Karl A Zimmerman1,2, Etienne Laverse3, Ravjeet Samra1, Maria Yanez Lopez4, Amy E Jolly1,2, Niall J Bourke1,2, Neil S N Graham1,2, Maneesh C Patel5, John Hardy6, Simon Kemp7,8, Huw R Morris3, David J Sharp1,2,9. 1. Computational, Cognitive and Clinical Neuroimaging Laboratory, Division of Brain Sciences, Hammersmith Hospital, Imperial College London, London W12 0NN, UK. 2. Care Research & Technology Centre, UK Dementia Research Institute, London W12 0BZ, UK. 3. Department of Clinical and Movement Neuroscience, University College London, London NW3 2PF, UK. 4. Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK. 5. Imaging Department, Imperial College Healthcare NHS Trust, Charing Cross Hospital, London W6 8RF, UK. 6. Department of Neurodegenerative Disease, Reta Lila Weston Laboratories, Queen Square Genomics, UCL Dementia Research Institute, London WC1N 3BG, UK. 7. Rugby Football Union, Twickenham, London TW2 7BA, UK. 8. Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK. 9. The Royal British Legion Centre for Blast Injury Studies, Imperial College London SW7 2AZ, UK.
Abstract
The recognition, diagnosis and management of mild traumatic brain injuries are difficult and confusing. It is unclear how the severity and number of injuries sustained relate to brain injuries, such as diffuse axonal injury, diffuse vascular injury and progressive neurodegeneration. Advances in neuroimaging techniques enable the investigation of neuropathologies associated with acute and long-term effects of injury. Head injuries are the most commonly reported injury seen during professional rugby. There is increased vigilance for the immediate effects of these injuries in matches, but there has been surprisingly little research investigating the longer-term effects of rugby participation. Here, we present a longitudinal observational study investigating the relationship of exposure to rugby participation and sub-acute head injuries in professional adult male and female rugby union and league players using advanced MRI. Diffusion tensor imaging and susceptibility weighted imaging was used to assess white matter structure and evidence of axonal and diffuse vascular injury. We also studied changes in brain structure over time using Jacobian Determinant statistics extracted from serial volumetric imaging. We tested 41 male and 3 female adult elite rugby players, of whom 21 attended study visits after a head injury, alongside 32 non-sporting controls, 15 non-collision-sport athletic controls and 16 longitudinally assessed controls. Eighteen rugby players participated in the longitudinal arm of the study, with a second visit at least 6 months after their first scan. Neuroimaging evidence of either axonal injury or diffuse vascular injury was present in 23% (10/44) of players. In the non-acutely injured group of rugby players, abnormalities of fractional anisotropy and other diffusion measures were seen. In contrast, non-collision-sport athletic controls were not classified as showing abnormalities. A group level contrast also showed evidence of sub-acute injury using diffusion tensor imaging in rugby players. Examination of longitudinal imaging revealed unexpected reductions in white matter volume in the elite rugby players studied. These changes were not related to self-reported head injury history or neuropsychological test scores and might indicate excess neurodegeneration in white matter tracts affected by injury. Taken together, our findings suggest an association of participation in elite adult rugby with changes in brain structure. Further well-designed large-scale studies are needed to understand the impact of both repeated sports-related head impacts and head injuries on brain structure, and to clarify whether the abnormalities we have observed are related to an increased risk of neurodegenerative disease and impaired neurocognitive function following elite rugby participation.
The recognition, diagnosis and management of mild traumatic brain injuries are difficult and confusing. It is unclear how the severity and number of injuries sustained relate to brain injuries, such as diffuse axonal injury, diffuse vascular injury and progressive neurodegeneration. Advances in neuroimaging techniques enable the investigation of neuropathologies associated with acute and long-term effects of injury. Head injuries are the most commonly reported injury seen during professional rugby. There is increased vigilance for the immediate effects of these injuries in matches, but there has been surprisingly little research investigating the longer-term effects of rugby participation. Here, we present a longitudinal observational study investigating the relationship of exposure to rugby participation and sub-acute head injuries in professional adult male and female rugby union and league players using advanced MRI. Diffusion tensor imaging and susceptibility weighted imaging was used to assess white matter structure and evidence of axonal and diffuse vascular injury. We also studied changes in brain structure over time using Jacobian Determinant statistics extracted from serial volumetric imaging. We tested 41 male and 3 female adult elite rugby players, of whom 21 attended study visits after a head injury, alongside 32 non-sporting controls, 15 non-collision-sport athletic controls and 16 longitudinally assessed controls. Eighteen rugby players participated in the longitudinal arm of the study, with a second visit at least 6 months after their first scan. Neuroimaging evidence of either axonal injury or diffuse vascular injury was present in 23% (10/44) of players. In the non-acutely injured group of rugby players, abnormalities of fractional anisotropy and other diffusion measures were seen. In contrast, non-collision-sport athletic controls were not classified as showing abnormalities. A group level contrast also showed evidence of sub-acute injury using diffusion tensor imaging in rugby players. Examination of longitudinal imaging revealed unexpected reductions in white matter volume in the elite rugby players studied. These changes were not related to self-reported head injury history or neuropsychological test scores and might indicate excess neurodegeneration in white matter tracts affected by injury. Taken together, our findings suggest an association of participation in elite adult rugby with changes in brain structure. Further well-designed large-scale studies are needed to understand the impact of both repeated sports-related head impacts and head injuries on brain structure, and to clarify whether the abnormalities we have observed are related to an increased risk of neurodegenerative disease and impaired neurocognitive function following elite rugby participation.
Mild traumatic brain injuries (mTBIs) are common, with a global incidence of
45–54 million per year. Sport-related mTBIs account for 15–20% of
these injuries requiring treatment in the USA., They are often considered relatively harmless. However,
symptoms can persist after injuries that appear relatively trivial and animal models show persistent brain injury
after mTBI. Some types of
neuropathology, such as diffuse axonal injury (DAI), are under-recognised by
conventional diagnostic imaging and repeated mTBI has been associated with
neurodegenerative diseases, such as chronic traumatic encephalopathy (CTE). Hence, detailed investigation of the
long-term effects of repeated sports mTBI on brain health is important.Rugby is a high-intensity collision team sport played in over 120 countries by over 9
million people and is
split into Rugby Union and Rugby League. In professional rugby union in the UK, mTBI
is the most common reported match injury (∼20% of injuries) with an
incidence of 20.4 per 1000 h. In Australia, the rate of mTBI in the National Rugby
League (NRL) was estimated to be 14.8 per 1000 player match hours. Despite relatively high
rates of head injury and an increasing focus on prevention in the form of law
variations and
player preparation,
there has been relatively little research investigating the long-term effects of
rugby participation. Previous work in retired rugby players has found evidence of a
limited effect of higher self-reported rates of depression and mild cognitive
impairment compared to controls.
