Tilburg University
Traumatic axonal injury
van Eijck, M.M.
Publication date:
2020
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van Eijck, M. M. (2020). Traumatic axonal injury: A study on prognostic factors. Ridderprint.
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Traumatic Axonal Injury:
A study on prognostic factors
Marleen M. van Eijck
Traumatic Axonal Injury
A study on prognostic factors
Traumatic Axonal Injury: a study on prognostic factors
© 2020 Marleen Maria van Eijck, The Netherlands. All rights reserved. No parts of this thesis may be reproduced, stored in a retrieval system or transmitted in any form or by any means without permission of the author. Alle rechten voorbehouden. Niets uit deze uitgave mag worden vermenigvuldigd, in enige vorm of op enige wijze, zonder voorafgaande schriftelijke toestemming van de auteur.
ISBN: 978-94-6375-927-4
Cover design & lay-out: Mirelle van Tulder, persoonlijkproefschrift.nl
Printing: Ridderprint | www.ridderprint.nl
Traumatic Axonal Injury:
a study on prognostic factors
Proefschrift ter verkrijging van de graad van doctor aan Tilburg University
op gezag van rector magnificus, prof. dr. K. Sijtsma, in het openbaar te verdedigen ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit
op vrijdag 30 oktober 2020 om 13.30 uur
CONTENTS
Chapter 1 General introduction and outline 7
Chapter 2 Prognosis in patients with Traumatic Brain Injury and Diffuse
Axonal Injury: A systematic review of the literature
Brain Injury 2018;32(4):395-402
19
Chapter 3 Patients with diffuse axonal injury can recover to a favourable
long-term functional and quality of life outcome
Journal of Neurotrauma 2018;35(20):2357-2364
53
Chapter 4 The use of the PSH-AM in patients with diffuse axonal injury
and autonomic dysregulation: A cohort study and review
Journal of Critical Care 49 (2019) 110-117
75
Chapter 5 Accuracy in prediction of long-term functional outcome in
patients with traumatic axonal injury: Comparison of MRI scales
Brain Injury 2020;34(5):595-601
115
Chapter 6 Lower fractional anisotropy in patients with traumatic axonal injury
is related to poor outcome, but not to conventional MRI grading
American Journal of Neuroradiology, Submitted
137
Chapter 7 Emotion recognition in patients with traumatic axonal injury is
positively related to health related quality of life
Quality of Life Research, Submitted
163
Chapter 8 General discussion 181
Summary of the main findings Nederlandse samenvatting List of abbreviations Dankwoord Curriculum vitae List of publications 193 198 202 204 208 210 Promotor: Prof. dr. J. de Vries
Tilburg University ETZ Tilburg
Copromotores: Dr. C.M.A.A. Roks
ETZ Tilburg
Dr. G.G. Schoonman
ETZ Tilburg
Promotiecommissie: Prof. dr. J.M.A. Visser-Meily
University Medical Center Utrecht
Prof. dr. J.A. Roukema
Tilburg University
Prof. dr. A.J.C. Slooter
University Medical Center Utrecht
Prof. dr. L.H. Visser
ETZ Tilburg
University of Humanistic Studies Utrecht
Dr. B. Jacobs
Chapter 1
8
9
Chapter 1 General introduction
Traumatic brain injury
Traumatic brain injury (TBI) refers to injuries sustained in the brain after blunt, penetrating, or sharp trauma. A concussion, contusion, subdural hematoma, traumatic subarachnoid hemorrhage, epidural hematoma, and axonal injury are all different types of TBI. These lesions can each appear isolated, but often a combination of lesions is seen in a single patient.1,2 TBI is a big problem in the Western world. Large numbers of patients suffer from TBI and related costs are significant. In The Netherlands, about 4% of the injury related Emergency Department (ED) visits are due to TBI. The incidence of TBI is higher in males (67%) and mostly caused by an incidental fall (46.1%). In 27.8% of the cases the patient is >65 years old.3 The total costs for TBI in The Netherlands is estimated €314.6 million per year, this includes direct costs such as healthcare costs and indirect costs like lost labour.4
Axonal injury DAI and TAI
TBI is divided into three groups; mild, moderate, and severe. This division is based on the Glasgow Coma Scale (GCS) in the (sub)acute phase after trauma.3 Axonal injury is mostly seen in patients with moderate to severe TBI, but also occurs in patients with mild TBI.2,5,6 Axonal injury is mostly seen after high-energy level trauma, such as road traffic accidents and falls from height.2 In these types of trauma, acceleration and deceleration forces can cause shear injury of axons.7-9 In the brain, the cell body of the neuron lies in the more dense grey matter and the axon in the white matter with a lower density. Due to the difference in density between grey and white matter, acceleration deceleration forces result in a difference in speed between grey and white matter. This results in the stretching of the axons (figure 1).8 The shear injury can cause primary lesion to the axon (axonotomy) and secondary injury as a result of an overstretched axon. This secondary or delayed injury is a result of axonal stretch followed by a progressive cascade of pathologic cellular mechanisms disrupting the structural integrity of the axon and neuron.10
Figure 1. Traumatic axonal injury
Acceleration-deceleration forces can result in lesions on the grey-white matter transition, where injury of the axon occurs. Stretching, tearing or complete shearing of the axon can be the result.
Axonal injury is referred to as diffuse axonal injury (DAI) or traumatic axonal injury (TAI). In radiologic imaging of TBI the definition of DAI is multiple axonal lesions in multiple brain regions, when lesions are confined to only one region it should be named TAI.11 In clinical practice DAI and TAI are being used almost interchangeably. Most patients with axonal injury have sustained moderate or severe TBI, but after mild TBI axonal injury can also be present.6
In patients with axonal injury a Computed Tomography (CT) scan of the brain can appear normal, but sometimes microbleeds can be visible indicating the presence of axonal injury. Magnetic Resonance Imaging (MRI) is more sensitive for axonal injury. It can be visible as microbleeds (see Figure 2) on a T2 star gradient echo (T2*GRE), a fast field echo (FFE), and/or susceptibility weighed image (SWI).12-15
Chapter 1 General introduction
Figure 2. Microbleeds on MRI
Fast Field Echo (FFE) images of a 24- year old male after a car accident, with microbleeds diffuse in the brain A. cortical lesions, B. lesions in the corpus callosum, C. lesions in the basal ganglia, D. lesions in the brainstem.
Grading of axonal injury on MRI is based on histopathological research.7,8 The lesions are graded according to the depth of the lesions, a higher lesion grade correlates with higher trauma impact.8 These lesions can also be scored on brain MRI: grade 1; cortical lesions, grade 2; lesions in the corpus callosum, and grade 3; lesions in the brainstem (image 2).12 See Figure 3.
Figure 3. Grading of axonal injury lesions
Grade 1 cortical lesions, 2. Grade 2 lesions in the corpus callosum, 3. Grade 3 lesions in the brainstem.
