search
for
 About Bioline  All Journals  Testimonials  Membership  News


Neurology India
Medknow Publications on behalf of the Neurological Society of India
ISSN: 0028-3886 EISSN: 1998-4022
Vol. 59, Num. 5, 2011, pp. 679-684

Neurology India, Vol. 59, No. 5, September-October, 2011, pp. 679-684

Original Article

1H-Magnetic resonance spectroscopy correlates with injury severity and can predict coma duration in patients following severe traumatic brain injury

Yanli Du1, Yu Li2, Qing Lan3

1 Department of Neurosurgery, Second Affiliated Hospital of Suzhou University, Jiangsu; Inner Mongolia General Forestry Hospital, Inner Mongolia, China
2 Department of Neurosurgery, Inner Mongolia General Forestry Hospital, Inner Mongolia, China
3 Department of Neurosurgery, Second Affiliated Hospital of Suzhou University, Jiangsu, China
Correspondence Address: Qing Lan, Department of Neurosurgery, Second Affiliated Hospital of Suzhou University, Jiangsu - 215 004, China, zzyyy@163.com

Date of Submission: 27-Apr-2011
Date of Decision: 29-May-2011
Date of Acceptance: 05-Sep-2011

Code Number: ni11210

PMID: 22019650

DOI: 10.4103/0028-3886.86540

Abstract

Background: Evaluation of the degree of severity of injury, coma duration, and prediction of outcome are integral parts of present-day management of severe traumatic brain injury (TBI).
Objective:
To investigate whether evaluation and prediction of outcome in early phase after severe TBI is possible by means of single-voxel proton magnetic resonance spectroscopy ( 1 H-MRS).
Materials and Methods:
Proton spectra were acquired from the posterior part of normal-appearing frontal lobes having predominantly white matter in 72 patients with severe TBI within a few days of trauma, mean 9.5 days and also in 30 controls.
Results: 1 H-MRS studies revealed lower ratios of N-acetylaspartate (NAA)/Choline (Cho) and NAA/ Creatine (Cr) and higher ratios of Cho/Cr in patients with TBI when compared to the control group. In patients with severe TBI, NAA/Cr, NAA/Cho and Cho/Cr ratios were significantly correlated with the initial Glasgow Coma Scale score (GCS) (P=0.004, r =0.439, P=0.018, r =0.364, P=0.004, r = -0.762, respectively), and with the clinical outcome, Glasgow Outcome Scores (GOS) (P=0.006, r =0.414; P=0.007, r =0.412; P=0.016, r = -0.775, respectively). An equation including clinical and spectroscopic variables, which can predict coma duration fairly accurately, was also obtained.
Conclusions: 1 H-MRS may be a novel method of assessing brain function, estimating coma duration, and predicting outcome in patients with severe TBI.

Keywords: Choline, creatinine, lactic acid spectroscopy, N-acetylaspartate, traumatic brain injury

Introduction

Traumatic brain injury (TBI) can be both focal and diffuse, [1],[2] not all of which can easily be visualized. Typically, focal injuries include contusions and hematomas, whereas diffuse injuries include diffuse axonal injury and diffuse microvascular damage. [3] Abnormalities detected by computed tomography (CT) scan or conventional magnetic resonance imaging (MRI) have limitations in classifying the degree of clinical severity and also in predicting outcomes. This can be explained by the widespread microscopic tissue damage occurring after trauma, which is not observable with the conventional structural imaging methods. Advances in neuroimaging over the past two decades have greatly helped in the clinical care and management of patients with TBI. Proton MR-spectroscopy ( 1 H-MRS) is a noninvasive approach that acquires metabolite information reflecting neuronal integrity and functions from multiple brain regions and allows assessment of clinical severity and also predicts disease outcome. [4],[5]

Evaluation of the degree of injury severity, coma duration, and prediction of outcome in severe TBI are integral parts of the present-day management of severe TBI. Efforts have been made to develop tools that aid in detecting injury severity and outcomes. The more commonly used indicators of the severity of TBI include Glasgow Coma Scale (GCS) scores, [6] duration of impaired consciousness and posttraumatic amnesia, [7] presence of nonreactive pupils, [8] and brain imaging techniques. [9] Unfortunately, these indicators of severity have not proved sufficiently accurate in predicting outcomes.

