Serum Metabolites Associated with Computed Tomography Findings after Traumatic Brain Injury.

There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of biomarkers to determine the need for CT and to distinguish among different types of injuries observed. Logistical regression models using metabolite data from the discovery cohort (n = 144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and those with negative findings on head CT. The resultant models were then tested in the validation cohort (n = 66, Cambridge, United Kingdom). The levels of glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein biomarkers in patients with TBI, the model that determined the need for a CT scan validated poorly (area under the curve [AUC] = 0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, three sugar derivatives, and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC = 0.77 in Turku patients and AUC = 0.73 in Cambridge patients). Further, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC = 0.87 in Turku patients and AUC = 0.68 in Cambridge patients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.

Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging.

Traumatic brain injury (TBI) is caused by a sudden external force and can be very heterogeneous in its manifestation. In this work, we analyse T1-weighted magnetic resonance (MR) brain images that were prospectively acquired from patients who sustained mild to severe TBI. We investigate the potential of a recently proposed automatic segmentation method to support the outcome prediction of TBI. Specifically, we extract meaningful cross-sectional and longitudinal measurements from acute- and chronic-phase MR images. We calculate regional volume and asymmetry features at the acute/subacute stage of the injury (median: 19 days after injury), to predict the disability outcome of 67 patients at the chronic disease stage (median: 229 days after injury). Our results indicate that small structural volumes in the acute stage (e.g. of the hippocampus, accumbens, amygdala) can be strong predictors for unfavourable disease outcome. Further, group differences in atrophy are investigated. We find that patients with unfavourable outcome show increased atrophy. Among patients with severe disability outcome we observed a significantly higher mean reduction of cerebral white matter (3.1%) as compared to patients with low disability outcome (0.7%).

High angular resolution diffusion-weighted imaging in mild traumatic brain injury.

We sought to investigate white matter abnormalities in mild traumatic brain injury (mTBI) using diffusion-weighted magnetic resonance imaging (DW-MRI). We applied a global approach based on tract-based spatial statistics skeleton as well as constrained spherical deconvolution tractography. DW-MRI was performed on 102 patients with mTBI within two months post-injury and 30 control subjects. A robust global approach considering only the voxels with a single-fiber configuration was used in addition to global analysis of the tract skeleton and probabilistic whole-brain tractography. In addition, we assessed whether the microstructural parameters correlated with age, time from injury, patient's outcome and white matter MRI hyperintensities. We found that whole-brain global approach restricted to single-fiber voxels showed significantly decreased fractional anisotropy (FA) (p = 0.002) and increased radial diffusivity (p = 0.011) in patients with mTBI compared with controls. The results restricted to single-fiber voxels were more significant and reproducible than those with the complete tract skeleton or the whole-brain tractography. FA correlated with patient outcomes, white matter hyperintensities and age. No correlation was observed between FA and time of scan post-injury. In conclusion, the global approach could be a promising imaging biomarker to detect white matter abnormalities following traumatic brain injury.

Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase-L1 Are Not Specific Biomarkers for Mild CT-Negative Traumatic Brain Injury.

Glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) have been studied as potential biomarkers of mild traumatic brain injury (mTBI). We report the levels of GFAP and UCH-L1 in patients with acute orthopedic injuries without central nervous system involvement, and relate them to the type of extracranial injury, head magnetic resonance imaging (MRI) findings, and levels of GFAP and UCH-L1 in patients with CT-negative mTBI. Serum UCH-L1 and GFAP were longitudinally measured from 73 patients with acute orthopedic injury on arrival and on days 1, 2, 3, 7 after admission, and on the follow-up visit 3-10 months after the injury. The injury types were recorded, and 71% patients underwent also head MRI. The results were compared with those found in patients with CT-negative mTBI (n = 93). The levels of GFAP were higher in patients with acute orthopedic trauma than in patients with CT-negative mTBI (p = 0.026) on arrival; however, no differences were found on the following days. The levels of UCH-L1 were not significantly different between these two groups at any measured point of time. Levels of GFAP and UCH-L1 were not able to distinguish patients with CT-negative mTBI from patients with orthopedic trauma. Patients with orthopedic trauma and high levels of UCH-L1 or GFAP values may be falsely diagnosed as having a concomitant mTBI, predisposing them to unwarranted diagnostics and unnecessary brain imaging. This casts a significant doubt on the diagnostic value of GFAP and UCH-L1 in cases with mTBI.

Human Serum Metabolites Associate With Severity and Patient Outcomes in Traumatic Brain Injury.

Traumatic brain injury (TBI) is a major cause of death and disability worldwide, especially in children and young adults. TBI is an example of a medical condition where there are still major lacks in diagnostics and outcome prediction. Here we apply comprehensive metabolic profiling of serum samples from TBI patients and controls in two independent cohorts. The discovery study included 144 TBI patients, with the samples taken at the time of hospitalization. The patients were diagnosed as severe (sTBI; n=22), moderate (moTBI; n=14) or mild TBI (mTBI; n=108) according to Glasgow Coma Scale. The control group (n=28) comprised of acute orthopedic non-brain injuries. The validation study included sTBI (n=23), moTBI (n=7), mTBI (n=37) patients and controls (n=27). We show that two medium-chain fatty acids (decanoic and octanoic acids) and sugar derivatives including 2,3-bisphosphoglyceric acid are strongly associated with severity of TBI, and most of them are also detected at high concentrations in brain microdialysates of TBI patients. Based on metabolite concentrations from TBI patients at the time of hospitalization, an algorithm was developed that accurately predicted the patient outcomes (AUC=0.84 in validation cohort). Addition of the metabolites to the established clinical model (CRASH), comprising clinical and computed tomography data, significantly improved prediction of patient outcomes. The identified 'TBI metabotype' in serum, that may be indicative of disrupted blood-brain barrier, of protective physiological response and altered metabolism due to head trauma, offers a new avenue for the development of diagnostic and prognostic markers of broad spectrum of TBIs.