Microbleeds on MRI are also described as hemorrhagic axonal injury. Also non-hemorrhagic axonal injury can be seen on the MRI in multiple sequences, i.e. fluid attenuated inversion recovery (FLAIR) and diffusion weighed imaging (DWI).15 Microbleeds on MRI (T2*GRE and SWI) are considered a biomarker for axonal injury. The SWI is a recently developed sequence and is more sensitive for microbleeds than T2*GRE.16 Both hemorrhagic and non-hemorrhagic lesions can attenuate or disappear over time, but hemorrhagic lesions are more stable in the first six months after trauma.17,18 Therefore, in clinical practice and in this thesis axonal injury refers to hemorrhagic lesions unless otherwise indicated. The strength of the MRI magnetic field influences sensitivity for detecting lesions. Thus a higher magnetic field strength (Tesla) results in a higher sensitivity.19,20
With DWI techniques the diffusion of water is measured. The direction of diffusion provides information regarding brain structures and lesions. This is referred to as diffusion tensor imaging (DTI).21 White matter tracts in the brain can be indicated in this matter because water diffuses in the direction of the white matter tracts. This is represented with the fractional anisotropy (FA). A FA of 1 indicates a perfect unidirectional diffusion and 0 a perfect random diffusion of water (figure 4).22 When there is axonal injury, the white matter tracts are disrupted and the diffusion of water is inhibited, resulting in a lower FA.23-25
Figure 4. Diffusion weighed imaging for diffusion tensor imaging
A. Fractional anisotropy map, B. Tractography.
12
13
Chapter 1 General introduction
Effects of axonal injury
Although patients with mild TBI have the best prognosis, 56% of them have an incomplete recovery after six months.26 Patients with moderate to severe TBI have a worse prognosis. After severe TBI 63% of the patients have a favourable functional outcome.27 A good functional outcome is related to better scores on neuropsychological tests. However, 18.5% score low on satisfaction with life and 20% of these patients score low on at least one neuropsychological test.28
Patients with axonal injury are often young males (77%) involved in traffic accidents.2 After the first resuscitation, patients generally are admitted to the Intensive Care Unit (ICU). During the hospital admission several complications can occur. For example, brain oedema can cause swelling of the brain, resulting in an increase of the intracranial pressure. Also, the autonomic regulation of blood pressure, heartrate, respiratory rate, and perspiration can be dysregulated due to the brain injury. Prior to their injury, patients usually participated in an educational or working environment and in social activities. Having brain injury often changes the future of these patients. However, predicting outcome in patients with axonal injury is very difficult. Patients with a high grade of axonal injury can recover very well. At the same time patients with a low grade of axonal injury sometimes do not return to their prior educational/working environment.
Aims and outline of this thesis
The focus in this thesis is on patients with axonal injury after TBI in order to gain more knowledge regarding outcome in these patients. Functional and health related quality of life (HRQL) outcome as well as predictors for outcome are studied. Three types of studies are included in this thesis, a review, a retrospective, and a prospective study. The retrospective study was performed on data from patients from the Elisabeth-Tweesteden Hospital (ETZ) Tilburg and the University Medical centre Groningen (UMCG). The prospective study was performed in two additional centres, Haaglanden Medical Centre (HMC) in The Hague and Medisch Spectrum Twente (MST) in Enschede. All participating centres are Level I trauma centres.
First, we reviewed the literature to establish the present state of knowledge regarding the outcome in patients with axonal injury and the different methods to score or quantify DAI in relation to outcome prediction. (Chapter 2)
Secondly, we performed a retrospective cohort study in the two Level I trauma centres mentioned. We studied the functional outcome and HRQL in patients with DAI. Patients were included regardless the severity of TBI. (Chapter 3)
Thirdly, the presence and symptoms of autonomic dysregulation in patients with DAI was described and was evaluated as a prognostic factor in these patients. (Chapter 4)
Fourthly, in order to improve outcome prediction in patients with DAI, different MRI grading methods were assessed. We compared the clinically most used MRI grading method with other methods described in the literature and small adjustments to the clinically most used method. This is the first study which directly compared MRI grading methods. (Chapter 5)
Fifthly, newer MRI techniques have become available and are promising in diagnosing DAI and predicting outcome in patients with DAI. We performed a prospective cohort study to establish which brain regions in patients with DAI are related to functional outcome. (Chapter 6)
Sixthly, the relationship between emotion recognition and HRQL was assessed. Also global network efficiency, calculated with DWI data, was related with emotion recognition. (Chapter 7)
Finally, the main findings of this thesis and future directions were described.
(Chapter 8)
Chapter 1 General introduction
REFERENCES
1. Skandsen T, Kvistad KA, Solheim O, Strand IH, Folvik M, Vik A. Prevalence and impact of diffuse axonal injury in patients with moderate and severe head injury: A cohort study of early magnetic resonance imaging findings and 1-year outcome. J Neurosurg. 2010;113(3):556-563.
2. Moe HK, Myhr JL, Moen KG, Håberg AK, Skandsen T, Vik A. Association of cause of injury and traumatic axonal injury: A clinical MRI study of moderate and severe traumatic brain injury. J Neurosurg. 2019;1(aop):1-9.
3. Steyerberg EW, Wiegers E, Sewalt C, et al. Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI: A european prospective, multicentre, longitudinal, cohort study. The Lancet Neurology. 2019;18(10):923-934.
4. Scholten AC, Haagsma JA, Panneman MJ, Van Beeck EF, Polinder S. Traumatic brain injury in the netherlands: Incidence, costs and disability-adjusted life years. PLoS one. 2014;9(10):e110905.
5. Gentleman SM, Roberts GW, Gennarelli TA, et al. Axonal injury: A universal consequence of fatal closed head injury? Acta Neuropathol. 1995;89(6):537-543. 6. Inglese M, Makani S, Johnson G, et al. Diffuse axonal injury in mild traumatic
brain injury: A diffusion tensor imaging study. J Neurosurg. 2005;103(2):298-303. 7. Gennarelli TA, Thibault LE, Adams JH, Graham DI, Thompson CJ, Marcincin
RP. Diffuse axonal injury and traumatic coma in the primate. Ann Neurol. 1982;12(6):564-74.
8. Adams JH, Doyle D, Ford I, Gennarelli TA, Graham DI, McLellan DR. Diffuse axonal injury in head injury: Definition, diagnosis and grading. Histopathology. 1989;15(1):49-59.
9. Zhang J, Yoganandan N, Pintar FA, Gennarelli TA. Role of translational and rotational accelerations on brain strain in lateral head impact. Biomed Sci
Instrum. 2006;42:501-506.
10. Li, Jia L, XueYuan F, DongFu P, DongChao. Biomarkers associated with diffuse traumatic axonal injury: Exploring pathogenesis, early diagnosis, and prognosis.
Journal of Trauma-Injury Infection & Critical Care. 2010;69(6):1610-1618.
11. Smith DH, Hicks RR, Johnson VE, et al. Pre-clinical traumatic brain injury common data elements: Toward a common language across laboratories. J Neurotrauma. 2015;32(22):1725-1735.
12. Gentry LR. Imaging of closed head injury. Radiology. 1994;191(1):1-17.
13. Gentry LR, Godersky JC, Thompson B, Dunn VD. Prospective comparative study of intermediate-field MR and CT in the evaluation of closed head trauma. AJR
Am J Roentgenol. 1988;150(3):673-682.
14. Mittl RL, Grossman RI, Hiehle JF, et al. Prevalence of MR evidence of diffuse axonal injury in patients with mild head injury and normal head CT findings.
AJNR Am J Neuroradiol. 1994;15(8):1583-1589.
15. Geurts BH, Andriessen TM, Goraj BM, Vos PE. The reliability of magnetic resonance imaging in traumatic brain injury lesion detection. Brain injury. 2012;26(12):1439-1450.