However, rates of dementia in the retired rugby player population are not
necessarily different from control levels. CTE has recently been reported in a small number of
ex-players: two in rugby league and four in rugby union., Therefore, further research is needed to
understand whether exposure to rugby participation and head injuries experienced
during a rugby career are sufficient to lead to lasting brain injury.Neuroimaging is key to the investigation of traumatic brain injury (TBI). Standard CT
and MRI often appear normal after mTBI. However, white matter injuries can be more sensitively
identified using advanced magnetic resonance imaging (MRI) sequences, such as
diffusion MRI and susceptibility weighted imaging (SWI). DAI
causes many of the long-term effects of TBI. It can be sensitively identified by
diffusion MRI. Abnormalities in the directionality of water diffusion, most commonly
quantified using changes in fractional anisotropy (FA), provide information about
the location and severity of DAI. White matter FA increases acutely and subsequently
reduces in the presence of longer-term damage. FA and
other diffusion metrics provide: (i) a validated measure of white matter integrity
after TBI in animals models of TBI e.g. Mac Donald et al.; (ii) increased sensitivity to DAI
compared to conventional MRI; and (iii) information that helps predict long-term
clinical outcome after TBI, including the type of post-traumatic problems that
develop.,Diffusion abnormalities have been demonstrated in a range of sporting mTBI types,
however, the direction of change is inconsistent. In mixed sport cohorts, ice hockey
players and American Footballers, FA has been shown to increase acutely after a
sports mTBI. This elevation has been attributed to increased
anisotropy caused by cerebral oedema., In several studies, these changes persist in the
chronic stage,,, particularly in cohorts of younger athletes. In
others, including studies of boxers, FA is observed to be decreased relative to
controls in the chronic stages after a sports mTBI, similar to changes observed in non-sport mTBI
and moderate-severe TBI. Several studies do not find abnormalities in FA as a result
of sports mTBI. Few studies investigate solely a population of
rugby players with diffusion tensor imaging (DTI). In 73 non-injured female
varsity and 11
retired rugby league players, evidence of reduced FA as well as elevated diffusivity was
observed in both studies.SWI provides additional information about the presence of diffuse vascular injury
(DVI). Gross
intracerebral haemorrhage identifiable on CT is relatively uncommon following sports
mTBI. However, more subtle DVI can occur and may be missed on conventional imaging.
DVI produces small peri-venular haemorrhages that are seen as petechial
microhaemorrhages on SWI. Post-traumatic microhaemorrhages are associated with more
cognitive impairment and worse clinical outcomes., However, studies utilizing SWI in a
sporting context are very limited. The majority of studies in boxing, ice hockey and
American Football have found little to no evidence of abnormal microhaemorrhage
prevalence in athletes. Currently, there exist no studies of rugby
players using SWI.In addition to the acute effects of sport mTBI, repeated head impacts can lead to
progressive neurodegeneration.,, Therefore, an important question is to what extent
different sports accelerate neurodegeneration and increase the risk of dementia.
Most recent research has focussed on sports, such as American Football and boxing,
where the long-term risks of CTE and other types of dementia have been clearly
demonstrated.,,, The neurodegenerative risks of other sports are less
clear and the prevalence of sports related dementia is generally uncertain as is the
dose of head injury exposure needed to accelerate neurodegeneration. Recent work has
demonstrated a surprisingly large increase in the risk of dementia, in particular
Alzheimer’s disease, in deceased association football players. In rugby, CTE pathology
has been reported in small case studies of ex-rugby players,, but the prevalence and consequences of
neurodegenerative pathology in rugby players are unclear.The presence of neurodegeneration can be studied using serial MRI. Brain atrophy is a
common end-point of various types of neurodegeneration. This is routinely used in
the assessment of dementia and can be sensitively measured using longitudinal brain
scanning. Serial structural imaging can be used to generate metrics of volume change
over time, such as the Jacobian Determinant (JD). White matter volume changes are highly
dependent on age. Volumes increase in children and young adults, before declining in
older age., The normal development and ageing of the white matter
can be affected by TBI. Atrophy is increased after single moderate-severe TBI, is more prominent in the
depths of sulci where CTE pathology occurs and is associated with poorer clinical outcomes. In other neurodegenerative diseases, atrophy
measured by MRI has been histologically validated at post-mortem. Hence, serial MRI
provides a method of sensitively assessing whether neurodegeneration is taking place
and mapping its spatial pattern, which may give an indication of the underlying
pathological process.Here, we report a longitudinal observational study of 41 male and 3 female elite
rugby union and league players using repeated diffusion, susceptibility weighted and
volumetric MRI to measure DAI, DVI and brain atrophy, respectively. We test the
hypotheses that participation in elite rugby will be associated with: (i) evidence
of DAI measured by diffusion MRI; (ii) evidence of DVI measured by SWI; and (iii)
evidence of abnormal white matter tract development and/or increased brain atrophy,
measured by longitudinal changes in brain volume. To investigate the acute and
long-term impact of rugby participation, players were recruited with or without a
recent history of mTBI. Players were compared against sporting and non-sporting
controls to investigate whether imaging abnormalities were associated with
participation in high intensity sporting activity.
Materials and methods
Subjects
Thirty-seven elite male and three female rugby union players, and four male rugby
league players were recruited from professional rugby clubs in the UK [mean age
25.2, standard deviation (SD) = 3.5, 41 males, 3 females]. Twenty-eight
players had baseline study visits without an acute injury, while 21 players
attended study visits shortly after a head injury as determined by medical
professionals in line with Rugby Union and Rugby League guidelines. All head
injuries met the Mayo Clinic classification of mild—probable TBI . Post-injury study
visits for injured players were performed a maximum of 7 days after
injury [mean days 4.7, SD = 1.2]. All study visits included an MRI
assessment and battery of neuropsychological tests. Five players had both a
baseline non-injury study visit and a study visit following a head injury (Fig. 1). Eighteen rugby players
attended a second assessment a mean of 12.1 months later. Inclusion
criteria were age 16–45, active rugby players with exclusion criteria
comprising other major neurological or psychiatric issues (e.g. substance abuse,
previous moderate-severe TBI) or contraindication to MRI.
Figure 1
Overview of study cohorts. Thirty-seven elite male and three female rugby
union players, and 4 male rugby league players were recruited from
professional rugby clubs in England. Twenty-eight players had baseline
study visits without an acute injury, while 21 players attended study
visits shortly after a head. Post-injury study visits for acutely
injured players were performed a maximum of 7 days after injury.
Five players had both a baseline non-injury study visit and a study
visit following an acute head injury, and 18 rugby players attended a
second assessment. Three control groups were recruited to the study,
including a Non-Sport and Sport Control group for cross-sectional
comparison, and a separate group of Longitudinal Controls for
longitudinal comparison. Longitudinal Controls only completed the
structural imaging components of the study.
Overview of study cohorts. Thirty-seven elite male and three female rugby
union players, and 4 male rugby league players were recruited from
professional rugby clubs in England. Twenty-eight players had baseline
study visits without an acute injury, while 21 players attended study
visits shortly after a head. Post-injury study visits for acutely
injured players were performed a maximum of 7 days after injury.
Five players had both a baseline non-injury study visit and a study
visit following an acute head injury, and 18 rugby players attended a
second assessment. Three control groups were recruited to the study,
including a Non-Sport and Sport Control group for cross-sectional
comparison, and a separate group of Longitudinal Controls for
longitudinal comparison. Longitudinal Controls only completed the
structural imaging components of the study.Injury characteristics, including the total numbers of symptoms after injury and
symptomatic days as well as the duration the player remained in the return to
play protocol were recorded. Any head injuries in rugby union that met criteria
for permanent immediate removal from play (e.g. loss of consciousness or ataxia
as previously described) were documented. Acutely injured players completed
the SCAT-5 which includes a cognitive and neurological screen, and a symptom
evaluation (symptom severity score out of 132). For all players, head injury
history and length of professional career were collected from the professional
sporting body, and where gaps existed, from players and the club. Self-reported
alcohol intake was also recorded (Supplementary Table 1).Healthy controls were screened according to the same exclusion criteria and were
required to additionally have no self-reported history of mTBI. Three control
groups were recruited to the study, including a Non-Sport and Sport Control
group for cross-sectional comparison, and a separate group of Longitudinal
Controls for longitudinal comparison. The Non-Sport Control group were a cohort
of controls not playing sports at university or professional competition level.