To date, the majority of studies on TBI using 1 H-MRS have been aimed at detecting group differences in NAA or in the ratio of total NAA signal to signal from other metabolites in the 1 H-MRS spectrum, such as Cho or Cr. [10],[11],[12],[13],[14],[15],[16] Few studies have been directed towards correlation between alteration in these neurometabolite concentrations and duration of post-injury coma (a measure of injury severity) as well as prediction of outcome in severe TBI. The aim of our study was to determine if there is a correlation between N-acetylaspartate (NAA)/Choline (Cho), NAA/ Creatine (Cr), and Cho/Cr with the degree of severity, GCS, [6],[17] or outcome, GOS. [18],[19] In addition, we sought to determine if we can obtain an equation to predict coma duration using clinical and spectroscopic values including NAA/Cr and GCS.

Materials and Methods

Patient population

We reviewed prospectively collected data on 80 patients with severe TBI admitted to our trauma centre. Inclusion criteria were age older than 18 years, admission within 6 h of injury, and GCS score ≤8. Patients were enrolled between September 2007 and December 2009 and TBI was verified by MRI. Exclusion criteria were preexisting conditions that might compromise cognitive functions, GCS score > >8, a body region other than brain with an Abbreviated Injury Severity score >3 (exclusion of significant systemic injuries), and a non-survivable brain injury. Of the 80 patients, conventional MRI and 1 H-MRS data were available for 72 (54 men, 18 women; age range: 17-66 years, mean age: 41.3 years). Causes of injury were: car accidents in 49, falls in 16 and physical trauma in 7.

Outcome measure included in-hospital mortality, discharge GCS, length of coma in the intensive care unit and length of hospital stay. GOSs were assessed at three months following TBI by a structured phone interview by an experienced trauma clinical research coordinator. Of the 72 patients, 8 patients had recovered or suffered minor disability; 38 patients had suffered moderate or severe disability; 14 were in a vegetative state; and 12 were dead.

Control group included 30 healthy subjects (22 males, 8 females, mean age of 40.2 years; range 25-62 years). The populations of the two cohorts were statistically comparable. This study had the approval of the Ethical Committee of Inner Mongolia General Forestry Hospital and written consent was obtained frompatients or next of kin.

Analysis

The Signa HDx 3.0T MRI scanner (GE Company, USA) was the scan used in this study and the scan data collected included T2WI (FSE), T2-FLAIR and T1-FLAIR. Injury position and properties were identified by conventional MRI. 1 H-MRS was performed at the earliest when patients were clinically stable, injury-to-scan-time: mean 9.5 days, range 1-16 days. 1 H-specta was acquired from the posterior aspect of one of the frontal lobes, containing predominantly white tracts. The voxel was carefully positioned to avoid any areas of T1 and T2 abnormality. Localization of the signal was performed using the stimulated echo acquisition mode (STEAM) sequence with a short TE and long TR (TE, 145 ms; TR, 1500 ms). A single-voxel acquisition (voxel size, 2×2×2 cm 3 ; number of acquisitions, 128; acquisition time, 228 s) was employed. The detailed procedure is given in [Table - 1]. Spectra data were auto-analyzed using the GE AWD 4.4 special magnetic resonance post-processing workstation-"Functool 2" software to automatically obtain the ratios of NAA/Cr, NAA/Cho and Cho/Cr. Image analyses were completed by two senior radiologists and two senior neurosurgeons.

Statistical methods

All values were expressed as mean ± SD. A P<0.05 was considered statistically significant. To test for differences in the values of spectrum between the control group and severe TBI group, analysis of variance (ANOVA) test was used. Linear regression was applied to correlate the GCS and GOS scores with the metabolite ratios. Forward stepwise regression (with α= 0.10) analysis was used to establish a model of coma duration prediction. Data were analyzed using the SPSS 11.5 statistical package. The statistician was blind to the two cohorts.

Results

Spectrum data

An example of a data set from a control subject, together with the early data from a patient, is shown in [Figure - 1]. The patient, a 61-year-old male, who was involved in a car accident with a GCS score of 5 following resuscitation, was studied on Day 14 of injury. The spectra obtained showed a reduced NAA/Cr and NAA/Cho, increased Cho/Cr in the patient when compared with the control.