16. Cheng AL, Batool S, McCreary CR, et al. Susceptibility-weighted imaging is more reliable than T2*-weighted gradient-recalled echo MRI for detecting microbleeds. Stroke. 2013;44(10):2782-2786.
17. Moen KG, Skandsen T, Folvik M, et al. A longitudinal MRI study of traumatic axonal injury in patients with moderate and severe traumatic brain injury. J
Neurol Neurosurg Psychiatry. 2012;83(12):1193-1200.
18. Messori A, Polonara G, Mabiglia C, Salvolini U. Is haemosiderin visible indefinitely on gradient-echo MRI following traumatic intracerebral haemorrhage?
Neuroradiology. 2003;45(12):881-886.
19. Scheid R, Ott DV, Roth H, Schroeter ML, Von Cramon DY. Comparative magnetic resonance imaging at 1.5 and 3 tesla for the evaluation of traumatic microbleeds.
J Neurotrauma. 2007;24(12):1811-1816.
20. Luccichenti G, Giugni E, Barba C. 3 tesla is twice as sensitive as 1.5 tesla magnetic resonance imaging in the assessment of diffuse axonal injury in traumatic brain injury patients. Funct Neurol. 2010;25(2):109.
21. Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. Journal of Magnetic Resonance, Series B. 1994;103(3):247-254. 22. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues
elucidated by quantitative-diffusion-tensor MRI. Journal of magnetic resonance.
Series B. 1996;111(3):209-19.
23. Galanaud D, Perlbarg V, Gupta R, et al. Assessment of white matter injury and outcome in severe brain traumaa prospective multicenter cohort. The Journal
of the American Society of Anesthesiologists. 2012;117(6):1300-1310.
24. Hellyer PJ, Leech R, Ham TE, Bonnelle V, Sharp DJ. Individual prediction of white matter injury following traumatic brain injury. Ann Neurol. 2013;73(4):489-499.
16
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Chapter 1 General introduction
25. Moen KG, Vik A, Olsen A, et al. Traumatic axonal injury: Relationships between lesions in the early phase and diffusion tensor imaging parameters in the chronic phase of traumatic brain injury. J Neurosci Res. 2016;94(7):623-635. 26. van der Naalt J, Timmerman ME, de Koning ME, et al. Early predictors of outcome
after mild traumatic brain injury (UPFRONT): An observational cohort study. The
Lancet Neurology. 2017;16(7):532-540.
27. Rieckmann P. Neurodegeneration and clinical relevance for early treatment in multiple sclerosis. Int MS J. 2005;12(2):42-51.
28. Nelson LD, Ranson J, Ferguson AR, et al. Validating multi-dimensional outcome assessment using the traumatic brain injury common data elements: An analysis of the TRACK-TBI pilot study sample. J Neurotrauma. 2017;34(22):3158-3172.
Chapter 2
Diffuse axonal injury after traumatic
brain injury is a prognostic factor for
functional outcome: A systematic
review and meta-analysis
Marleen M. van Eijck Guus G. Schoonman Joukje van der Naalt Jolanda de Vries Gerwin Roks
20
21
Chapter 2 Prognosis of DAI
ABSTRACT
Objective To determine the prognosis of adult patients with traumatic brain injury
(TBI) and diffuse axonal injury (DAI).
Methods Online search (PubMed, Embase and Ovid Science Direct) of articles
providing information about outcome in I) patients with DAI in general, II) DAI vs. Non-DAI, III) related to MRI classification, and IV) related to lesion location/load. A reference check and quality assessment were performed.
Results A total of 32 articles were included. TBI patients with DAI had a favourable
outcome in 62%. The risk of unfavourable outcome in TBI with DAI was three times higher than in TBI without DAI. OR for unfavourable outcome was 2.9 per increase of DAI grade on MRI. Lesions located in the corpus callosum were associated with an unfavourable outcome. Other specific lesion locations and lesions count showed inconsistent results regarding outcome. Lesion volume was predictive for outcome only on Apparent Diffusion Coefficient and Fluid Attenuation Inversion Recovery MRI-sequences.
Conclusions Presence of DAI on MRI in patients with TBI results in a higher
chance of unfavourable outcome. With MRI grading, OR for unfavourable outcome increases threefold with every grade. Lesions in the corpus callosum in particular, are associated with an unfavourable outcome.
Key words: Diffuse Axonal Injury; Head Injury; Outcome; Traumatic Brain Injury
INTRODUCTION
The prognosis op patients with traumatic brain injury (TBI) is complicated by the fact that outcomes highly depend the location, the type and the severity of the injury. High-impact trauma with acceleration-deceleration forces, especially rotational acceleration, can lead to stretching and deformation of the brain tissue resulting in Diffuse Axonal Injury (DAI).1,2 In autopsy studies, DAI has been found in 100% of the fatal cases of severe Traumatic Brain Injury (TBI) (Glasgow Coma Score (GCS) 3-8).3 DAI has also been described in surviving patients with moderate or severe TBI DAI.4,5 The characteristic deep petechial haemorrhages in DAI can be shown with Magnetic Resonance Imaging (MRI).6 In patients with mild TBI, white matter changes in predilection sites for DAI can be found with Diffusion Tensor Imaging (DTI).5 Staging of DAI is based on a neuropathological study performed by Adams et al.7 In vivo Magnetic Resonance Imaging (MRI) is superior to Computed Tomography (CT) in visualisation of DAI. Three stages can be distinguished on MRI: 1) visible lesions in the lobar white matter 2) lesions in the corpus callosum and 3) lesions in the brain stem.6
Literature is inconsistent regarding the prediction of outcome in TBI patients with DAI. One of the problems is the lack of a worldwide consensus on the definition and classification of DAI, and another problem is the heterogeneity of patients. TBI research is often done in patients with TBI of various severities, and patients with DAI are usually only a subgroup of the included patients. Conclusions regarding outcome prediction for patients with DAI may also be affected by other elements of study design, such as inclusion criteria, MRI field strength, performed sequences, and timing of the MRI. Therefor results are difficult to compare, for example one study reported that only stage 3 was related to an unfavourable outcome, whereas DAI stage 1 and 2 were not related to outcome.4 Conversely, another study found a good correlation of stage 2 and 3 with a vegetative state.8 Another study found that lesions in the genu of the corpus callosum were associated with unfavourable outcome after one year, although these lesions were not specified in the three grades MRI rating scale.9 Because of these inconsistent results, predicting outcome in patients with TBI and DAI is a particular challenge in clinical practice.
Chapter 2 Prognosis of DAI
Our main objective was to determine the functional prognosis, as measured with the Glasgow Outcome Scale (GOS) or the Glasgow Outcome Scale-Extended (GOSE), in adult patients with TBI and DAI. To ensure the most informed answer, we performed a systematic review. This information can support clinicians in providing information to patients with DAI and/or their families and it can support clinical decisions concerning treatment.
We firstly hypothesized that patients with a higher grading of DAI will have a more unfavourable outcome. Second, we hypothesized that outcome is related to lesion volume and location.
METHODS
Search strategyOn January 6, 2015, an electronic database search was performed in PubMed, Ovid Embase and Science Direct. Synonyms for DAI were used as search terms, and MRI was added as a compulsory term. Finally, outcome was added, which could also be defined as prognosis, Modified Rankin Score, Glasgow Outcome Score or Quality of Life. The exact search syntaxes are presented in supplementary table. No limitations were placed on the search. A reference check of the included articles was performed to ensure a complete selection of articles.