The Sport Controls group were a cohort of non-collision sport athletes recruited
from university sport clubs. Inclusion criteria for the Sport Controls were age
16–45, active athletes at least 6 h of exercise per week with
additional exclusion criteria of history of playing collision sports
competitively. This included representing their high school competitively in
rugby or soccer. Sport Controls comprised of 3 swimmers, 1 water polo player, 9
rowers, 1 cyclist and 1 weight lifter, with a median hours of exercise per week
of 12 (IQR = 6.9). The Longitudinal Control group were the
third cohort of controls and comprised of individuals who had participated in a
longitudinal imaging study of outcomes after TBI which used aligned imaging and
exclusion protocols.
Longitudinal Controls only completed the structural imaging components of the
study.Recruitment was coordinated by local research facilities at the Hammersmith
Hospital. All study participants provided written informed consent in accordance
with the Declaration of Helsinki. Ethical approval was approved by the
University College London research ethics committee (7385/001).
Neuropsychological testing
Established paper neuropsychological tests sensitive to impairments after
TBI were
administered during study visits, including the Test of Premorbid Functioning
(TOPF), Trail Making Test (TMT), Delis-Kaplan Executive Function System (D-KEFS
Stroop), Hopkins Verbal Learning-Test (HVLT) and the Brief Visuospatial Memory
Test-Revised (BVMT). Participants also completed a battery of cognitive tasks on
an IPad as part of a subset of previously studied and described tasks., These included
Visuospatial Working Memory, Paired Associates and Self-Ordered Search, Feature
Match, Odd One Out and Spatial Planning. A visuospatial memory
Fractals task on a touchscreen computer was also completed
following a previously described protocol.
MRI acquisition
Participants were scanned with the following sequences: resolution structural
T1-weighted MPRAGE with voxel dimensions of 1 mm3 (160 slices, matrix
= 208 × 208, repetition time = 2300 ms, echo time
= 2.98 ms, flip angle = 9°, FOV = 256
× 256 mm, GRAPPA = 2), T2 FLAIR (Fluid
attenuated inversion recovery), T2 SWI (120 1.2-mm-thick transverse
slices, TR = 28 ms, TE = 20 ms, FA =
15°, in-plane resolution = 0.8 × 0.6 mm, field of
view = 225 × 225 mm) and DTI using a multishell 99
direction protocol (66 slices, isotropic 2 mm3 voxels, field of view
= 25.6 cm × 25.6 cm, TR = 5000 ms, TE
= 85 ms, b-value 1 = 700 s/mm2
with 30 directions, b-value 2 = 2000 s/mm2 with
60 directions, 6 direction b-value = 0 s/mm2 and
6 reverse phase encoding direction b-value = 0
s/mm2 volumes).Longitudinal controls were scanned with the same structural sequences.
Participants were all scanned on a Siemens 3T Verio (Siemens Healthcare) scanner
using a 32-channel head coil. All scans were examined by a consultant
neuroradiologist for the presence of focal lesions or microbleeds.
Neuroimaging analysis
Diffusion data processing
Diffusion weighted images were processed following the standard TBSS pipeline
in the FMRIB Software Library (version 5.0.8), including correcting
susceptibility and eddy current induced distortions and diffusion tensor fitting
(Fig. 2). Freesurfer was used to skull
strip brains and remove non-brain voxels from the field map. Tensor-based
registration was performed using DTI-TK involving the creation of a group
template using affine and non-linear diffeomorphic registrations followed by
registration of participant diffusion imaging to the template. Images were
warped to 1 mm isotropic space and the mean FA map produced was
thresholded at 0.2 to produce a white matter skeleton. Subject FA and mean
diffusivity (MD) data were projected onto the mean FA skeleton and tract
level data generated using the Johns Hopkins University (JHU) white matter
atlas. Neurite density index (NDI), orientation dispersion index (ODI) and
isotropic volume fraction (ISOVF) maps were generated using NODDI modelling
using the Accelerated Microstructure Imaging via Convex Optimization (AMICO)
framework.
NDI, ODI and ISOVF maps were registered to DTI-TK-space using the
transformation matrix generated during the DTI-TK pipeline. Images were
visually inspected at the brain extraction, eddy current correction and
tensor registration stage. Subjects with poor quality data or un-correctable
artefacts were removed.
Figure 2
Overview of study methods. (A) Image processing of
diffusion data followed the standard TBSS pipeline, including
correcting for susceptibility and eddy current induced distortions
and diffusion tensor fitting. Freesurfer was used to skull strip
brains and remove non-brain voxels from the field map. Tensor-based
registration was performed using DTI-TK involving the creation of a
group template using affine and non-linear diffeomorphic
registrations followed by registration of participant diffusion
imaging to the template. Images were all warped to 1 mm
isotropic space and the mean fractional anisotropy map produced was
thresholded at 0.2 to produce a white matter skeleton. Subject
fractional anisotropy and mean diffusivity data were projected onto
the skeleton and tract level data generated using the Johns Hopkins
University white matter atlas. Neurite density index (NDI),
orientation dispersion index (ODI) and isotropic volume fraction
(ISOVF) maps were generated using NODDI modelling using the
Accelerated Microstructure Imaging via Convex Optimization (AMICO)
framework. NDI, ODI and ISOVF maps were registered to DTI-TK-space
using the transformation matrix generated during the DTI-TK
pipeline. Images were visually inspected at the brain extraction,
eddy current correction and tensor registration stage for quality
control checks. Image processing of cross-sectional structural data
used SPM to segment T1 images into tissue probability maps. A
study-specific template was generated using DARTEL registration for
non-linear spatial normalization and then affine registered to
MNI152 space. All images were then normalized to MNI152 space via
the study template. (B) Processing of longitudinal
structural images involved within-subject registration of baseline
and follow-up images and generation of a within-subject temporal
average image and Jacobian determinant image. The Jacobian
determinant image represented a voxelwise statistic of spatial
expansion and contraction required to match baseline and follow-up
images. Average images were then segmented into grey and white
matter and Jacobian determinant images normalized by tissue
probability. A study-specific longitudinal template was generated
with DARTEL and affine registered to MNI152 space. Individual
average images were then normalized to MNI152 space via the
longitudinal study template. (C) Statistical analysis
was carried out in both a region of interest and voxelwise manner.
Region of interest analysis involved sampling of mean diffusion and
structural metrics of interest within pre-defined regions of
interest in spatially standardized images. Voxelwise analysis was
carried out using Randomise (FSL) with 5000 permutations using the
threshold-free cluster enhancement and adjusting for age, gender and
intracranial volume (cross-sectional structural only).