The metabolite ratios (NAA/Cr, NAA/Cho, Cho/Cr) of the 30 controls and 72 patients (mean 9.5 days) are shown in [Table - 2]. NAA/Cr and NAA/Cho were significantly reduced and the Cho/Cr was significantly increased in the patients when compared with the controls.

Correlation of neurometabolite concentrations with GCS and GOS

Using Spearman linear regression analysis, NAA/Cr, NAA/Cho, Cho/Cr ratios were significantly correlated with changes in GCS (P =0.004, r =0.439; P =0.018, r =0.364; P =0.004, r = -0.762, respectively [Figure - 2] and with clinical outcome of the patients (GOS), P =0.006, r =0.414; P =0.007, r =0.412; P =0.016, r = -0.775, respectively. In addition, four patients with severe TBI had high lactate peaks and they were either in a vegetative state or dead.

Application of 1 H-MRS in predicting coma duration in patients with severe TBI

A base model using stepwise regression, with α (size of test) = 0.10, was constructed to predict the duration of coma using patient age and initial GCS scores as increasing age and decreasing GCS are associated with worse outcome following TBI in terms of mortality and functional outcomes. [6],[8],[20],[21] Different variables were then tested with the base model, separately and in combination, to develop a model with the highest predictive accuracy (evidenced statistically by Adjusted R Square). The results for significant variables are given in [Table - 3]. Finally we decided to use the indices including age (X1, years), GCS score (X2), conditions of pupils (X3, 1 = not in equal diameter, 0=in equal diameter), number of foci (X4), NAA/Cr value (X5), and coma duration (days). The total duration of coma in all the 72 patients were also recorded. An equation of coma duration was modeled (F = 69.00, p ≈ 0), Y =predicted coma duration. In (y) = In10 (1.027 + 0.004595 (age) - 0.0755 (GCS) - 0.0987 (conditions of pupils) + 0.04518 (number of foci) + 0.527/ (NAA /Cr))

We used an exponential function to normalize the coma duration (range from 4.8 to 22.5 days), because initial results of Y were skewed in distribution (data not shown). The result indicated a negative correlation (r = -0.651, P < 0.0001) between NAA/Cr values and predicted coma duration in the patients. The result showed that the average of time error was 1.47 d, which was acceptable. Among 26 patients who were in a vegetative state or dead (see "patient population" above), the predicted time was all above 19 days. Subsequently, 20 patients of the 72 patients with severe TBI were selected randomly. Their predicted coma duration and actual time for each of them are shown in [Figure - 3].

Discussion

Being rapid, sensitive and non-invasive, the 1 H-MRS technique can identify and quantify the biochemical compounds and explore metabolic and biochemical changes in TBI. Peaks in Cho, Cr, NAA, lactate, glucose, myo-Inositol (MI) and other substances appear in the proton spectrum. Because NAA is produced in neuronal mitochondria and adenosine triphosphate is required for synthesis, mitochondrial dysfunction may contribute to the temporary reduction in NAA levels seen in TBI. [18],[22],[23] It has been postulated that a temporary decrease in NAA levels after brain injury may be caused by accelerated lipid synthesis involved in myelin repair or may be attributable to NAA providing a temporary source of cellular energy locally at the site of axonal injury, which would produce a transient decrease that might precede any loss of NAA as a result of axonal death. [24] Thus, NAA measurements may serve as a sensitive specific biomarker of neuronal injury, dysfunction, loss, or repair. [25],[26],[27] As a choline derivative, the spikes of Cho are composed of several compounds, mainly free choline, choline glycerophosphatide and phosphocholine. [28] The synthesis and decomposition of Cho cause cytoplasmic membrane metabolic changes. Cho increases indicate incision injury of the myelin sheath and cytoplasmic membrane rupture. Lactate due to impaired aerobic glycolysis is a specific marker for post-traumatic secondary hypoxic and ischemic injury. [29] Several studies have shown that an increase in lactate in the normal-appearing white matter area of patients with severe TBI could suggest poor prognosis (death or severe disability) after post-traumatic secondary ischemic and hypoxic injury. [25],[29],[30] Lactate presence has been related to multiple factors, including excessive release of glutamate, disordered mitochondrial and oxidative metabolism, and systemic responses to trauma. [31],[32],[33],[34] In our study, lactate peaks appeared in four patients with severe TBI with GOS either vegetative state or death. It has been demonstrated that increase in lactate concentrations indicates poor prognosis in patients with severe TBI.