Selection criteria
Studies were included if they reported outcome (GOS/GOSE) in adult patients with TBI and DAI diagnosed by MRI (Fluid Attenuated Inversion Recovery (FLAIR), T2*Gradient Echo imaging (T2*GRE), Susceptibility Weighed Imaging (SWI) or Diffusion Weighed Imaging (DWI)), all magnetic field strengths. Since the definition of DAI is inconsistent in literature, we limited the inclusion of studies to DAI confirmed by MRI. By including the different sequences and MR field strengths, we still ensured a broad inclusion of studies describing outcome in patients with DAI.
Since DAI can occur after mild, moderate and severe TBI we included all severities of TBI. Length of follow-up was no exclusion criterion, again to ensure the completeness of information. Besides, since TBI patients with DAI often also have other types of brain injury, this review included studies on patients with pure DAI,
as well as studies on patients with DAI in combination with other types of TBI. Including studies on all patients with DAI provided complete and clinically relevant information about prognosis in these patients. However, articles were excluded if they described outcome of patients with TBI including patients with DAI, but did not provide outcome results for patients with DAI separately.
We only included peer reviewed, published articles in English, Dutch or German, no publication date was excluded. All research designs were included except review articles and case reports (<5 patients). Reviews were excluded to prevent bias by double count of a patient population, and case reports were excluded because the results can often not be generalised to a larger population. Studies performed only in children were excluded, and studies on adults and children in which outcome of adults could not be distinguished from outcome of children were excluded if the majority of patients was 16 years or younger.
Article selection
After filtering out duplicates, the titles and abstracts of the remaining articles were screened, using the following selection criteria: 1) patients with TBI and with DAI as diagnosed by MRI, 2) prognosis as outcome measure, 3) original data. Articles that fulfilled these criteria were retrieved, and full texts were assessed for inclusion or exclusion. Case reports (<5 patients included) and post-mortem research were excluded. If several articles reported on the same patient population, the most relevant article concerning prognosis in patients with DAI was selected. In case of any doubt, the decision on in- or exclusion of articles was reached through discussion and mutual consensus (M.E. and G.R.).
Data collection and quality assessment
Of all the included articles, data were extracted using a standardized form. The following variables were collected: total number of patients, number of DAI patients, age, DAI grading, MRI: timing, field strength and used sequences, follow-up period, outcome for all patients, and outcome for DAI patients.
The GOS is a 5-point scale for functional outcome, ranging from 1=death to 5=Good Recovery. The GOSE is an 8-point scale, ranging from 1=death to 8=Good recovery.6,10 Both the dichotomised and, if available, the complete scores were extracted. We
24
25
Chapter 2 Prognosis of DAI
dichotomised the GOS and GOSE into favourable outcome (GOS 4-5 or GOSE 6-8) and unfavourable outcome (GOS 1-3 or GOSE 1-5). This dichotomisation was chosen to include the maximum number of high-quality articles in the meta-analysis. All studies were assessed for quality and risk of bias. For observational studies no standardized system for quality control is available. We used the STROBE criteria to evaluate the quality of observational studies.11 STROBE is a list of 22 items, which should all be fully reported and comprehensively explained for the article to be of high quality. We scored each item 0 if it was not present or insufficient and 1 if present, hence a maximum of 22 points could be awarded. High quality was defined as a score of ≥19 with prospectively collected outcome measurements. The high-quality articles were included for meta-analysis.
Data analysis
The included articles were assigned to at least one out of four categories:
1) outcome of patients with DAI in the acute and sub-acute phase (including all the selected articles), 2) outcome in patients with TBI without DAI compared to patients with DAI (including only high-quality articles), 3) outcome of patients with DAI according to MRI grading (grade 1-3) (including only high-quality articles) and 4) outcome of patients with DAI according to other MRI scales, number or distribution of lesions (including all the selected articles).
Analysis according to category 1 to 3 were pre-specified. However we found a number of articles that did provide information concerning DAI and prognosis but did not use the MRI grading Gentry et al described.6 These articles were described in a fourth category without statistical analyses.
Data were pooled if similar DAI descriptions and outcomes were reported. Articles not suitable for pooling were described. Absolute risks and Odds Ratios (OR) and associated 95% Confidence Interval (CI) were collected. For pooled articles, an OR and associated 95% CI was calculated. Statistical analysis was performed using IBM SPSS Statistics 19. A p-value of p ≤0.05 was considered statistically significant.
RESULTS
Of a total number of 902 articles found after entering the search syntax (446 PubMed, 392 Ovid Embase, 64 Science Direct), 164 duplicates were extracted, resulting in 738 remaining articles. Title and abstract screening reduced this number to 85 articles selected for full text screening, which resulted in 30 relevant articles. A reference check of these 30 articles identified two additional articles, resulting in 32 articles being included in this review. Flowchart 1 describes the selection process and the reasons for exclusion.
The results for category 1-3 are summarized in table 1. Data extraction and quality assessment of the 32 included articles are presented in the supplementary table.
1. Outcome DAI in general
In this first category, all patients with DAI were included to determine the prognosis for this entire group of patients. Articles describing outcome in patients with DAI in the acute and sub-acute phase after injury were included, which resulted in 13 articles describing a total of 549 patients with a mean age of 33.5 years.4,9,12-22 DAI was present in 449 patients, and an unfavourable outcome was found in 38% (n=169, 95%CI 0.33-0.42).
The field strength of the MR scanners differed: two studies used a 1.0 Tesla (T) scanner12,21, two studies did not describe MRI field strength15,17, and the other 9 studies used a 1.5 T MR scanner.
One other study described outcome in patients with DAI, however that study was not included in this analysis because it only included patients in a vegetative state (n=42), in all of these patients DAI was present. None of them recovered from their vegetative state in the follow-up period of 12 months.8
An imitation-inhibition test performed by Schroeter et al. showed that patients with DAI were impaired three years after trauma. The Stroop task was unaltered for these patients.23
Chapter 2 Prognosis of DAI
Flowchart 1. Article selection process
Table 1. Summary of results
N % favourable outcome
(95% CI)
OR (95% CI)
DAI in general 395 52 (0.5 – 0.6)
-TBI with DAI vs. -TBI without DAI –
+ 14164 83 (0.7-0.9)62 (0.5-0.7) 2.9 (1.4 - 6·0)
DAI according to MRI classification 1
2 3 88 107 63 83 (0.7-0.9) 60 (0.5-0.7) 37 (0.3-0.5) 2 vs. 1 3 vs. 1 3 vs. 2 3.3 (1.7 – 6.4) 8.5 (4.0 – 18.0) 2.6 (1.4 – 4.9)
Legend: - : Diffuse Axonal Injury absent, +: Diffuse Axonal Injury present, 1: Diffuse Axonal Injury grade 1, 2: Diffuse Axonal Injury grade 2, 3: Diffuse Axonal Injury grade 3
Abbreviations: N: number of patients, OR: Odds Ratios, 95% CI: 95% Confidence Interval, TBI: Traumatic Brain Injury
2. Outcome TBI with DAI vs. TBI without DAI
In this category, we aimed to answer the question whether outcome differed between patients with DAI after TBI and TBI patients without DAI. Articles comparing outcomes in patients with TBI and DAI versus patients with TBI but without DAI were scarce. Only two high-quality articles were found and included in the presented analysis.4,15 Three additional articles describing these outcomes were considered to be of low quality and were therefore not included in the analysis.16,18,24
The high-quality articles described 141 patients with DAI and 64 patients without DAI. Mean age of patients was 30.5 years (range 5-71 years), and the mean follow-up time was nine months (range 6-12). Of the patients with DAI after TBI 38% had an unfavourable outcome, compared to 17% of the patients without DAI after TBI. The OR for an unfavourable outcome for TBI patients with DAI versus TBI patients without DAI was 2.9 (95% CI 1.4–6.0).