Injury profiles, demography and representativeness of patients with TBI attending a regional emergency department.

OBJECTIVES: The aim of this study was to describe the demography and epidemiology of Finnish patients with TBI and to analyse the representativeness of a study sample. MATERIALS AND METHODS: This prospective multi-centre study was conducted as part of an international collaboration within the EU-funded TBIcare project. The study group was recruited from patients attending the regional emergency department (ED) of the Turku University Hospital, Finland. Pre-defined exclusion criteria included age < 18 years, more than 2 weeks from the injury and uncertain diagnosis of TBI. To be included, a need for an acute head CT (NICE-criteria) was required. RESULTS: Of the 620 patients with TBI or suspected TBI, 203 patients were recruited to the study. Falls were the most common injury mechanism. The study group included more males than the total eligible population (p = 0.011), but no other statistical differences were found. The most common cause for being excluded was lack of information available to the research group before discharge (34%). CONCLUSION: This study supports previous findings that falls are the most common injury mechanism in the Western countries. Uncertainty about the diagnosis of TBI, lack of representativeness without continuous recruitment and poor information transfer about the ED attendees are major challenges for prospective TBI studies.

The Levels of Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase-L1 During the First Week After a Traumatic Brain Injury: Correlations With Clinical and Imaging Findings.

BACKGROUND: Glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) are promising biomarkers of traumatic brain injury (TBI). OBJECTIVE: We investigated the relation of the GFAP and UCH-L1 levels to the severity of TBI during the first week after injury. METHODS: Plasma UCH-L1 and GFAP were measured from 324 consecutive patients with acute TBI and 81 control subject enrolled in a 2-center prospective study. The baseline measures included initial Glasgow Coma Scale (GCS), head computed tomographic (CT) scan at admission, and blood samples for protein biomarkers that were collected at admission and on days 1, 2, 3, and 7 after injury. RESULTS: Plasma levels of GFAP and UCH-L1 during the first 2 days after the injury strongly correlated with the initial severity of TBI as assessed with GCS. Additionally, levels of UCH-L1 on the seventh day after the injury were significantly related to the admission GCS scores. At admission, both biomarkers were capable of distinguishing mass lesions from diffuse injuries in CT, and the area under the curve of the receiver-operating characteristic curve for prediction of any pathological finding in CT was 0.739 (95% confidence interval, 0.636-0.815) and 0.621 (95% confidence interval, 0.517-0.713) for GFAP and UCH-L1, respectively. CONCLUSION: These results support the prior findings of the potential role of GFAP and UCH-L1 in acute-phase diagnostics of TBI. The novel finding is that levels of GFAP and UCH-L1 correlated with the initial severity of TBI during the first 2 days after the injury, thus enabling a window for TBI diagnostics with latency. ABBREVIATIONS: AUC, area under the curveCI, confidence intervalED, emergency departmentGCS, Glasgow Coma ScaleGRAP, glial fibrillary acidic proteinIMPACT, International Mission for Prognosis and Clinical TrialROC, receiver-operating characteristicTBI, traumatic brain injuryTRACK-TBI, Transforming Research and Clinical Knowledge in Traumatic Brain InjuryUCH-L1, ubiquitin C-terminal hydrolase-L1.

Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase-L1 as Outcome Predictors in Traumatic Brain Injury.

OBJECTIVE: Biomarkers ubiquitin C-terminal hydrolase-L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) may help detect brain injury, assess its severity, and improve outcome prediction. This study aimed to evaluate the prognostic value of these biomarkers during the first days after brain injury. METHODS: Serum UCH-L1 and GFAP were measured in 324 patients with traumatic brain injury (TBI) enrolled in a prospective study. The outcome was assessed using the Glasgow Outcome Scale (GOS) or the extended version, Glasgow Outcome Scale-Extended (GOSE). RESULTS: Patients with full recovery had lower UCH-L1 concentrations on the second day and patients with favorable outcome had lower UCH-L1 concentrations during the first 2 days compared with patients with incomplete recovery and unfavorable outcome. Patients with full recovery and favorable outcome had significantly lower GFAP concentrations in the first 2 days than patients with incomplete recovery or unfavorable outcome. There was a strong negative correlation between outcome and UCH-L1 in the first 3 days and GFAP levels in the first 2 days. On arrival, both UCH-L1 and GFAP distinguished patients with GOS score 1-3 from patients with GOS score 4-5, but not patients with GOSE score 8 from patients with GOSE score 1-7. For UCH-L1 and GFAP to predict unfavorable outcome (GOS score ≤ 3), the area under the receiver operating characteristic curve was 0.727, and 0.723, respectively. Neither UCHL-1 nor GFAP was independently able to predict the outcome when age, worst Glasgow Coma Scale score, pupil reactivity, Injury Severity Score, and Marshall score were added into the multivariate logistic regression model. CONCLUSIONS: GFAP and UCH-L1 are significantly associated with outcome, but they do not add predictive power to commonly used prognostic variables in a population of patients with TBI of varying severities.