At early points (mean=9.5 days), we found that NAA/Cr, NAA/Cho were significantly reduced (P < 0.05, P < 0.01, respectively), and Cho/Cr significantly increased (P < 0.05). We conclude that there is a sustained alteration in NAA, Cho, and Cr. Similar findings have been reported by two other MRS studies in TBI, which focused on metabolite ratios rather than absolute concentration levels. Govindaraju and colleagues [13] assessed ratio scores (NAA/Cr and NAA/Cho) from 25 single predominantly gray- or white-matter voxels, and reported that both ratios were reduced in TBI patients for two of the white-matter voxels. Similarly, Vagnozzi and associates [16] recently reported reduced NAA/Cr in TBI patients in anterior periventricular white matter. Significant differences were observed between severe TBI patients and matched controls for several 1 H-MRS metabolites, indicating that sensitivity of 1 H-MRS to metabolite alterations might serve as biomarkers of severe TBI.

We have found that not only did the ratios of NAA/Cr, NAA/Cho, and Cho/Cr significantly correlate with changes in GCS but they also correlated with the clinical outcome, GOS at three months follow-up, indicating that 1 H-MRS could reflect the degree of nerve tissue injury objectively and is a reliable and innovative means to evaluate the trauma levels and prognosis of TBI patients. These findings provide evidence for cellular injury not visible by conventional techniques. This may be relevant to understanding the extent of disability following TBI.

At present, the predictions of coma duration in patients with severe TBI patients are difficult to quantify. Benson et al., [35] found that the fractional anisotropy (FA) value of the whole white matter decreases after TBI and it was closely related to the GCS (r = 0.47) and post-traumatic coma duration (r = 0.64). Other studies proved that poor outcome can be predicted by GCS, status of pupils [8] and number of foci. [36] NAA /Cr contributed significantly to outcome prediction, more than the other metabolite ratios. [25]

Our next analyses evaluated whether such clinical and spectroscopic variables discussed above would predict the coma duration. Using stepwise regression analysis we found that a combination of age, clinical variables, and metabolite data was most accurate in predicting coma duration. The age and GCS score alone were not quite good at predicting the duration. The addition of brain metabolite data, particularly the NAA/Cr ratio, improved our ability to predict the duration of post-injury coma. We also tried to include injury-to-scan-time as a variable in the modeling, because neurochemicals seen on the MRS vary, especially in the first few weeks of injury. It is also likely that time-to-scan is related to the severity of the injury. But it seemed that adding the time impaired our ability of prediction.

It remains, however, that MRS scanning in TBI patients involves a number of technical restrictions, including the need for non-magnetic equipment, positioning tolerance of patient with regard to intracranial pressure, and the complexity of patient transportation. Although the equation was fairly accurate, this sample was small, and thus our findings need to be replicated in a large independent sample. In addition, the optimal time for 1 H-MRS examination and the best region of interest are still not clear for TBI patients.

In conclusion, areas of frontal white matter, which appear normal on conventional MRI, show significant 1 H-MRS abnormalities flowing TBI. These abnormalities have a significant correlation with the injury degree severity and clinical outcome. Thus 1 H-MRS helps in proper stratification of TBI patients and allocation of scarce resources in the overall planning of care.

Acknowledgments

The authors are grateful to M.D Zhao Yu and Wang Bin for their help and support. This work was supported by the Natural Science Foundation of Inner Mongolia, China (2010MS1137).