3. Outcome DAI according to MRI classification
Five articles describing outcome in relation to MRI grading were of high quality and were therefore included in the analysis to determine the prognosis in relation to MRI grading.4,9,12,13,15 Three other articles also described outcome in relation to MRI grading, but due to their lower quality they were not included in the analysis.17,18,25 The remaining five articles described a total of 258 patients with DAI. Grade 1 was seen in 88 patients, grade 2 in 107 patients and grade 3 in 63 patients. Mean age was 35.3 years and the MRI was performed after a mean of 19.8 days. An unfavourable outcome was seen in 17% (95% CI 0.1-0.3) of patients with DAI grade 1, in 40% (95% CI 0.3-0.5) with DAI grade 2 and in 63% (95% CI 0.5-0.7) with DAI grade 3.
Table 2 presents the results of outcome related to the 3 grades. The OR for an unfavourable outcome gradually rises per DAI grade. A continuous OR was calculated. For each step increase in DAI grade the OR for an unfavourable outcome is 2.9 (95%CI 2.0-4.2).
Firsching et al. only reported mortality in patients with DAI in relation to MRI grading. One out of 32 patients with DAI grade 1 or 2 died and eight out of 32 patients with
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Chapter 2 Prognosis of DAI
DAI grade 3 died, resulting in an OR of 10.3 (95% CI 1.2-88.4).26 It must be noted that this study only included patients with a severe TBI with GCS <8.
One other study on 15 patients with DAI grade 1 and 2 found no relation between MRI findings and the total scores on the working memory tests or the attention test.27
Neither of these two articles could be included in the analyses, because in neither of them reported the GOS or GOSE. Another study by Chelly et al. on 38 patients with DAI grade 1 and 2 could not be included in the analysis either, since outcomes were not described for grade 1 and 2 separately.25
4. Outcome DAI in relation to other MRI scales or distribution of lesions
Outcomes were also described in relation to other types of MRI grading or in relation to number, volume, or location of lesions. Pooling of the data provided by these studies was not possible because of the wide variation of classifications used.
Number of lesions
Several studies described lesion counts on different MRI sequences in relation to outcome. Five articles described a relation between number of lesions and outcome22,25,28-30, and five other articles found no relation31-35. Therefore this relation was not consistently proven throughout literature.
Lesion volume
The relation between lesion volume and outcome prediction was examined by applying several MRI sequences, mostly FLAIR and apparent diffusion coefficient (ADC). Schaefer et al. found a correlation between volume of lesions on FLAIR, DWI and T2 spin echo and the modified Rankin Scale Score but they could not find this correlation for the volume of lesions on T2*GRE.28
White matter DAI volumes in patients after moderate to severe TBI were found to be correlated with functional outcomes at 6-month follow-up. The greater the proportion of the brain volume affected by DAI, the poorer the GOSE scores. A greater lesion volume in the region of the internal /external capsule region predicted an unfavourable outcome.36 Unfavourable outcome was also predicted by the
volume of lesions (MRI <4 weeks) in the corpus callosum, brain stem, and thalamus after severe TBI.25 Another study found that global clinical outcome in early MRI was associated with the volume of non-haemorrhagic DAI lesions as well as with the number of DAI lesions.29
Compared to controls, patients with DAI had significantly different mean ADC values in the peripheral grey and white matter, deep grey and white matter, and posterior fossa. Besides patients with an unfavourable outcome (GOS 1-3) had significantly higher mean ADC values in the deep white matter than patients with a favourable outcome (GOS 4-5).19
Location
The location of lesions has often been used as a classification and related to functional outcome. In table 2, all described locations are summarized. Most studies focussed on lesions in the corpus callosum9,21,25,28,33,37-39 or other deep brain regions such as the basal ganglia28,39 or the brain stem28,35,37,39. Only lesions in the corpus callosum were consistently reported to have a relation with outcome. Six out of seven studies found this relation, in one of these studies only found a relation with outcome when there were multiple lesions in the corpus callosum (table 2). No consistent relationship between prognosis and other locations of the lesions could be distilled from these articles.
In patients with hypopituitarism after trauma more lesions were found in the body of the corpus callosum, in the basal ganglia, in the thalamus, and in the and grey-white matter junction in the cerebrum structures. Injuries to these structures and hypopituitarism have a relation with an unfavourable outcome, but no definitive pathophysiological basis was found for a causal relationship between hypopituitarism and an unfavourable outcome.39
Chapter 2 Prognosis of DAI
Table 2. Lesion location and relation to outcome Location Ta kao ka 20 02 Sc ha ef er 20 04 Je on g 2 01 0 Sc h ei d 2 01 0 Ca lv i 2 01 1 M at su kawa 20 11 Ch ell y 20 11 Moe n 2 01 4 Corpus Callosum Splenium Genu -. . + . . + + -. . SL- ML+ . . + . . + . . + . . Basal ganglia . - + . . . . . Brain stem . - + - SL- ML+ . - + Midbrain . . . - . . . . Thalamus . - + . . . . + GWM junction cerebrum . . + . . . . .
The included articles describing lesion location in relation to outcome regarding: corpus callosum, basal ganglia, brain stem, midbrain, thalamus and gray-white matter (GWM) junction in the cerebrum. Legend: + : a relation between lesion location and outcome was found, -: no relation between lesion location and outcome was found, .: the mentioned lesion location is not described in the article. When distinction between a single lesion (SL) or multiple lesions (ML) was mad this is mentioned.
DISCUSSION
This systematic review of the literature aimed to summarize the current knowledge on the prognosis of TBI patients with DAI and to establish whether TBI patients with a higher grading of DAI have a more unfavourable outcome and whether outcome in these patients is related to lesion volume and location. Results of 32 included articles showed that the overall functional outcome of patients with DAI was unfavourable in 38%. The presence of DAI resulted in a threefold higher risk of an unfavourable outcome than in TBI patients without DAI: the risk for an unfavourable outcome also increased threefold for each increase in DAI grade. An unfavourable outcome was seen more often in patients with lesions in the corpus callosum, whereas for other locations this relation was inconsistent. The relation between lesion count and outcome was inconsistent, as well as the relation between volume and outcome. Comparison of patients with DAI and patients without DAI, showed that the risk for an unfavourable outcome was almost threefold higher in patients with DAI. Overall, however, 62% of patients with DAI had a favourable outcome. Possibly the high percentage of favourable outcome in DAI patients in general can be explained
by the exclusion of patients with other brain injuries and of patients with a high risk of mortality. Among patients with DAI, a higher DAI grade resulted in a higher risk of an unfavourable outcome; nevertheless, it must be noted that a favourable outcome was found in 37% of patients with DAI grade 3. Therefore, the diagnosis of DAI, even grade 3, does not automatically imply an unfavourable outcome. Contrary to our findings, Adams et al. only found a relation between DAI grade 3 and an unfavourable outcome.7 This difference in results is probably due to the difference between the MRI classification as defined by Gentry et al. and the histopathological grading used by Adams et al. According to the histopathological definition DAI grade 1 comprises microscopical lesions either in the lobar white matter, the corpus callosum, the brain stem or the cerebellum. However, in the MRI classification, DAI grade 1 only comprises lesions in the cerebral hemispheres, whereas lesions in the corpus callosum are classified as DAI grade 2.
