quantify brain iron content in Parkinson's disease(PD)patients by using quantitative susceptibility mapping(QSM)based on phase linearity fitting.Combined with texture analysis methods,the magnetic susceptibility distribution characteristics of gray matter nuclei in PD patients were quantitatively analyzed with multiple parameters and dimensions,and the sensitivity of texture features was evaluated with clinical scoring.Methods·Quantitative susceptibility images from 20 PD patients and 20 healthy controls(HC)were analyzed retrospectively.Regions of interest in basal ganglia were manually segmented,followed by three-dimensional texture analysis by using gray-level run-length matrix(GLRLM).One-way analysis of variance(ANOVA)was performed to compare differences between the two groups,and the bilateral Pearson linear correlation coefficient(r)was calculated to evaluate the correlation between texture parameters and UPDRS-Ⅲ clinical scores.Results·The analysis of texture feature parameters showed that there were significant differences between the PD and HC groups in the gray matter nuclei.Among all the texture feature parameters of GLRLM,LngREnch showed significant differences between the PD group and the HC group in the five gray matter nuclei measured.The average magnetic susceptibility of gray matter nuclei and GLRLM texture parameters were sensitive in distinguishing PD from HC(AUC>0.5).The AUC values of RLNonUni,LngREnch,ShrtREmp,and Fraction were higher than that of the average magnetization susceptibiliyt.The correlation analysis showed that RLNonUni and GLevNonU in the caudate nucleus(CN),as well as GLevNonU in the red nucleus(RN),were significantly correlated with UPDRS-Ⅲ scores,while no significant clinical correlations were found for the remaining parameters.Conclusion·Compared to the mean magnetic susceptibility values,GLRLM texture parameters provide better differentiation between the PD and HC groups.Multiparameter texture analysis offers a novel approach to QSM-based quantitative assessment of brain iron content,which can provide additional multidimensional quantitative information for the non-invasive diagnosis of PD.
2.Study on multi-parametric texture analysis for quantifying brain magnetic susceptibility in patients with Parkinson's disease
Journal of Shanghai Jiaotong University(Medical Science) 2025;45(1):69-78
Objective·To quantify brain iron content in Parkinson's disease(PD)patients by using quantitative susceptibility mapping(QSM)based on phase linearity fitting.Combined with texture analysis methods,the magnetic susceptibility distribution characteristics of gray matter nuclei in PD patients were quantitatively analyzed with multiple parameters and dimensions,and the sensitivity of texture features was evaluated with clinical scoring.Methods·Quantitative susceptibility images from 20 PD patients and 20 healthy controls(HC)were analyzed retrospectively.Regions of interest in basal ganglia were manually segmented,followed by three-dimensional texture analysis by using gray-level run-length matrix(GLRLM).One-way analysis of variance(ANOVA)was performed to compare differences between the two groups,and the bilateral Pearson linear correlation coefficient(r)was calculated to evaluate the correlation between texture parameters and UPDRS-Ⅲ clinical scores.Results·The analysis of texture feature parameters showed that there were significant differences between the PD and HC groups in the gray matter nuclei.Among all the texture feature parameters of GLRLM,LngREnch showed significant differences between the PD group and the HC group in the five gray matter nuclei measured.The average magnetic susceptibility of gray matter nuclei and GLRLM texture parameters were sensitive in distinguishing PD from HC(AUC>0.5).The AUC values of RLNonUni,LngREnch,ShrtREmp,and Fraction were higher than that of the average magnetization susceptibiliyt.The correlation analysis showed that RLNonUni and GLevNonU in the caudate nucleus(CN),as well as GLevNonU in the red nucleus(RN),were significantly correlated with UPDRS-Ⅲ scores,while no significant clinical correlations were found for the remaining parameters.Conclusion·Compared to the mean magnetic susceptibility values,GLRLM texture parameters provide better differentiation between the PD and HC groups.Multiparameter texture analysis offers a novel approach to QSM-based quantitative assessment of brain iron content,which can provide additional multidimensional quantitative information for the non-invasive diagnosis of PD.
3.Proton magnetic resonance spectroscopy of brain metabolism after traumatic axonal injury in rats
Xueyuan LI ; Jianqi LI ; Dongfu FENG ; Jia LI ; Mingxia FAN ; Mengchao PEI ; Lei GU ; Weiwei MEN
Chinese Journal of Trauma 2011;27(3):213-217
Objective To investigate the brain metabolic changes and evaluate their spatial distributions after traumatic axonal injury (TAI)in rats by using proton magnetic resonance spectroscopy(1H-MRS).Methods The TAI model was made by subjecting the head of the rats to the linear and angular accelerations.The multi-voxel MRS was employed to detect the tissue metabolic state at the levels of hippocampus-caudate and pons prior to injury and at 24 hours after injury.The alterations of NAA/Cr,NAA/Cho and Cho/Cr values as well as the spatial distribution of NAA/Cr reduction were accessed. Immunohistochemical staining for β-APP was used to observe the injured axons. Results A siguificantdecrease in NAA/Cr and NAA/Cho(P<0.05)and subtle increase in Cho/Cr(P>0.05)were observed in rats at 24 hours after TAI in comparison to the pre-injury levels.Notable decrease in NAA/Cr value was observed in the areas including the brain stem,hippocampus,internal capsule,corpus callosum and thalamus,where axonal injuries were confirmed by the histological examination. Conclusion Metabolic imbalances Occur in the brains of rats with TAI.with notable changes in the brain stem and the hippocampus.

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