References

1.Bigler ED. The lesion(s) in traumatic brain injury: Implications for clinical neuropsychology. Arch Clin Neuropsychol 2001;16:95-131.  Back to cited text no. 1    
2.Graham DI, Adams JH, Nicoll JA, Maxwell WL, Gennarelli TA. The nature, distribution and causes of traumatic brain injury. Brain Pathol 1995;5:397-406.  Back to cited text no. 2    
3.Povlishock JT, Katz DI. Update of neuropathology and neurological recovery after traumatic brain injury. J Head Trauma Rehabil 2005;20:76-94.  Back to cited text no. 3    
4.Ashwal S, Holshouser BA, Tong KA. Use of advanced neuroimaging techniques in the evaluation of pediatric traumatic brain injury. Dev Neurosci 2006;28:309-26.  Back to cited text no. 4    
5.Suskauer SJ, Huisman TA. Neuroimaging in pediatric traumatic brain injury: Current and future predictors of functional outcome. Dev Disabil Res Rev 2009;15:117-23.  Back to cited text no. 5    
6.Jennett B, Bond M. Assessment of outcome after severe brain damage. Lancet 1975;1:480-4.  Back to cited text no. 6    
7.Broman SH, Michel ME. Traumatic Head Injury in Children. New York, NY: Oxford University Press; 1995.  Back to cited text no. 7    
8.Levin HS, Aldrich EF, Saydjari C, Eisenberg HM, Foulkes MA, Bellefleur M, et al. Severe head injury in children: experience of the Traumatic Coma Data Bank. Neurosurgery 1992;31:435-443.  Back to cited text no. 8    
9.van der Naalt J, Hew JM, van Zomeren AH, Sluiter WJ, Minderhoud JM. Computed tomography and magnetic resonance imaging in mild to moderate head injury: early and late imaging related to outcome. Ann Neurol 1999;46:70-8.  Back to cited text no. 9    
10.Babikian T, Freier MC, Ashwal S, Riggs ML, Burley T, Holshouser BA. MR spectroscopy: Predictinglong-term neuropsychological outcome following pediatric TBI. J Magn Reson Imaging 2006;24:801-11.  Back to cited text no. 10    
11.Cimatti M. Assessment of metabolic cerebral damage using proton magnetic resonance spectroscopy in mild traumatic brain injury. J Neurosurg Sci 2006;50:83-8.  Back to cited text no. 11    
12.Cohen BA, Inglese M, Rusinek H, Babb JS, Grossman RI, Gonen O. Proton MR spectroscopy and MRI volumetry in mild traumatic brain injury. Am J Neuroradiol 2007;28:907-13.  Back to cited text no. 12    
13.Govindaraju V, Gauger GE, Manley GT, Ebel A, Meeker M, Maudsley AA. Volumetric proton spectroscopic imaging of mild traumatic brain injury. Am J Neuroradiol 2004;25:730-7.  Back to cited text no. 13    
14.Kirov I, Fleysher L, Babb JS, Silver JM, Grossman RI, Gonen O. Characterizing ''mild'' in traumatic brain injury with proton MR spectroscopy in the thalamus: Initial findings. Brain Inj 2007;21:1147-54.  Back to cited text no. 14    
15.Tavazzi B, Vagnozzi R, Signoretti S, Amorini AM, Belli A, Cimatti M, et al. Temporal window of metabolic brain vulnerability to concussions: Oxidative and nitrosative stresses-part II. Neurosurgery 2007;61:390-5; discussion 395-6.  Back to cited text no. 15    
16.Vagnozzi R, Signoretti S, Tavazzi B, Floris R, Ludovici A, Marziali S, et al. Temporal window of metabolic brain vulnerability to concussion: A pilot 1h-magnetic resonance spectroscopic study in concussed athletes-Part III. Neurosurgery 2008;62:1286-95; discussion 1295-86.  Back to cited text no. 16    
17.Jennett B. The history of Glasgow coma scale: An interview with Professor Bryan Jennett. Interview by Carole Rush. Int J Trauma Nurs 1977;3:114-8.  Back to cited text no. 17    
18.Teasdale G, Jennett B. Assessment of coma and impaired consciousness: A practical scale. Lancet 1974;2:81-4.  Back to cited text no. 18    
19.Wilson JT, Wiedmann KD, Hadley DM, Condon B, Teasdale G, Brooks DN. Early and late magnetic resonance imaging and neuropsychological outcome after head injury. J Nerurol Neurosurg Psychiatry 1988;51:391-6.  Back to cited text no. 19    
20.Hukkelhoven CW, Steyerberg EW, Rampen AJ, Farace E ,Habbema JD, Marshall LF, et al. Patient age and outcome following severe traumaticbrain injury: an analysis of 5600 patients. J Neurosurg 2003;99:666-73.  Back to cited text no. 20    