To represent everyday practice, articles were only included if DAI was diagnosed using a conventional MRI technique, whereas articles were excluded if diagnosis only involved DTI or functional MRI. This review focussed on the relation between DAI and outcome, but outcome is also influenced by other factors such as, pupillary response, GCS, duration of loss of consciousness, age and the presence of dysautonomia.9,25,30,33
Patients with severe TBI were more likely to have DAI, and they also showed more severe DAI grades. Histopathological lesions in the lobar white matter, in the corpus callosum, and in the dorsolateral aspects of the brain stem were related to an increased severity of trauma.7 DAI was diagnosed in 69% of patients with moderate TBI and in 89% of patients with severe TBI.35 DAI grade 3 was found more often in patients with severe TBI than in patients with moderate TBI (30% vs. 20%).35 We expected a higher number or volume of lesions to predict an unfavourable outcome, but this could not be confirmed due to inconstancies in the reported results. SWI is a more sensitive for the detection of microbleeds than T2*GRE.40 However, the relation between DAI lesions detected with SWI and outcome is not clear. Only one of the included articles reported the use of SWI, but no relation between lesions detected with SWI and outcome was described.34
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Chapter 2 Prognosis of DAI
Outcome is most often reported with a functional outcome measure, but other outcome measures such as cognitive impairment and quality of life are also relevant. In patients with pure DAI, all cognitive domains can be affected.32 However, a study on a cohort of patients with TBI demonstrated no relation between DAI and cognitive impairment.33 Perhaps this relation was not found because patients also had other intracerebral lesions which had more effect on cognition. Comparison of the studies was hampered by differences in the use of cognitive screening methods, follow-up period, and presence of other types of brain injury.
None of the included articles reported patient-reported outcome measures, such as quality of life. Even though providing the patient’s experience of outcome is becoming increasingly important.
Limitations
Despite the efforts to provide a complete summary of current literature, it is possible that relevant articles were missed in this review. We aimed to provide a complete overview of the literature by using several synonyms for DAI, MRI, and outcome in the search, as well as cross referencing the references of relevant articles. However, outcome measures in particular differ greatly between studies, and therefore we also included other terms such as, ‘outcome’ and ‘prognosis’, in our search terms to prevent the missing of other outcome measures then GOS or GOSE (supplementary table). The different outcome measures and follow-up periods impaired the comparison of results.
Selection bias might have been caused by the fact that patients with moderate or severe TBI more often receive additional MRI scanning than patients with mild TBI. Only one article exclusively included patients with mild TBI, while patients with mild TBI were excluded in 13 of the included articles. As a result patients with moderate to severe TBI and DAI are overrepresented in this review. Patients with a more severe TBI are expected to have a less favourable outcome, therefore this overrepresentation possibly resulted in a higher percentage of unfavourable outcomes. To reduce this bias in the results, we reported the analysis per DAI grade of the articles with a high STROBE score. An analysis which also included the articles with a lower strobe score, resulted in similar risks for a favourable outcome.
The definition of DAI differs throughout all published articles. This review only included articles in which DAI was proven with MRI. The MRI field strength and the used sequences differed between articles or were not described The use of an MRI with a lower field strength could have caused DAI lesions to be missed, which may have resulted either in a lower number of patients with DAI or in the attribution of a lower DAI grade. The MRI classification described by Gentry et al. is a widely used and accepted MRI scale, but other types of grading or MRI ratings were used as well.6 Timing of the MRI after trauma varied from less than 24 hours to 36 months, or was not mentioned. This may have influenced results, since DAI lesions can disappear over time and haemorrhagic lesions may attenuate. The MRI should preferably be made within a few weeks after trauma in order not to miss valuable information.29
The future
The results of this review demonstrate clearly that the presence of DAI after TBI is unfavourable in relation to functional outcome. However, the diagnosis of DAI alone is not sufficient to provide accurate prognostic information to patients or their families. DAI grading on MRI helps to indicate the odds of an unfavourable outcome. Other scoring methods than the 3-graded Gentry classification have been insufficiently reported to incorporate these into everyday practice. An internationally accepted definition of DAI would facilitate comparison of research. Also, in clinical practice, predicting outcome in patients with DAI would benefit greatly from a prognostic model that includes an imaging scoring system, preferably in combination with clinical predictors.
In the future, predicting outcome may be based on other MRI sequences used to diagnose DAI, such as SWI and DTI. SWI is more sensitive to the number and volume of DAI lesions than the T2*-weighed gradient echo imaging, but the relation of number or volume of DAI lesions on SWI was not proven in this review.41,42
DTI is used to visualise and calculate white matter tracts.43 It is not yet clear which role DTI might play in everyday practicein the outcome predictionof patients with DAI. Most research on DTI has been done in patients with TBI in general, and results are often not specified for patients with DAI proven on conventional MRI.5,44-46 In patients with DAI grade 1 and 2, the distribution of white matter abnormalities
Chapter 2 Prognosis of DAI
correlated with the results of the neuropsychological tests of working memory and attention.27 Alterations in anisotropy along fibre tracts at predilection sites for DAI have been shown in patients with TBI when conventional MRI was unremarkable. The degree of fractional anisotropy was correlated to the discharge Rankin Score.47 Future research should incorporate advanced imaging techniques in relation to neuropsychological impairments.
CONCLUSION
In patients with TBI and DAI confirmed with MRI, outcome is unfavourable compared to patients without DAI. When DAI is scored using the current MRI scoring system grade 1 to 3, the odds for an unfavourable outcome increase threefold with every grade. The number or volume of DAI lesions were not found to predict outcome. As for the location, only DAI lesions in the corpus callosum predicted an unfavourable outcome.
DECLARATION OF INTEREST
This work was supported by a grant of the Dutch organisation for health research and care innovation (ZonMW) section TopCare Xperiment, grand number 842004002. The funding source played no role in the design, collection, analysis, interpretation or publication of the data. Nobody other than the authors is responsible for the content of this paper.
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20. Wada T, Kuroda K, Yoshida Y, Ogawa A, Endo S. Recovery process of immediate prolonged posttraumatic coma following severe head injury without mass lesions. Neurol Med Chir (Tokyo). 2005;45(12):614-9; discussion 619-20.
21. Takaoka M, Tabuse H, Kumura E, et al. Semiquantitative analysis of corpus callosum injury using magnetic resonance imaging indicates clinical severity in patients with diffuse axonal injury. J Neurol Neurosurg Psychiatry. 2002;73(3):289-293. 22. Yanagawa Y, Sakamoto T, Takasu A, Okada Y. Relationship between maximum
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23. Schroeter ML, Ettrich B, Schwier C, Scheid R, Guthke T, von Cramon DY. Diffuse axonal injury due to traumatic brain injury alters inhibition of imitative response tendencies. Neuropsychologia. 2007;45(14):3149-3156.
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26. Firsching R, Woischneck D, Klein S, Ludwig K, Dohring W. Brain stem lesions after head injury. Neurol Res. 2002;24(2):145-146.
