Functional And Structural Magnetic Resonance Imaging In Patients With Traumatic Brain Injury

With the rapid development of society and economy,traumatic brain injury is paid more and more attention.Patients often suffer lasting cognitive,physical,behavioral and emotional dificits and abnormality after traumatic brain injury,which cause heavy burden to patients and their families,and even the society.This paper mainly focused on the change of regional brain function,white matter structure and inflammation of patients with traumatic brain injury,as well as their association with patients' cognitive and emotional deficits.This paper was divided into three parts,and the specific content was as follows:Section I Regional Homogeneity in Patients with Acute Mild Traumatic Brain Injury:A Resting-State f MRI StudyObjective:Mild traumatic brain injury(m TBI)is characterized by structural disconnection and large-scale neural network dysfunction in the resting state.However,little is known concerning the intrinsic changes in local spontaneous brain activity in patients with m TBI.The aim of the current study was to assess regional synchronization in acute m TBI patients.Methods:Fifteen acute m TBI patients(mean age,38.5 ± 11.5 years)and 15 sex-,age-,and education-matched healthy controls(mean age,39.3 ± 11.5 years)were included in this study.Clinical assessment was performed within 2 hours of MR imaging for the two groups,including the Glasgow Coma Scale(GCS)score,Mini-Mental State Examination(MMSE),Beck's Depression Inventory(BDI),and the Hamilton Anxiety Rating Scale(HAMA).Siemens Trio Tim 3.0-Tesla scanner was used to obtain resting-state f MRI data and high-resolution three-dimensional T1-weighted images.The resting-state functional data were analyzed using Data Processing Assistant for Resting-State f MRI-Advanced(DPARSFA,http://www.restfmri.net)based on Statistical Parametric Mapping(SPM8,http://www.fil.ion.ucl.ac.uk/spm).Re Ho maps were generated by calculating Kendall's coefficient of concordance(KCC)within a gray matter mask.Two-sample t-tests were performed to assess the differences in age and duration of education between the two groups using the SPSS 13.0 software package.A two-sample t-test was performed to compare the Re Ho differences between the two groups in SPM8 software.Voxels with a cluster size >1053 mm~3(39 voxels),and p value < 0.01(corresponding to Alpha Sim p < 0.05 multiple correction),were considered to have a significant difference between groups.In m TBI patients,we further examined Pearson's correlation between the Re Ho values of voxels in the group-difference areas and behavior variables.Results:1.There was no significant difference in age and years of education between the m TBI patients and healthy controls.In the m TBI group,9/15 participants were injured because of motor vehicle accident,and the others were injured as a result of a fall or strike.Only 4/15(26.7%)patients were diagnosed with mild scalp swelling on both T2 WI and SWI;the others had no abnormalities on T2 WI and SWI.2.All of the subjects had normal MMSE scores(> 27),and no significant differences were found(p = 0.109).Patients had significantly higher levels of depression(p = 0.005)and anxiety(p = 0.004)than did healthy controls.3.Compared with healthy controls,patients with acute m TBI showed significantly decreased Re Ho in brain regions,including the left insula,left precentral/postcentral gyrus,and left supramarginal gyrus at the threshold in clusters larger than 39 voxels at p < 0.01.There was no increased Re Ho in acute m TBI patients.4.A positive correlation was found between the Re Ho of the left insula and MMSE score(r = 0.65,p < 0.008).No significant correlation was observed between the mean abnormal Re Ho values in other brain areas and clinical assessments.Conclusion:1.The Re Ho method may provide an objective biomarker for evaluating the functional abnormity of mTBI in the acute setting.2.These abnormalities may play an important role in the pathophysiology of post-concussion symptoms in m TBI patients.Section II Amplitude of Low-Frequency Fluctuations in MultipleFrequency Bands in Acute Mild Traumatic