The oxidative stress is believed to be one of the mechanisms involved in the neuronal damage after acute traumatic brain injury (TBI). However, the disease severity correlation between oxidative stress biomarker level and deep brain microstructural changes in acute TBI remains unknown. In present study, twenty-four patients with acute TBI and 24 healthy volunteers underwent DTI. The peripheral blood oxidative biomarkers, like serum thiol and thiobarbituric acid-reactive substances (TBARS) concentrations, were also obtained. The DTI metrics of the deep brain regions, as well as the fractional anisotropy (FA) and apparent diffusion coefficient, were measured and correlated with disease severity, serum thiol, and TBARS levels. We found that patients with TBI displayed lower FAs in deep brain regions with abundant WMs and further correlated with increased serum TBARS level. Our study has shown a level of anatomic detail to the relationship between white matter (WM) damage and increased systemic oxidative stress in TBI which suggests common inflammatory processes that covary in both the peripheral and central reactions after TBI.
Approximately 1.4 million people sustain traumatic brain injury (TBI) in the United States every year [
Lipid peroxidation and inflammatory processes have been shown to increase blood-brain barrier permeability. As an immediate response, vasogenic and cytotoxic edema develop within the first hour after TBI. Thiobarbituric acid reactive species (TBARS) is widely adapted as a sensitive method for measuring lipid peroxidation [
Diffuse axonal injury (DAI) and cortical contusions constitute the vast majority of primary intra-axial lesions in cases of TBI and are associated with significant morbidity. During TBI, the subcortical white matter, internal capsule, corpus callosum, fornix, and infratentorial white matter (brain stem and cerebellum) are the most common predicted regions of brain injury [
To date, the relations of a panel of inflammatory markers and MRI DTI findings in acute TBI patients have not been examined. Under the hypothesis that increased systemic inflammatory biomarkers are associated with loss of anatomic integrity, this study measured DTI metrics at the deep brain regions in TBI patients to evaluate their correlation with serum inflammatory biochemical marker levels.
Sixty-three patients who sustained TBI between June and December 2012 and admitted at Kaohsiung Chang Gung Memorial Hospital were enrolled. The diagnosis of acute TBI was confirmed by history and brain CT scans. All of the patients underwent brain CT scan shortly after arriving at the emergency room. Repeat brain CT scan or/and MRI were performed for any clinical deterioration (e.g., acute-onset focal neurologic deficits, seizures, status epilepticus, and progressively disturbed consciousness) and as routine postneurosurgical procedure. After complete neurologic examination and history taking, the patients were under continuous observation and monitored regularly for Glasgow Coma Scale (GCS) Score, electrocardiogram, blood pressure, pulse rate, temperature, fluid balance, and laboratory parameters.
On initial CT study, patients with massive epidural/subdural hemorrhage that could distort the brain tissue or with any parenchymal lesion that might affect diffusion tensor MRI results were excluded. Those with the following were also excluded: (1) age < 20 years; (2) under medication with antiplatelet or anticoagulant drugs before the acute TBI; (3) having evidence of alcoholism, any other addictive disorders, or known affective or other psychiatric diseases than those caused by sedatives or neuroleptics; (4) having known neurologic disorders potentially affecting the central nervous system; and (5) having major systemic diseases like end-stage renal disease, liver cirrhosis, or congestive heart failure.
Among the 63 patients, 25 had at least one of massive epidural hematoma (EDH), subdural hematoma (SDH), or subarachnoid hematoma (SAH) that caused anatomical structure distortions, while 11 had minor EDH, SDH, or SAH but combined with parenchymal contusion hematoma. Two patients were excluded due to alcoholism and one for age < 20 years. Twenty-four patients with TBI were finally included in this study. For diffusion tensor MRI and biomarker comparison, 24 age- and sex-matched healthy volunteers were also enrolled. The Ethics Committee of the hospital’s Institutional Review Board approved the study and all participants provided written informed consent.
All subjects received blood sampling in day one after TBI (for the patients) or when normal controls were enrolled in the study. Sera were isolated from peripheral blood samples drawn from each subject before and after the expedition. Blood samples were centrifuged at 3000 rpm for 10 minutes. Each serum sample was collected and frozen at −80°C prior to biochemical measurements.