27. Gu, Lei L, Jia F, et al. Detection of white matter lesions in the acute stage of diffuse axonal injury predicts long-term cognitive impairments: A clinical diffusion tensor imaging study. Journal of Trauma and Acute Care Surgery. 2013;74(1):242-247. 28. Schaefer PW, Huisman TA, Sorensen AG, Gonzalez RG, Schwamm LH. Diffusion-weighted MR imaging in closed head injury: High correlation with initial glasgow coma scale score and score on modified rankin scale at discharge. Radiology. 2004;233(1):58-66.
29. Moen KG, Skandsen T, Folvik M, et al. A longitudinal MRI study of traumatic axonal injury in patients with moderate and severe traumatic brain injury. J
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30. Zheng WB, Liu GR, Kong KM, Wu RH. Coma duration prediction in diffuse axonal injury: Analyses of apparent diffusion coefficient and clinical prognostic factors.
Conf Proc IEEE Eng Med Biol Soc. 2006;1:1052-1055.
31. Lee H, Wintermark M, Gean AD, Ghajar J, Manley GT, Mukherjee P. Focal lesions in acute mild traumatic brain injury and neurocognitive outcome: CT versus 3T MRI. J Neurotrauma. 2008;25(9):1049-1056.
32. Scheid R, Walther K, Guthke T, Preul C, von Cramon DY. Cognitive sequelae of diffuse axonal injury. Arch Neurol. 2006;63(3):418-424.
33. Scheid R, von Cramon DY. Clinical findings in the chronic phase of traumatic brain injury: Data from 12 years’ experience in the cognitive neurology outpatient clinic at the university of leipzig. Dtsch Arztebl Int. 2010;107(12):199-205.
34. Chung SW, Park YS, Nam TK, Kwon JT, Min BK, Hwang SN. Locations and clinical significance of non-hemorrhagic brain lesions in diffuse axonal injuries. J Korean
Neurosurg Soc. 2012;52(4):377-383.
35. Moen KG, Brezova V, Skandsen T, Haberg AK, Folvik M, Vik A. Traumatic axonal injury: The prognostic value of lesion load in corpus callosum, brain stem, and thalamus in different magnetic resonance imaging sequences. J Neurotrauma. 2014;31(17):1486-1496.
36. Marquez de la Plata C, Ardelean A, Koovakkattu D, et al. Magnetic resonance imaging of diffuse axonal injury: Quantitative assessment of white matter lesion volume. J Neurotrauma. 2007;24(4):591-598.
37. Calvi MR, Beretta L, Dell’Acqua A, Anzalone N, Licini G, Gemma M. Early prognosis after severe traumatic brain injury with minor or absent computed tomography scan lesions. J Trauma. 2011;70(2):447-451.
38. Skandsen T., Moen K.G., Folvik M., Kvistad K.A., Rydland J., Vik A. Magnetic resonance imaging of diffuse axonal injury. serial quantitative assessment and relation to patient outcome. . 2012.
39. Jeong JH, Kim YZ, Cho YW, Kim JS. Negative effect of hypopituitarism following brain trauma in patients with diffuse axonal injury. J Neurosurg. 2010;113(3):532-538. 40. Sharp DJ, Ham TE. Investigating white matter injury after mild traumatic brain
injury. Curr Opin Neurol. 2011;24(6):558-563.
41. Chastain CA, Oyoyo UE, Zipperman M, et al. Predicting outcomes of traumatic brain injury by imaging modality and injury distribution. J Neurotrauma. 2009;26(8):1183-96.
42. Hunter JV, Wilde EA, Tong KA, Holshouser BA. Emerging imaging tools for use with traumatic brain injury research. J Neurotrauma. 2012;29(4):654-71.
43. Huston JM, Field AS. Clinical applications of diffusion tensor imaging. Magn Reson
Imaging Clin N Am. 2013;21(2):279-298.
44. Bazarian JJ, Zhong J, Blyth B, Zhu T, Kavcic V, Peterson D. Diffusion tensor imaging detects clinically important axonal damage after mild traumatic brain injury: A pilot study. J Neurotrauma. 2007;24(9):1447-1459.
45. Benson RR, Meda SA, Vasudevan S, et al. Global white matter analysis of diffusion tensor images is predictive of injury severity in traumatic brain injury.
J Neurotrauma. 2007;24(3):446-459.
46. Yuh EL, Cooper SR, Mukherjee P, et al. Diffusion tensor imaging for outcome prediction in mild traumatic brain injury: A TRACK-TBI study. J Neurotrauma. 2014;31(17):1457-1477.
47. Huisman TAGM, Sorensen AG, Hergan K, Gonzalez RG, Schaefer PW. Diffusion-weighted imaging for the evaluation of diffuse axonal injury in closed head injury. J Comput Assist Tomogr. 2003;27(1):5-11.
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Chapter 3
Patients with diffuse axonal injury
can recover to a favourable long-term
functional and quality of life outcome
Chapter 3 Long-term functional and quality of life outcome
ABSTRACT
Objective Functional outcome and quality of life are difficult to predict in patients
with diffuse axonal injury (DAI) after traumatic brain injury (TBI). The primary aim of this cross-sectional cohort study was to assess the long-term functional outcome in patients with DAI and to identify prognostic factors. Secondly, health-related quality of life (HRQL) at long-term follow-up was assessed.
Methods Patients aged ≥16 with TBI and DAI (admitted 2008-2014) were included.
Clinical and imaging data were collected. The primary outcome parameter was the Glasgow Coma Scale Extended (GOSE) at long-term follow-up. Secondly, the HRQL was assessed with the Quality Of Life after Brain Injury (Qolibri) questionnaire.
Results DAI was diagnosed in 185 patients. Long-term functional outcome was
obtained in 134 patients (72%), median follow-up 54 months (range 14-100). 51% had a favourable outcome (GOSE 6-8). Independent prognostic factors were age, pupillary reaction, Hb, DAI grading, and return of consciousness ≤7 days. Sixty-two percent had a good HRQL, after a median follow-up of 57 months (range 14-100) with age as an independent prognostic factor.
Conclusions More than half of patients with DAI had a favourable functional
outcome and a good HRQL at long-term follow-up. Also in patients with a DAI grade 3 a favourable outcome was seen. HRQL is a clinically relevant outcome measure since it reflects perceived outcome by patients. Independent prognostic variables for the functional outcome were factors obtained in the acute phase after injury, whereas age was an independent prognostic factor for HRQL.
Key words: Diffuse Axonal Injury, Traumatic Brain Injury, GOSE, Qolibri, health
related quality of life
INTRODUCTION
For patients with diffuse axonal injury (DAI) after traumatic brain injury (TBI) prognosis, in terms of functional outcome and quality of life, is not clear. It is uncertain whether the patient will remain in a vegetative state, or will be able to participate in a working environment again. In the (sub)acute phase after injury, patients and their relatives are in need of more individualized information concerning long-term prognosis.
DAI is the result of tearing of axons caused by acceleration-deceleration forces during trauma.1 After sustaining fatal TBI, DAI is present in all patients, however it occurs also in mild, moderate and severe TBI.2,3 DAI can be diagnosed with magnetic resonance imaging (MRI), the most used MRI grading for DAI represents the depth of the lesions in 3 grades: 1) cortical, 2) corpus callosum, and 3) brainstem.4 Prior research indicates DAI to be a prognostic factor for an unfavourable outcome.5 A higher grade of DAI is associated with a higher mortality and a higher risk of an unfavourable functional outcome.6-8 However, this association does not result in a reliable individual prognosis assessment in clinical practice.