Overview of study methods. (A) Image processing of
diffusion data followed the standard TBSS pipeline, including
correcting for susceptibility and eddy current induced distortions
and diffusion tensor fitting. Freesurfer was used to skull strip
brains and remove non-brain voxels from the field map. Tensor-based
registration was performed using DTI-TK involving the creation of a
group template using affine and non-linear diffeomorphic
registrations followed by registration of participant diffusion
imaging to the template. Images were all warped to 1 mm
isotropic space and the mean fractional anisotropy map produced was
thresholded at 0.2 to produce a white matter skeleton. Subject
fractional anisotropy and mean diffusivity data were projected onto
the skeleton and tract level data generated using the Johns Hopkins
University white matter atlas. Neurite density index (NDI),
orientation dispersion index (ODI) and isotropic volume fraction
(ISOVF) maps were generated using NODDI modelling using the
Accelerated Microstructure Imaging via Convex Optimization (AMICO)
framework. NDI, ODI and ISOVF maps were registered to DTI-TK-space
using the transformation matrix generated during the DTI-TK
pipeline. Images were visually inspected at the brain extraction,
eddy current correction and tensor registration stage for quality
control checks. Image processing of cross-sectional structural data
used SPM to segment T1 images into tissue probability maps. A
study-specific template was generated using DARTEL registration for
non-linear spatial normalization and then affine registered to
MNI152 space. All images were then normalized to MNI152 space via
the study template. (B) Processing of longitudinal
structural images involved within-subject registration of baseline
and follow-up images and generation of a within-subject temporal
average image and Jacobian determinant image. The Jacobian
determinant image represented a voxelwise statistic of spatial
expansion and contraction required to match baseline and follow-up
images. Average images were then segmented into grey and white
matter and Jacobian determinant images normalized by tissue
probability. A study-specific longitudinal template was generated
with DARTEL and affine registered to MNI152 space. Individual
average images were then normalized to MNI152 space via the
longitudinal study template. (C) Statistical analysis
was carried out in both a region of interest and voxelwise manner.
Region of interest analysis involved sampling of mean diffusion and
structural metrics of interest within pre-defined regions of
interest in spatially standardized images. Voxelwise analysis was
carried out using Randomise (FSL) with 5000 permutations using the
threshold-free cluster enhancement and adjusting for age, gender and
intracranial volume (cross-sectional structural only).
Subject-level diffusion analysis
Mean FA was calculated for selected large white matter tracts based on tract
size, reproducibility and sensitivity. The mean and standard deviation
of FA for each tract region of interest (ROI) across the Non-Sport Control
cohort was then used to calculate subject Z-scores for each
ROI. Z-scores were converted to P-values
(two-tailed, with 95% confidence interval) and corrected for multiple
comparisons across all tract ROIs using FDR. Abnormalities in
subjects’ FA were determined by tracts that have significantly lower
or higher FA in the subject compared to the control group,
P < 0.05, FDR corrected.
Subject-level and ROI analysis was only conducted for FA, and not other
diffusion metrics.
Voxelwise diffusion analysis
Voxelwise analysis of skeletonised diffusion metrics was conducted using the
general linear model with non-parametric permutation testing (5000) in FSL
Randomise.
Diffusion weighted voxelwise results reported are corrected for multiple
comparisons at a threshold of P < 0.05
with age and gender included as a nuisance covariate.
Cross-sectional structural data processing and analysis
Volumetric data were analysed using standard approaches (Fig. 2). SPM 12 (UCL) was used to segment T1
images into grey matter, white matter and CSF, and to calculate volumes of
these tissue classes at baseline and follow up. Cross-sectional analysis
involved the generation of a study template using SPM DARTEL non-linear
registration
before affine registration of segmented images to MNI152 space, with
normalization of volume and smoothing using an 8 mm kernel. Tract
level data were generated using eroded JHU white matter atlas’ masks
to sample tissue volumes. Cross-sectional voxelwise analyses were conducted
using non-parametric permutation testing (5000) with age, gender and
intracranial volume included as nuisance covariates.
Longitudinal structural data processing and analysis
Longitudinal volumetric analysis was performed using the SPM12 longitudinal
registration tool. Baseline and follow-up T1 images were iteratively
co-registered to produce a temporal average image, with the transformation
required to move from the baseline to follow-up image encoded in the JD of
the expansion/contraction at a voxel-wise level. JD was then weighted by the
interval between baseline and follow-up to give an annualized rate of change
and further weighted by tissue class. A study-specific template was
generated using SPM DARTEL’s non-linear registration and
tissue-specific JD images normalized to group space before affine
registration to MNI152 space with normalization of volume and smoothing
using an 8 mm kernel. Tract level data were generated using
skeletonised JHU white matter atlas’ masks in MNI152 space. Voxelwise
analysis was conducted using non-parametric permutation testing (5000) with
age included as a nuisance covariate and results reported are corrected for
multiple comparisons at a threshold of
P < 0.1. Voxelwise correlation between
JD and DTI metrics were conducted after registration of DTI images to MNI152
space, using non-parametric permutation testing (5000).
Statistical analysis
Whole brain summary and voxelwise measures were calculated by adding grey and
white matter tissue data. Summary measures of brain volume were normalized for
participant head-size by dividing them into total intracranial volume (grey
matter + white matter + CSF). Statistical tests were completed in
the open-source software package R . Planned analyses included the comparison of
demographics, neuropsychological performance and diffusion metrics in rugby
players and all controls as a group, and sub-analysis between sub-acutely
injured players and non-acutely injured players (Fig. 1). An individualized assessment of FA was
planned to identify abnormalities in DTI using methods previously described
. An analysis of
brain atrophy comparing rugby players and a sub-group of controls with
longitudinal data were also planned using previously described methods.Non-sport and sport control groups were combined as an ‘All
controls’ group for comparisons with the largest N. This
was done for a comparison of demographics, neuropsychological test performance
and voxelwise diffusion and cross-sectional volumetric imaging analyses. Further
sub-analyses were performed using the Sport and Non-Sport Control groups
individually to investigate the effect of sports participation and test if the
group-wise differences in diffusion measures remained. Rugby players were also
split into sub-acutely and non-acutely injured players to investigate the
effects of a sub-acute injury on neuropsychological performance and imaging
metrics. Longitudinal controls, who were not screened for sports participation,
were used for longitudinal volumetric imaging analyses comparisons against a
group of both sub-acutely and non-acutely injury players, combined to maintain
large enough group sizes for powering. A subgroup analysis was performed using
only male Rugby Union players and utilised the same methodology as the main
analyses but included only male non-sport and sport controls for cross-sectional
comparisons.Group differences between all rugby players and all controls in demographics and
neuropsychological performances were investigated using
t-tests, with effect sizes reported using Cohen’s d. The
effect of sub-acute injury and sports participation on neuropsychological test
performance was assessed using an analysis of variance with Tukey multiple
post
hoc comparisons of means. FDR correction for multiple
comparisons was used. Details on neuroimaging statistical analysis are detailed
in the neuroimaging section. Pearson’s correlation was used to test the
relationship between JD and FA, and between the neuropsychological test score
performances and neuroimaging metrics. Categorical variables were compared using
the Chi-squared test and effect sizes reported using Cramer’s V. In cases
where the normality assumption was violated, the Wilcoxon test was used. The
data were not manipulated to account for missing data and design and analysis
not prespecified publically.
Data availability
The data that support the findings of this study are available from the
corresponding author, upon reasonable request.
Results
From 26 July 2017 until 1 March 2019, 44 elite level rugby players were recruited
into the study. Twenty-one players were assessed shortly after a mild TBI that
was sustained whilst playing professional rugby. On average these players were
4.7 days post-injury. Sub-acutely injured players presented with a mean
symptom severity score of 10.3 on the SCAT-5 during their pitch side assessment
at the time of injury and had an average return to play duration of
7.2 days (Supplementary Table 1). Demographic and physical characteristics
were well matched between sub-acutely injured and non-acutely injured rugby
players. Eighteen rugby players attended a second assessment a mean of
12.1 months later and players who returned for a follow-up were not
significantly different in demographics, baseline neuropsychological test
performance or any imaging measures compared to players who did not return for
follow-up.Rugby players were compared to three control groups. A non-collision sport
cross-sectional (Sport Controls), a non-sport cross-sectional (Non-Sport
Controls) and non-sport longitudinal control group (Longitudinal Controls).