Thiobarbituric acid-reactive substances (TBARS) was measured based on a well-established method for detecting lipid peroxidation [
The ability of antioxidative defense in response to increased oxidative damage was evaluated by measuring the serum level of total reduced thiols since serum thiols were physiologic free radical scavengers. Serum total protein thiols were estimated by directly reacting thiols with 5,5-dithiobis 2-nitrobenzoic acid (DTNB) to form 5-thio-2-nitrobenzoic acid (TNB). The amount of thiols in the sample was calculated from the absorbance determined using the extinction coefficient of TNB (A412 = 13,600 M−1 cm−1).
MRI was performed in all subjects in the same day of blood sampling. Subjects were examined for DTI study in day one after TBI (for the patients) or when normal controls were enrolled in this study. The DTI datasets were acquired by using single-shot diffusion spin-echo, echo-planar imaging with a TR/TE of 15 800 millisecond/minimum, a 2.5 mm section, a matrix of 128 × 128, number of excitations of 3, and an FOV of 25.6 × 25.6 cm, yielding an in-plane resolution of 2 mm, with a total acquisition time of 12 min. The DTI encoding entailed 13 noncollinear directions, with
The DTI sets were transferred to an offline workstation for further analysis using the FuncTool diffusion tensor protocol (Advanced Workstation 4.2; GE Healthcare), which contained a preprocessing function to remove echo-planar imaging distortions like scaling, shearing, and translation due to eddy current effects from a diffusion gradient. The distortion-corrected data were then interpolated to attain isotropic voxels and decoded to obtain the tensor field for each voxel. The algorithm computed the 6 coefficients of the diffusion tensor for each pixel location. The tensor field data was then used to compute the DTI metrics, including the mean diffusivity (ADC) and FA for each voxel.
Regions of interest, 50–100 mm2 depending on the anatomic region, were measured by a radiologist and confirmed by another radiologist to avoid malpositioning (Figure
Regions of interest were placed on the (a) caudate, putamen, and globus pallidum; (b) the anterior and the posterior limbs of the internal capsule, thalamus; (c) cerebral peduncles, superior cerebellar peduncles; (d) middle cerebellar peduncles, pontine crossing tract, and medial lemniscus; (e) the genu, body, and splenium of corpus callosum.
The first level of the region of interest was selected at the foramen of Monro. At this level, regions of interest at the caudate, putamen, globus pallidum, and thalamus were measured on two continuous sections (Figures
The second level was selected at the inferior colliculus and the regions of interest at the cerebral peduncle and superior cerebellar peduncle and measured on two continuous sections (Figure
The Statistics Package for Social Science, Version 17.0 (SPSS Inc, Chicago, IL, USA) software, was used to perform all statistical analyses. The Student’s
The MANCOVA model with age and sex as covariates was also used to investigate differences in the diffusivity indices of the regions of interest between the two groups. Post-hoc tests with Bonferroni’s correction were performed for multiple comparisons. The DTI indices between the two groups were significant when
To access the correlation between serum oxidative stress factors and DTI-related indices for the regions of interest, Pearson’s partial correlation analysis with age and sex as confounding covariates was performed. To further investigate the relationships among TBI severity, serum oxidative stress factors, and DTI-related indices for regions of interest, the patients were graded based on their GCS, with a GCS > 12 as grade 1, GCS 9–12 as grade 2, and GCS < 9 as grade 3. Pearson’s partial correlation analysis with age and sex as confounding covariates was again performed. Statistical significance was set at
The demographic and clinical information were listed in Table
Demographic data of patients with traumatic brain injury (TBI) and healthy controls.
Patients with TBI | Normal controls |
|
| |
---|---|---|---|---|
Numbers | 24 | 24 | ||
Sex (male/female) | 11/13 | 12/12 | 1.000 | |
Age (age) | 42.79 ± 15.56 | 42.67 ± 12.68 | 2.003 | 0.164 |
Serum thiol concentration | 1.63 ± 0.27 | 1.45 ± 0.35 | 4.065 | 0.050 |
Serum TBARS concentration | 18.24 ± 13.70 | 10.66 ± 3.244 | 6.558 | 0.014* |
Initial Glasgow Coma Scale | 13.74 ± 3.02 | |||
Motor deficit | 3 (12.5%) | |||
Posttraumatic amnesia | 5 (20.8%) | |||
Seizure | 0 (0%) | |||
Brief unconsciousness | 7 (29.2%) | |||
Depressed skull fracture | 0 (0%) | |||
Pneumocranium | 4 (16.7%) | |||
Traumatic subarachnoid hemorrhage | 12 (50%) | |||
Subdural hematoma | 12 (50%) | |||
Epidural hematoma | 5 (20.8%) | |||
Parenchymal contusion hematoma | 0 (0%) | |||
Operation | 2 (8.3%) | |||
Ventriculostomy | 2 (8.3%) | |||
Craniectomy | 0 (0%) | |||
Craniotomy | 2 (8.3%) | |||
Days of total hospitalization | 11.70 ± 7.95 | |||
Days of intensive care unit | 3.87 ± 4.51 | |||
Newly onset of neurological deficit | 1 (4.2%) | |||
Deterioration of consciousness | 2 (8.3%) |
Data are demonstrated as means ± standard deviation.