The use of prognostic models, such as the IMPACT and CRASH, have improved prognosis estimates in patients with TBI.9,10 Both models use clinical data and Computed Tomography (CT) imaging data to predict outcome after TBI. Although the presence of DAI on the MRI is a prognostic factor, in neither of these models MRI specific factors were included. Since DAI specific clinical or MRI features may affect prognosis, a prognostic model focussing solely on DAI patients would provide the opportunity to predict more specifically functional outcome and quality of life for the individual patient with DAI.
Outcome is often defined as functional outcome or as the scores on neurocognitive tests. The ‘quality of life after brain injury’ (Qolibri) questionnaire provides the opportunity to assess disease-specific health-related quality of life (HRQL) in patients with brain injury.11 With this instrument the perceived patient outcome can be measured. Outcome defined as HRQL after TBI in patients with MRI proven DAI has not yet been addressed.
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The primary aim of this cross-sectional cohort study, was to assess long-term functional outcome in patients with DAI and to identify prognostic factors. Second, we aimed to assess the perceived outcome of patients with DAI by determining the HRQL at the long-term follow-up.
MATERIALS AND METHODS
Study designIn this cross-sectional study, we studied all patients with DAI admitted to one of the participating Dutch level I trauma centres (St. Elisabeth Hospital (EH) or University Medical Centre Groningen (UMCG)) during a seven year period (January 1, 2008, to December 31, 2014). Patients with TBI, age ≥16 at the time of the injury, and with DAI on the MRI (which was performed <6 months after the injury) were included. DAI was defined as microbleeds on the MRI, either on Fast Field Echography (FFE) or on T2 Stir Gradient Echo Resonance (T2*GRE). Exclusion criteria were MRI artefacts impairing diagnostics, large cerebral infarction, pre-existent mental retardation, and other neurological conditions that affect long-term follow-up
Data collection and analysis
Clinical data were extracted from the electronic medical records, comprising: age, trauma mechanism, initial Glasgow Coma Score (GCS), length of Intensive Care Unit (ICU), return of consciousness (defined as a motor score of M6), and hospital admittance. Also the imaging data such as, the Marshall score of the first performed CT (Computed Tomography) scan, the timing and field strength of the MRI, and the result of the MRI. The long-term follow-up was assessed prospectively and consisted of the Glasgow Outcome Scale Extended (GOSE) and the Qolibri.
The GOSE is a functional outcome scale with 8 categories, from 1= death to 8= good recovery. A score of ≥6 resembles participation in a working environment and is considered a favourable outcome.12 The Qolibri is a validated questionnaire assessing HRQL in patients with TBI. With 37 questions a maximum score of 100 can be obtained, from 0 = very poor quality of life to 100 = very good quality of life.11,13 A total score of ≥60 is considered a good quality of life.14
The patients were contacted by telephone and a structured telephone interview was assessed to complete the GOSE. The Qolibri was sent by mail after the telephone interview. The GOSE could be obtained either from the patient or a relative, while the Qolibri had to be filled out by the patient. The researcher was blinded for the DAI grading of the patients. When patients repeatedly could not be contacted by telephone, both the Qolibri and GOSE were sent by mail.
Image technique
In the EH the MRI scans were performed on a 1Tesla (T) MRI (only in 2008), a 1.5T MRI (2009-2014), and a 3T MRI (2011-2014) (all Phillips Medical Systems). The scanning protocol differed over time and per MRI scanner, however in all patients FFE imaging was performed as well as T2 sagittal imaging. Diffusion Weighed Imaging was performed when cerebral ischemia was suspected. In the UMCG all the MRI scans were performed on a 1.5T scanner (Siemens Medical Systems), T2*GRE and T2 sagittal imaging were performed in all patients. All MRI scans were initially assessed by a neuroradiologist and reassessed for DAI grading by a researcher (ME), in case of inconclusive assessment a neuroradiologist (JP) was consulted.
Ethical approval
The study did not meet the criteria for medical scientific research, according to the Dutch Medical Research Involving Human Subject Act (1998). The study-protocol was presented to the Medical Ethical Committee Brabant in The Netherlands, which on these grounds deemed no further ethical evaluation necessary. Patients and/or their representatives were asked for a written informed consent for participation in the study.
Statistical analysis
First, a univariable analysis comparing putative risk factors with the functional outcome, GOSE, as ordinal outcome measure was performed. Proportional odds logistic regression was used to calculate the Odds Ratio (OR) with 95% Confidence Interval (CI).15 Next, a multivariable proportional odds logistic regression analysis was performed. Variables with a p-value of p<0.20 in the univariable analyses were included in the multivariable analysis. For the multivariable analyses, a backward elimination procedure was performed to define the final independent risk factors. Variables were eliminated from the model if the p-value was p >0.10.16
Chapter 3 Long-term functional and quality of life outcome
Second, univariable linear regression analysis with the HRQL (Qolibri) as continuous dependent factor was performed. The β-coefficient with 95% CI was calculated. A step backward multivariable linear regression analysis was performed on variables with a p-value of p<0.20 in the univariable analysis. Variables were eliminated from the model if the p-value was p>0.10.
Finally, we explored the relation between the functional outcome and the HRQL in the surviving patients. The GOSE and Qolibri outcomes were dichotomized in favourable and unfavourable outcome. First, a Pearson correlation was calculated. Second, a binary logistic regression with the GOSE as dependant variable was performed to calculate the OR with 95% CI.
Statistical analyses were performed with IBM SPSS Statistics version 24.
Missing data
The data were checked and missing variables were completed when possible. After assessment of the randomness of the missing data, multiple imputation was performed. The putative prognostic variables were included in the multiple imputation model and missing data were imputed. The outcome variables (GOSE and Qolibri) were included as a predictor in the imputation model, these values were not imputed.17 The number of imputations (m) was defined by the highest percentage of missing data per variable.18 This was 13% in the variable pupillary reaction, therefore we imputed the data 15 times (m=15).
RESULTS
PatientsA total of 714 patients with TBI had an MRI scan of the brain. In 185 patients DAI was proven on an MRI scan performed within 6 months after trauma, eight patients were excluded for further analysis. In flowchart 1 the selection process and outcomes were presented. Within this DAI cohort, 63% of patients had severe TBI (admission GCS 3-8), 22% had moderate TBI (GCS 9-12) and 15% had mild TBI (GCS 13-15). The main cause of the TBI was high energy trauma in traffic. Cranial neurosurgical intervention was performed in 21 patients (decompression (n=11), evacuation of an epidural (n=4) and/or a subdural (n=7) hematoma, depressed skull fracture (n=2), and extra ventricular drainage (n=1)). 158 patients (89%) were admitted to
the ICU, the duration of ICU admission was median 11.0 days (0-100 days). The median duration of the hospital admission was 25 days (range 1-179), a higher DAI grading resulted in a longer hospital stay (DAI 1: median 17 days (range 1-77), DAI 2 median 29 days (range 4-94), and DAI 3 median 31 days (range 2-179)). The patient characteristics were summarized in table 1.
Flowchart 1. Patient selection and outcome
*Qolibri collection possible in 155 patients (22 deceased) Abbreviations: EH: Elisabeth Hospital, UMCG: University Medical Centre Groningen, TBI: Traumatic Brain Injury, DAI: Diffuse Axonal Injury, MRI: Magnetic Resonance Imaging, GOSE: Glasgow Outcome Score Extended, Qolibri: Quality of life after brain injury, Med FU: Median follow-up.