Sport Controls were younger than rugby players (t =
−3.44, P = 0.0022,
d = 1.05) with no difference in
proportion of males to females. Non-Sport Controls were well matched for age,
but had a lower proportion of males to female
(X2= 10.7,
P = 0.001,
V = 0.42) than the rugby players.
Longitudinal Controls were older than the rugby players who returned for their
longitudinal assessment (t = 6.28,
P < 0.001,
d = 2.16) but were matched for gender.
Alcohol intake was not significantly different between rugby players and
controls.
Rugby players showed lower neuropsychological test performance at
baseline
Rugby players as a group showed lower visual memory immediate recall
(t = 3.64,
P = 0.0083,
d = 0.99) and lower premorbid intelligence
scores (FSIQ; t = 3.2,
P = 0.030,
d = 0.99) compared to Non-Sport and Sport
controls as a single group (Non-Rugby controls) (Fig. 3). Rugby players also showed trends towards
slower performance on two tests of processing speed (Trails B, Trails B minus A)
and poorer performance on verbal memory immediate recall, however, these did not
survive correction for multiple comparisons. There were no differences between
players and controls in computerized testing performance or on measures of
executive function.
Figure 3
Neuropsychological performance in all controls and rugby players. Grouped
violin plots of rugby player and non-rugby control performance in select
neuropsychological tests. The width of the coloured area represents the
distribution of scores, with the mean defined by the black horizontal
lines. Independent samples t-tests were conducted, with
* = uncorrected
P < 0.05,
** = uncorrected
P < 0.01,
*** = uncorrected
P < 0.001.
Premorbid FSIQ is a composite score of intelligence, Trails B and Trails
B minus A are tests of speed of processing, Stroop InhSwi versus
CombiBase is a composite score indicative of executive function, BVMT
Total Recall and HVLT Total Recall are scores of immediate memory. BVMT,
Brief Visuospatial Memory Test; CombiBase, Combined Baseline; FSIQ, Full
Scale Intelligence Quotient; HVLT, Hopkins Verbal Learning Test; InhSwi,
Inhibition Switch.
Neuropsychological performance in all controls and rugby players. Grouped
violin plots of rugby player and non-rugby control performance in select
neuropsychological tests. The width of the coloured area represents the
distribution of scores, with the mean defined by the black horizontal
lines. Independent samples t-tests were conducted, with
* = uncorrected
P < 0.05,
** = uncorrected
P < 0.01,
*** = uncorrected
P < 0.001.
Premorbid FSIQ is a composite score of intelligence, Trails B and Trails
B minus A are tests of speed of processing, Stroop InhSwi versus
CombiBase is a composite score indicative of executive function, BVMT
Total Recall and HVLT Total Recall are scores of immediate memory. BVMT,
Brief Visuospatial Memory Test; CombiBase, Combined Baseline; FSIQ, Full
Scale Intelligence Quotient; HVLT, Hopkins Verbal Learning Test; InhSwi,
Inhibition Switch.
Neuropsychological test performance in rugby players was not influenced by
sub-acute injury
To assess if these differences were present in both sub-acutely injured players
and non-acutely injured players, and if there was an effect of sport
participation in controls, we compared baseline performance between the 4
groups. A significant effect of group was found for premorbid intelligence
scores (FSIQ; F(3,37) = 5.74,
P = 0.03). Post hoc tests
showed that these effects were driven by lower FSIQ scores in both sub-acutely
injured rugby players (P = 0.0035) and
non-acutely injured players (P = 0.0095)
when compared to Non-Sport Controls. There were trends towards effects of group
on visual memory immediate recall and verbal memory immediate recall, however,
these did not survive correction for multiple comparisons. There were no
differences between neuropsychological test scores of non-acutely and
sub-acutely injured rugby players at baseline, nor any differences between
baseline and follow-up scores within players who returned for a second
visit.
Abnormal white matter integrity in rugby players
White matter structure was assessed using diffusion, volumetric and
susceptibility weighted MRI scans. Three baseline DTI scans of rugby players and
2 Sport Control DTI scans were discarded after quality control checks. We
investigated the white matter structure at the individual level by calculating
the mean FA from a number of large white matter tract and the whole white matter
skeleton and comparing results to control ranges. This approach is illustrated
in the case study presented in Fig.
4. Conventional MRI of this rugby player with a sub-acute injury
showed no evidence of abnormalities. In contrast, FA averaged across specific
white matter tracts showed abnormalities in the genu of the corpus callosum, and
left and right corticospinal tract, with low FA characteristic of white matter
abnormality.
Figure 4
Subject level analysis of fractional anisotropy: Case study 1.
(A) Routine MRI scans including T1-MPRAGE
(magnetization-prepared rapid acquisition with gradient echo), SWI
(susceptibility weighted imaging) and FLAIR (fluid attenuated inversion
recovery) of the player showed no abnormalities. (B) An
individualized approach to DTI analysis. Mean FAs from specific white
matter tracts are plotted; highlighted in red and inset above are the
areas sampled corresponding to the left corticospinal tract. The
boxplots represent the values found using the Non-Sport Control cohort
(n = 32). Single points on the
plot represent the individuals mean FA value within the specific tract.
Black dots represent where a value is not abnormal, while red points
indicate where an individual has a significantly abnormal FA compared to
the control cohort. Abnormal FA is defined by using a
z-scoring approach, comparing the individual to the
Non-Sport Control cohort,
P < 0.05, 95% confidence
interval, FDR corrected. CC, corpus callosum; CR, corona radiata; CST,
corticospinal tract; ILF, inferior longitudinal fasiculus; MCP, middle
cerebellar peduncle; WM Skel, whole white matter skeleton.
Subject level analysis of fractional anisotropy: Case study 1.
(A) Routine MRI scans including T1-MPRAGE
(magnetization-prepared rapid acquisition with gradient echo), SWI
(susceptibility weighted imaging) and FLAIR (fluid attenuated inversion
recovery) of the player showed no abnormalities. (B) An
individualized approach to DTI analysis. Mean FAs from specific white
matter tracts are plotted; highlighted in red and inset above are the
areas sampled corresponding to the left corticospinal tract. The
boxplots represent the values found using the Non-Sport Control cohort
(n = 32). Single points on the
plot represent the individuals mean FA value within the specific tract.
Black dots represent where a value is not abnormal, while red points
indicate where an individual has a significantly abnormal FA compared to
the control cohort. Abnormal FA is defined by using a
z-scoring approach, comparing the individual to the
Non-Sport Control cohort,
P < 0.05, 95% confidence
interval, FDR corrected. CC, corpus callosum; CR, corona radiata; CST,
corticospinal tract; ILF, inferior longitudinal fasiculus; MCP, middle
cerebellar peduncle; WM Skel, whole white matter skeleton.Across the whole cohort, there was a higher proportion of rugby players with DTI
abnormalities defined in this way than controls (X2
= 3.97, P = 0.046,
V = 0.21). Seventeen per cent of rugby
players (7/42) had abnormalities in mean FA in at least one of the sampled
tracts, compared to 3% of Non-Sport Controls (1/32). Sport Controls
showed no abnormality in FA (Fig.
5). The prevalence of abnormalities was highest in the corpus callosum
(3/7, 43%) and the corticospinal tracts (5/7, 71%). There were no
differences in alcohol intake between players with diffusion abnormalities and
those without.
Figure 5
Results of individualized analysis of fractional anisotropy across the
groups. Mean FAs from select white matter tracts where abnormalities
were observed are plotted. Single points on the plot represent an
individuals’ mean FA value within the specific tract. Black dots
represent where a value is not abnormal, while red points indicate where
an individual has a significantly abnormal FA compared to the Non-Sport
Control cohort. Individuals with at least one abnormal value across the
tracts are determined to be DTI abnormal. Across the groups, a higher
proportion of rugby players with abnormalities compared to controls can
be observed.