*Significant differences (
The initial clinical symptoms of the patients with TBI were motor deficit (
There were significant differences in oxidative stress factors, including serum thiol and TBARS concentrations, between the two groups. The serum TBARS concentration of patients with TBI was significantly higher than those of the controls (
The FAs were significantly reduced in patients with TBI compared to those of the controls in the anterior limbs of the bilateral internal capsule, bilateral superior cerebellar peduncles, and left cerebral peduncle (Figure
The (a) FAs and (b) ADC of patients compared to the healthy controls. The al-IC and pl-IC represent the anterior and posterior limbs of the internal capsule, respectively, while the gCC, bCC, and sCC represent the genu, body, and splenium of the corpus callosum. The attached R/L represents the right/left side. *Significant difference between the patients and controls (
There was significant correlation between serum TBARS concentration and the FAs of DTI (Figure
Increased serum TBARS concentration correlated with the decreased FAs in the (a) left (
This is the first study to show correlations between serum inflammatory markers and changes of DTI metrics in patients with TBI using DTI metrics. There is a higher systemic TBAR level in patients with TBI than in healthy controls. The study also confirms the hypothesis that anatomic integrity subsequently decreases in the acute phase of the disease, even without visible injury on conventional imaging studies, and that serum TBAR values can predict the degree of DTI metrics degradation in TBI.
After the initial injury in TBI, neuronal damage or death produce proinflammatory substances and generate free radicals [
Similar to other antioxidant biomarkers like ascorbic acid,
Another important finding is the changes of microstructure integrity in the deep brain WM after TBI. By quantification of tissue water diffusion [
In present study, we did not found significant DTI metrics change in gray matter. Differences in GM and WM diffusion after TBI could be due to variability between these two tissue types at any stage in the process that leads from injury to altered diffusion. Gray matter has been traditionally considered to be more vulnerable than white matter to ischemia [
The most important finding in the present study is the bridge between central white matter injury and systemic inflammation after TBI. Although the true pathophysiologic mechanism is unclear, several explanations may be posited. Animal model studies and substantial clinical data suggest that blood-brain barrier breakdown frequently follows head trauma [
In contrast, leukocyte infiltration from serum into the CNS after breakdown of the blood-brain barrier can further damage neurons by releasing cytotoxic substances [
Unfortunately, neither increased TBARS nor decreased WM integrity correlate with disease severity in the present study. The study cohort is predominantly lesser affected patients, and thus the proteins may be less or have insignificant response after injury. The relatively small number of subjects in a cross-sectional study may also alter the interpretation. Although DTI is well suited for evaluating WM integrity, whether demyelination, axonal injury, or both lead to lower FA values in the present study remains unclear. Further studies with more diffusivity parameters analyses, such as radial diffusivity or axial diffusivity in diffusion tensor ellipsoid model, are needed. A longitudinal study of the present cohort may yield different relations between TBI and inflammatory markers that are more consistent with previous findings.
In conclusion, increased TBARS level and decreased WM integrity in vulnerable brain areas are found in patients with TBI. Possible interactions between peripheral inflammation and CNS microstructural damage likely represent the acute pathologic processes in TBI.
The authors do not have any actual or potential conflict of interests including any financial, personal, or other relationships with other people or organizations within three years of beginning the submitted work that could inappropriately influence or be perceived to influence their work.
Drs. Wei-Ming Lin and Meng-Hsiang Chen contributed equally to this work and shared the role of first author.
The authors acknowledge MR support from the MRI Core Facility, CGMH. The authors also thank Tsui-Min Chiu, YiFang Chaing, Yi-Wen Chen, and all subjects who participated in this study.