Brain injury: A RestingState f MRI StudyObjective:Functional disconnectivity during the resting state has been observed in mild traumatic brain injury(m TBI)patients during the acute stage.However,it remains largely unknown whether the abnormalities are related to specific frequency bands of the low-frequency oscillations(LFO).Here,we used the amplitude of low-frequency fluctuations(ALFF)to examine the amplitudes of LFO in different frequency bands(slow-5: 0.01–0.027 Hz;slow-4: 0.027–0.073 Hz;and typical: 0.01–0.08 Hz)in patients with acute m TBI.Methods:A total of 24 acute mTBI patients and 24 age-,sex-,and education-matched healthy controls participated in this study.Mini-Mental State Examination(MMSE)assessment was performed within 2 hours of MR imaging for the two groups.Siemens Trio Tim 3.0-Tesla scanner was used to obtain resting-state f MRI data and high-resolution three-dimension T1-weighted images.The resting-state functional data were analyzed using Data Processing Assistant for Resting-State f MRIAdvanced(DPARSFA,http://www.restfmri.net)based on Statistical Parametric Mapping(SPM8,http://www.fil.ion.ucl.ac.uk/spm).For ALFF,we first conducted one-sample two-tailed t-tests to determine the within-group effects across the three frequency bands(slow-5: 0.01–0.027 Hz;slow-4: 0.027–0.073 Hz;and typical: 0.01–0.08 Hz).Then,a second-level independent two-sample t-test was performed to determine the difference between groups in the typical frequency band(0.01–0.08 Hz).An analysis of variance(ANOVA)was used to obtain the main effects of frequency band,the main effect of group,and their interactions.Gaussian random field(GRF)correction(i.e.,clusters with a voxel-level p-value < 0.01 and clusterlevel p < 0.05)was used to obtain a significant difference between the two groups.In m TBI patients,correlation analyses were conducted between the MMSE score and ALFF values extracted from brain regions with significant group differences in three frequency bands,separately.Results:1.ALFF analyses in typical frequency band(0.01–0.08 Hz)(1)For both the acute mTBI and healthy control groups,there were significantly higher ALFF values than the global averaged values in some regions,including the visual cortex,posterior cingulate cortex(PCC)/precuneus,bilateral thalami,bilateral ventral medial prefrontal cortices(VMPFC),bilateral middle temporal gyri(MTG),and dorsolateral prefrontal cortex(DLPFC),mainly along the midline.(2)Compared with healthy controls,patients with acute mTBI showed lower ALFF in the right middle frontal gyrus [Brodmann's area(BA)10].Patients also exhibited higher ALFF in the right lingual/fusiform gyrus(BA 19/18/37)and left middle occipital gyrus(BA 19).2.ALFF changes in different frequency bands(1)The main effect of group was observed in the bilateral middle frontal gyri(BA 10),left posterior cerebellum lobe(m TBI < HC),bilateral middle occipital gyri(BA 18/19),and right postcentral gyrus(BA 3/2),extending into the right precentral regions(BA 4)(m TBI > HC).(2)The main effect of frequency was presented in the right inferior frontal gyrus(BA 11/4 7/10)(slow-4 < slow-5)and left white matter(slow-4 > slow-5).(3)No significant interaction between frequency band and group was observed.Further analyses revealed that m TBI patients showed lower ALFF in the right middle frontal gyrus and higher ALFF in the right lingual/fusiform gyrus(BA 19/18/37)and the bilateral cuneus/lingual gyri(BA 31/18/17)in the slow-4 band and only exhibited higher ALFF in the right lingual gyrus(BA 19)and left middle occipital gyrus(BA 19/18)in the slow-5 band.