Results of individualized analysis of fractional anisotropy across the
groups. Mean FAs from select white matter tracts where abnormalities
were observed are plotted. Single points on the plot represent an
individuals’ mean FA value within the specific tract. Black dots
represent where a value is not abnormal, while red points indicate where
an individual has a significantly abnormal FA compared to the Non-Sport
Control cohort. Individuals with at least one abnormal value across the
tracts are determined to be DTI abnormal. Across the groups, a higher
proportion of rugby players with abnormalities compared to controls can
be observed.Voxelwise group comparisons of diffusion MRI also provided evidence for altered
white matter integrity in rugby players. Voxelwise cross-sectional comparison of
all rugby players to all controls (Non-Sport and Sport Controls combined) showed
reductions in FA in the posterior thalamic radiation, left posterior corona
radiata, left posterior limb of internal capsule and the superior cerebellar
peduncle bilaterally (Fig. 6A). No
significant differences were observed for the other DTI metrics investigated
(MD, NDI, ODI and ISOVF).
Figure 6
Voxelwise comparison of diffusion metrics between groups. Voxelwise
comparisons were conducted using FSL Randomise with age and gender added
as covariates. Green denotes the white matter skeleton and areas in red
indicate a result where corrected
P < 0.05.
(A) Comparisons of fractional anisotropy (FA) between
all rugby players
(n = 42) and
all controls (n = 45) showed
regions of lower FA in rugby players compared to controls. No
differences were seen in other diffusion metrics. (B)
Regions of lower FA, higher mean diffusivity (MD), and lower neurite
density index (NDI) were observed in non-acutely injured rugby players
(n = 27) when
compared to all controls. (C) Elevated FA was observed in
sub-acutely injured players
(n = 19) when
compared to non-acutely injured players
(n = 24)
excluding multiple observations of the same player. No differences were
seen in other DTI metrics. (D) When splitting the control
group, non-acutely injured rugby players still showed areas of reduced
FA relative to Non-Sport Controls
(n = 32). No
differences were observed in other DTI metrics, nor between Non-Sport
Controls and sub-acutely injured players or between Sport Controls
(n = 13) and
either rugby group.
Voxelwise comparison of diffusion metrics between groups. Voxelwise
comparisons were conducted using FSL Randomise with age and gender added
as covariates. Green denotes the white matter skeleton and areas in red
indicate a result where corrected
P < 0.05.
(A) Comparisons of fractional anisotropy (FA) between
all rugby players
(n = 42) and
all controls (n = 45) showed
regions of lower FA in rugby players compared to controls. No
differences were seen in other diffusion metrics. (B)
Regions of lower FA, higher mean diffusivity (MD), and lower neurite
density index (NDI) were observed in non-acutely injured rugby players
(n = 27) when
compared to all controls. (C) Elevated FA was observed in
sub-acutely injured players
(n = 19) when
compared to non-acutely injured players
(n = 24)
excluding multiple observations of the same player. No differences were
seen in other DTI metrics. (D) When splitting the control
group, non-acutely injured rugby players still showed areas of reduced
FA relative to Non-Sport Controls
(n = 32). No
differences were observed in other DTI metrics, nor between Non-Sport
Controls and sub-acutely injured players or between Sport Controls
(n = 13) and
either rugby group.
Differences in white matter integrity between non-acutely and sub-acutely
injured players
To disentangle the effects of a sub-acute injury, we investigated diffusion
changes in sub-acute and non-acutely injured players separately. Out of the 7
players with DTI abnormalities, 5 were non-acutely injured and 2 were scanned
sub-acutely after injury. Voxelwise analysis showed that imaging abnormalities
were most prominent in non-acutely injured players. Compared to all controls,
reductions in FA in the non-acutely injured group were seen in the corona
radiata and sagittal stratum, as well as elevations of MD in the genu of the
corpus callosum, corona radiata, posterior thalamic radiation, retrolenticular
part of internal capsule and sagittal stratum. Furthermore, lower NDI was seen
in widespread white matter regions in the non-acutely injured players (Fig. 6B). In contrast,
sub-acutely-injured rugby players showed no difference in diffusion metrics when
compared to all controls.We then compared the sub-acutely injured players with non-acutely injured rugby
players. MD was reduced in sub-acutely-injured players compared to non-acutely
injured players within the genu of the corpus callosum, retrolenticular part of
the internal capsule, corona radiata and external capsule (Fig. 6C). There were no differences in the other DTI
metrics.We split the control groups to investigate the effect of sporting activity on
diffusion measures. There were no differences between observed in any of the DTI
metrics between the Non-Sport Controls and Sport Controls. We investigated if
the diffusion differences were still present using only Sport or Non-Sport
Controls. Reductions in FA were still observed in non-acutely injured rugby
players when compared to only Non-Sport Controls in the corona radiata,
posterior thalamic radiation, sagittal stratum and corticospinal tract (Fig. 6D). There were no reductions in
other DTI metrics, differences between sub-acutely injured players and Non-Sport
Controls nor differences when comparing the Sports Control group with either
rugby group.
Microbleed evidence for DVI
Three rugby players had microbleeds, 2 of whom were sub-acutely injured, while
none were present in Non-Sport Controls (Fig. 7). One Sport Control showed microbleeds. FA abnormalities were
not observed in the players with microbleeds. Hence, 23% of players
(10/44) had evidence of diffuse axonal or DVI. Longitudinal SWI was stable in
individuals with follow-up scans, with no change in microbleed incidence or
evolution of microbleeds on SWI scans.
Figure 7
Presence of microbleeds on susceptibility weighted imaging: Case study 2.
(A) A player with a sub-acute injury presented with no
abnormalities on routine structural MRI scans, but had evidence of
microbleeds (highlighted in the magnified imaged) on susceptibility
weighted imaging (SWI). (B) Utilising the individualized
approach to DTI analysis, no abnormalities were found in FA for this
player. CC, corpus callosum; CR, corona radiata; CST, corticospinal
tract; ILF, inferior longitudinal fasiculus; MCP, middle cerebellar
peduncle; WM Skel, whole white matter skeleton.
Presence of microbleeds on susceptibility weighted imaging: Case study 2.
(A) A player with a sub-acute injury presented with no
abnormalities on routine structural MRI scans, but had evidence of
microbleeds (highlighted in the magnified imaged) on susceptibility
weighted imaging (SWI). (B) Utilising the individualized
approach to DTI analysis, no abnormalities were found in FA for this
player. CC, corpus callosum; CR, corona radiata; CST, corticospinal
tract; ILF, inferior longitudinal fasiculus; MCP, middle cerebellar
peduncle; WM Skel, whole white matter skeleton.
Rugby players show abnormal white matter volume change over time
We assessed volumetric differences between the rugby players and controls.
Cross-sectional comparisons were made between the groups at baseline. A
voxelwise analysis of grey and white matter volumes showed no significant
differences at baseline between players and all controls. There were no
differences between the control groups, or between non-acutely injured and
sub-acutely injured rugby players.We then investigated whether there was any evidence for abnormal brain volume
changes in rugby players using a sensitive measure of brain volume change over
time (Jacobian Determinant, ‘JD’). Voxelwise comparison of JD maps
between rugby players who attended 2 visits and the Longitudinal Control group
showed lower white matter JD in rugby players, specifically within the lateral
occipital cortex and post central gyri (Fig. 8A). A lower JD suggests that either the rate of volume
expansion was lower in rugby players than controls, or players were losing
volume at a higher rate than controls. Longitudinal Controls were slightly older
than the rugby players (mean age in years 33.3 versus 24.8,
t = 6.28,
P < 0.001), and so would be expected to
have lower JD values than the rugby players. However, the reverse was true.