21.Schönberger M, Ponsford J, Reutens D, Beare R, O'Sullivan R. The Relationship between age, injury severity, and MRI findings after traumatic brain injury. J Neurotrauma 2009;26:2157-67.  Back to cited text no. 21    
22.Demougeot C, Garnier P, Mossiat C, Bertrand N, Giroud M, Beley A, et al. N-Acetylaspartate, a marker of both cellular dysfunction and neuronal loss: its relevance to studies of acute brain injury. J Neurochem 2001;77:408-15.  Back to cited text no. 22    
23.Clark JB. N-Acetyl aspartate: A marker for neuronal loss or mitochondrial dysfunction. Dev Neurosci 1998;20:271-6.  Back to cited text no. 23    
24.Cecil KM, Hills EC, Sandel ME, Smith DH, McIntosh TK, Mannon LJ, et al. Proton magnetic resonance spectroscopy for detection of axonal injury in the splenium of the corpus callosum of brain-injured patients. J Neurosurg 1998;88:795-801.  Back to cited text no. 24    
25.Aaen GS, Holshouser BA, Sheridan C, Colbert C, McKenney M, Kido D, et al. Magnetic resonance spectroscopy predicts outcomes for children with nonaccidental trauma. Pediatrics 2010;125:295-303.  Back to cited text no. 25    
26.Garnett MR, Blamire AM, Rajagopalan B, Styles P, Cadoux-Hudson TA. Evidence for cellular damage in normal appearing white matter correlate with injury severity in patients following traumatic brain injury: A magnetic resonance spectroscopy study. Brain 2000;123:1403-9.  Back to cited text no. 26    
27.Baslow M. N-acetylaspartate in the vertebrate brain: metabolism and function. Neurochem Res 2003;28:941-53.  Back to cited text no. 27    
28.Brooks WM, Friedman SD, Gasparovic C. Magnetic resonance spectroscopy in traumatic brain injury. J Head Trauma Rehabil 2001;16:149-64.  Back to cited text no. 28    
29.Signoretti S, Marmarou A, Fatouros P, Hoyle R, Beaumont A, Sawauchi S, et al. Application of chemical shift imaging for measurement of NAA in head injured patients. Acta Neuochir Suppl 2002;81:373-5.  Back to cited text no. 29    
30.Holshouser BA, Tong KA, Ashwal S. Proton MR spectroscopic imaging depicts diffuse axonal injury in children with traumatic brain injury. AJNR Am J Neuroradiol 2005;26:1276-85.  Back to cited text no. 30    
31.Krishnappa IK, Contant CF, Robertson CS. Regional changes in cerebral extracellular glucose and lactate concentrations following severe cortical impact injury and secondary ischemia in rats. J Neurotrauma 1999;16:213-24.  Back to cited text no. 31    
32.Hovda DA, Becker DP, Katayama Y. Secondary injury and acidosis. J Neurotrauma1992;9(suppl 1):S47-60.  Back to cited text no. 32    
33.Prasad MR, Ramaiah C, McIntosh TK, Dempsey RJ, Hipkens S, Yurek D. Regional levels of lactate and norepinephrine after experimental brain injury. J Neurochem 1994;63:1086-94.  Back to cited text no. 33    
34.Kawamata T, Katayama Y, Hovda DA, Yoshino A, Becker DP. Lactate accumulation following concussive brain injury: the role of ionic fluxes induced by excitatory amino acids. Brain Res 1995;674:196-2.  Back to cited text no. 34    
35.Benson RR, Coplin W, Govindarajan KA, Meda SA, Vasudevan S, Kou Z, et al. Global white matter analysis of diffusion tensor images is predictive of injury severity in traumatic brain injury. J Neurotrauma 2007;24:446-59.  Back to cited text no. 35    
36.Rosa CM, Luigi B, Antonio D, Nicoletta A, Gloria L, Marco G. Early prognosis after severe traumatic brain injury with minor or absent computed tomography scan lesions. J Trauma 2011;70:447-51.  Back to cited text no. 36    

Copyright 2011 - Neurology India


The following images related to this document are available:

Photo images

[ni11210t3.jpg] [ni11210f1.jpg] [ni11210t1.jpg] [ni11210t2.jpg] [ni11210f3.jpg] [ni11210f2.jpg]
Home Faq Resources Email Bioline
© Bioline International, 1989 - 2024, Site last up-dated on 01-Sep-2022.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Google Cloud Platform, GCP, Brazil