(4)No significant correlation between MMSE score and standardized ALFF value was found in any brain region in the three frequency bands.Conclusion:1.The abnormality of spontaneous brain activity in acute m TBI patients existed in the frontal lobe as well as in distributed brain regions associated with integrative,sensory,and emotional roles,and the abnormal spontaneous neuronal activity in different brain regions could be better detected by the slow-4 band.2.These findings might contribute to a better understanding of local neural psychopathology of acute m TBI.Future studies should take the frequency bands into account when measuring intrinsic brain activity of m TBI patients.Section III A Comparison of Diffusion Tensor Imaging and Diffusion Basis Spectrum Imaging in Patients with Chronic Traumatic Brain InjuryObjective:White matter(WM)injury is a hallmark pathology of chronic traumatic brain injury(TBI),and plays a key role in the development of long-term neurodegenerative disease.White matter pathology has been reported highly associated with persistent neuroinflammation following head trauma in TBI patients.However,few clinical neuroimaging approaches are able to detect white matter injury and the concomitant neuroinflammation.Although diffusion tensor imaging(DTI)measure has been widely used in examining white matter abnormality,DTI model could not detect inflammatory cell infiltration and edema.In recent years,a novel diffusion basis spectrum imaging(DBSI)method is sensitive to characterize white matter damage and inflammation in central nervous system.In this study,we aim to apply DBSI to quantitatively assess white matter injury and coexisting inflammation in chronic TBI,and to compare the application value of DTI and DBSI measures in assessing white matter pathology.Methods:Eighteen chronic(range from 90 to 730 days post-injury)mild-to-severe TBI and twenty healthy controls were included.Siemens Trio Tim 3.0 Tesla was used to obtain high-resolution three dimensional T1-weighted imaging and DBSI.Neuropsychological tests were performed within 24 hours after MRI scanning,including the Glasgow Coma Scale(GCS)score,Mini-Mental State Examination(MMSE)and Beck's Depression Inventory(BDI).Preprocessing included correction for head movement and eddy current distortions by using FMRIB software library(FSL,www.fmrib.ox.ac.uk/fsl.version 4.19).DTI data were processed in FSL with DTI FIT,while DBSI metrics were processed and generated using in-house software scripted in MATLAB.Post-processing of DTI and DBSI was conducted with tractbased spatial statistics(TBSS).Demographic statistics between the TBI and healthy controls were compared,the threshold for statistical significance was set at p < 0.05.A voxel-wise analysis of both DBSI and DTI data was performed using a statistical package in FSL.Correlations between DTI/DBSI metrics and neuropsychological tests were then performed for TBI group.Results:1.Compared with healthy controls,TBI patients showed widespread WM abnormality evidenced by the various changes of diffusion MR metrics.Twenty-four WM showed significantly decreased DTI-FA among all the white matter tracts.The twenty-four WM tracts were then selected for further analyses.Our results showed that,DTI-AD decreased in right ALIC,right CP;DTI-RD increased in bilateral ACR,bilateral ALIC,bilateral EC,bilateral IFWM,left PCR,right CP,right SCR,right SFWM,right SOWM and entire CC;DBSI-FA decreased in bilateral ACR,bilateral ALIC,left PCR,right EC,right SFWM,right SOWM,right SPWM and GCC,suggesting white matter abnormality;DBSI-AD decreased in right ALIC and right CP,suggesting axonal injury;DBSI-RD increased in bilateral ACR,left PCR,right EC,right SFWM and GCC,suggesting demyelination;DBSI-fiber fraction decreased in bilateral ACR,bilateral IFWM,left CP,left STWM,right IOWM,right MOWM,right STWM and entire CC,suggesting axonal loss;DBSI-restricted fraction increased in left STWM,right CP,right MOWM and right SOWM,suggesting inflammatory cell infiltration;DBSI-hindered fraction increased in bilateral ACR,left IFWM,right IOWM,right MFWM,GCC and BCC,suggesting vasogenic edema.2.There's a significant correlation(| r | > 0.3,p < 0.05)between DTI-FA/DTIRD and neuropsychological tests in all the WM tracts,and a significant correlation(| r | > 0.3,p < 0.05)between DBSI-fiber fraction and neuropsychological tests in most of the WM tracts.Conclusion:1.Both DTI and DBSI could examine white matter abnormality in chronic TBI patients.2.DBSI technique is able to detect widespread inflammation in chronic TBI patients,including inflammatory cell infiltration and edema.3.DBSI metrics provide novel imaging biomarkers for examining various complicated pathology of white matter in chronic TBI.