Sampling the mean JD values from these regions revealed that 50% of
players (9/18) had mean JD values below zero (indicating brain volume loss)
compared to 25% of controls (4/16) (Fig. 8B). These results suggest that the rugby players had an
abnormal trajectory of white matter volume change for individuals of that age
(Fig. 8C). Mean JD within the
grey, white matter or whole brain did not correlate significantly with head
injury history.
Figure 8
Longitudinal changes in volume in rugby players. Voxelwise comparisons
were conducted using FSL Randomise with age as a covariate and results
shown for areas where corrected
P < 0.1 (one
tailed t-test). (A) Lower annualized
Jacobian Determinant (JD) in rugby players
(n = 18) compared to
Longitudinal Controls
(n = 16) was
observed in the white matter. (B) When plotting the JD
values within the significant areas, values between rugby players (blue)
and Longitudinal Controls (red) look similar. (C) However,
when plotting against age, a proportion of rugby players have JD values
that appear lower than what would be expected for individuals of that
age, suggesting there are altered trajectories for white matter volume
change in rugby players.
Longitudinal changes in volume in rugby players. Voxelwise comparisons
were conducted using FSL Randomise with age as a covariate and results
shown for areas where corrected
P < 0.1 (one
tailed t-test). (A) Lower annualized
Jacobian Determinant (JD) in rugby players
(n = 18) compared to
Longitudinal Controls
(n = 16) was
observed in the white matter. (B) When plotting the JD
values within the significant areas, values between rugby players (blue)
and Longitudinal Controls (red) look similar. (C) However,
when plotting against age, a proportion of rugby players have JD values
that appear lower than what would be expected for individuals of that
age, suggesting there are altered trajectories for white matter volume
change in rugby players.
White matter integrity and longitudinal volume change in rugby
players
We tested whether areas of the white matter showing evidence of abnormal volume
changes over time (low JD) in rugby players were associated with abnormalities
in white matter integrity (low FA). We sampled the diffusion metrics and JD
values within the white matter tracts in areas where there was a significant
difference in JD between players and controls and found no correlation between
baseline FA, MD or NDI with JD in these areas. Additionally, there were no
significant correlations when restricting analysis only to non-acutely injured
rugby players.
White matter volume changes, white matter integrity and neuropsychological
performance
We also explored the relationship between atrophy rates, white matter integrity
and cognitive function. Investigating tasks which showed differences at
baseline, no correlations were found between the mean FA, MD or NDI in white
matter tract ROI’s and neuropsychological test performance. Rugby players
who showed abnormalities in at least one white matter tract ROIs
(n = 7) did not
perform significantly differently in neuropsychological tests, including
premorbid intelligence scores, compared to players not classified as abnormal on
their individualized DTI. No correlations were found either with mean JD in
grey, white matter or whole brain and neuropsychological test scores. We
investigated if premorbid intelligence influenced neuroimaging parameters. We
removed 3 non-sport controls at the higher range of FSIQ scores so that the
non-sport controls (n = 29) and rugby
players (n = 42) were matched for
premorbid intelligence. Running the individualized DTI assessment with FSIQ
matched controls, players previously identified as abnormal on DTI remained
abnormal. Furthermore, FSIQ scores were not correlated with mean FA within rugby
players or controls.
Subgroup imaging analysis in male Rugby Union players only
We investigated if there were any differences in the results when looking at
scans from male rugby union players only
(n = 37) and included
only male controls for the cross-sectional comparison. A similar pattern of
abnormalities was observed, with 11% of rugby players (4/35) with DTI
abnormalities and 8% with microbleeds (3/37). In total, 19% of
players (7/37) had evidence of diffuse axonal or DVI. Voxelwise comparisons of
diffusion metrics showed similar results, with reductions in FA and NDI in
non-acutely injured rugby players persisting. With 3 players excluded from the
longitudinal volumetric analysis
(n = 15), the area of
abnormality in JD within the white matter remained but was slightly reduced in
size.
Discussion
Our longitudinal observational study shows abnormalities of brain structure
associated with elite rugby participation. DTI and SWI were used to assess white
matter structure and evidence of axonal injury was seen in several players studied.
Across the group of rugby players studied abnormalities of FA and other diffusion
measures were seen. In contrast, sport playing controls were not classified as
showing abnormalities of FA. We also studied changes in brain structure over time.
Abnormal trajectories of white matter volume were seen in elite rugby players,
suggesting an impact of elite rugby participation on brain development. To our
knowledge, this is the first study to investigate MR imaging changes in active elite
rugby players.Diffusion imaging abnormalities of FA, neurite density and MD were seen in the rugby
group. Similar directions of change are seen in other mild TBI patients scanned in
the chronic stage,, and longitudinally after an injury. We used an
individualized approach to DTI analysis to identify players with neuroimaging
abnormalities. This
allowed us to investigate the structure of a number of large white matter tracts in
a focussed way. Twenty-three per cent of the rugby players showed signs of either
diffuse axonal or DVI. The majority of the players with evidence of DAI showed
abnormalities within the corticospinal tract. Reductions in FA are associated with
abnormalities of motor function in other contexts., Although this was not explicitly
assessed, the players studied did not show any evident abnormalities of motor
function and all players were successfully competing at an elite level. However,
retired rugby players have been shown to display reduced fine motor control
ability., Therefore, it is possible that reductions of FA within
the corticospinal tract might be significant in terms of future motor function.Abnormalities of white matter structure are correlated with clinical features of
injury severity and neuropsychological test performance following moderate-severe
TBI, with evidence of DAI (low FA) usually associated with cognitive
impairment.,, Although the rugby players we studied showed did show
poorer performance on a number of cognitive tests, cognitive performance did not
correlate with white matter abnormalities. Players with white matter abnormalities
did not perform significantly worse than those classified as normal. Rather than
effect of a rugby participation or sub-acute injury, the difference in performance
observed across a select number of neuropsychological tests may have been related to
group differences in IQ and appears unrelated to injury or imaging abnormalities
within this study.Multi-shell diffusion-MRI was acquired. This allowed Neurite Orientation Dispersion
and Density Imaging (NODDI) to be performed. NODDI is an advanced diffusion MRI
technique was used to calculate a range of diffusion metrics that potentially
provide more sensitive and specific diffusion metrics of white matter pathology.
NODDI separates the diffusion signal from three different tissue compartments:
intra-neurite (restricted diffusion), extra-neurite (hindered diffusion) and
cerebrospinal fluid (free diffusion) to extract a NDI, ODI and ISOVF. Sub-acutely after a mild
TBI, studies have observed reduced NDI, which has correlated with reductions in FA and
increased symptom load.
In athletes not acutely injured, but with a history of injury, studies have found
abnormalities in FA which were negatively correlated to ODI., We extend these findings by showing
widespread reductions in NDI in our non-acutely injured rugby players, but not in
the sub-acutely injured players, with no differences in ODI or ISOVF. These results
are suggestive of lower white matter tissue density and that the FA and MD findings
are not primarily driven by variations in free water volume.Moderate-severe TBI produces a progressive loss of brain volume, particularly
affecting the white matter., This is a marker of the progressive neurodegenerative
process that can be triggered by TBI. Abnormal white matter volume changes were observed in
the rugby group. Reductions in a region of white matter volume, as defined by a
negative JD, were seen in around 50% of the rugby players studied, and a
higher rate of white matter volume loss was seen across the group when compared to a
control group who were slightly older. White matter volume is expected to increase
until the age of around 40,, and this pattern was seen in our control group who had
longitudinal imaging. The rugby players studied had an average age of
25 years old and the oldest was 31 years old. In this age range
reductions of white matter volume are abnormal and may be an early sign of an active
neurodegenerative process that might increase the risk of neurodegenerative disease
in later life. The pathological correlates of abnormal white matter volume we
detected with advanced neuroimaging in rugby players is unknown and requires more
investigation. However, evidence of CTE in retired professional rugby players has
been previously observed, and in
deceased professional Scottish football players where head injury risk is lower but
exposure to heading the football is seen as a unique sport-specific risk factor, a
five-fold increased risk of developing Alzheimer’s disease was
identified.The current focus of head injury management programmes in sport is the identification
of defined observable signs, such as loss of consciousness and ataxia, and assessment for the
presence of characteristic symptoms and alterations from baseline in cognitive
function and balance. Effective surveillance at the elite and community levels of
Rugby Union is overseen in the UK by the Rugby Football Union and any signs or
symptoms of mTBI routinely lead to a player’s removal from play and a
graduated return to play once these have resolved. Animal studies show that early
markers of neurodegeneration such as tau pathology, vascular damage and
neuroinflammation can be produced by mild injuries of the type frequently
experienced by professional rugby players., However, an important observation is that
this pathology can be seen in the absence of concussive symptoms. Players in a range
of sports are repeatedly exposed to head impacts in matches and training that may in
themselves be sufficient to result in the subsequent development of
neurodegenerative pathology. However, these impacts would not trigger removal from
play and are not routinely measured over a player’s career. Further studies
of both active and retired rugby players are needed to investigate whether these
subthreshold impacts as well as reported mTBIs are associated with evidence of brain
injury and to ascertain how cumulative injury burden relates to neurodegeneration
and ongoing brain health.We compared rugby players with a recent history of mTBI to those without. Reduced MD
was seen in sub-acutely injured rugby players compared to non-acutely injured
players, although there were no differences when compared to the control group. This
is in keeping with several previous studies of sport mTBI, which have shown reduced
diffusivity alongside elevated FA in recently injured players.,, Other diffusion metrics did not show
any abnormalities sub-acutely after injury. Previous studies have described the
dynamic nature of diffusion changes seen in the early stages of TBI where FA
increases initially in the acute to sub-acute period. However, sub-acutely injured players did
not show abnormalities of FA compared to controls. Similar findings have been
described in other studies of non-acutely injured contact sport athletes. In the context of reduced FA observed in
our non-acutely injured players, the absence of evidence for diffusion changes in
sub-acutely injured players may be due to the acute effects being occluded by longer
term reductions in FA.Three players also had microbleeds visible on their SWI, an abnormality not seen in
any of our non-sporting controls, but observed in 1 sporting control. Microbleeds
are a marker of DVI and are produced by small perivascular haemorrhage that can be
missed by conventional imaging and that remains visible on SWI because of the
persistence of haemosiderin laden macrophages in the perivsascular region., Previous studies of
have reported the presence of microbleeds after mild TBI, including in contact sport
athletes., We extend these findings by showing that microbleeds
can occur in the absence of diffusion abnormalities and vice versa. The distinct
information identified by these two imaging methods has recently been shown in
moderate-severe TBI.
This illustrates that DVI and DAI can occur independently after TBI and that SWI and
diffusion MRI provide complementary information about the presence of subtle brain
injury.There are some limitations to our study. Our longitudinal control group were
non-sport controls, meaning that the effect of exercise was not controlled for in
our longitudinal analyses. However, we do not believe this likely to have a large
effect on the comparison as evidence suggests exercise should lead to higher grey
and white matter volume. A
further limitation to our study was that we had gender and age differences in our
control groups when compared to the rugby players. We minimised this effect by
modelling age in all groupwise analyses, and gender where appropriate. One potential
limitation is that diffusion metrics such as FA have been shown to be related to
premorbid intelligence scores,, which were higher in our control group. This did not
appear to be a major confound for our results, as a sensitivity analysis showed no
difference in classification of DTI abnormalities in rugby players when the groups
were matched for FSIQ, and intelligence scores were not correlated to FA. Our
non-collision sport control group were also not professional athletes and not
matched for BMI which limits our ability to exclude the effect of high-level
sporting participation on our results. We only had a small sample of players who had
a followed-up visit, meaning we were not well powered to investigate the effect of a
sub-acute injury on longitudinal volume change, which may be influenced by the
resolution of oedema or inflammation, and lacked longitudinal DTI to help interpret
the volumetric changes. Our sports control group was small and may have been
underpowered to detect differences in a group wise analysis. We therefore utilised
an individualized analysis to detect abnormalities in FA, and did not observe any
abnormalities in our sports control group compared to 17% of rugby
players.It is important to note that our results in adult professional rugby union and league
players are not directly comparable to play at the community or youth levels. The
overall health benefit of participating in sports and physical exercise have been
well established including the reduction in mortality and chronic diseases such as
dementia,, and have been explored in detail within rugby. In the general
professional sport setting, evidence of long-term health benefits includes lower
all-cause mortality., The clinical implications on an individual level of
the imaging changes associated with elite rugby participation are unclear. In
retired rugby players, a lower risk of cardiovascular disease, with no evidence of
exposure to repetitive head injuries nor participation in elite rugby affecting
later life mental health, social or work functioning was found.In conclusion, our study shows diffusion and brain volume abnormalities in adult male
and female rugby union and league players competing at an elite level. The results
are in keeping with the presence of axonal injury, potentially related to repeated
head impacts. Unexpected reductions in brain volume were seen in around 50%
of the rugby players studied, which might indicate excess neurodegeneration in white
matter tracts affected by injury. Rugby governing bodies, including the Rugby
Football Union, are increasingly active collaborators in a range of head injury
prevention and management projects as well as cross-sectional studies looking at
brain health in retired players., To date these have rarely had a major focus on
reporting neuroimaging changes. Further longitudinal imaging research in active and
retired rugby players is needed to understand the impact of both repeated
sports-related head impacts and head injuries on brain structure, and to clarify
whether the abnormalities we have observed are related to an increased risk of
neurodegenerative disease and impaired neurocognitive function following elite rugby
participation.
Supplementary material
Supplementary material is
available at Brain Communications online.Click here for additional data file.
Authors: E A Wilde; S R McCauley; J V Hunter; E D Bigler; Z Chu; Z J Wang; G R Hanten; M Troyanskaya; R Yallampalli; X Li; J Chia; H S Levin Journal: Neurology Date: 2008-03-18 Impact factor: 9.910
Authors: Brandon E Gavett; Robert A Stern; Robert C Cantu; Christopher J Nowinski; Ann C McKee Journal: Alzheimers Res Ther Date: 2010-06-25 Impact factor: 6.982
Authors: Mehul A Trivedi; Michael A Ward; Timothy M Hess; Shawn D Gale; Robert J Dempsey; Howard A Rowley; Sterling C Johnson Journal: J Neurotrauma Date: 2007-05 Impact factor: 5.269
Authors: Barbara B Bendlin; Michele L Ries; Mariana Lazar; Andrew L Alexander; Robert J Dempsey; Howard A Rowley; Jack E Sherman; Sterling C Johnson Journal: Neuroimage Date: 2008-05-07 Impact factor: 6.556
Authors: Kathryn Y Manning; Amy Schranz; Robert Bartha; Gregory A Dekaban; Christy Barreira; Arthur Brown; Lisa Fischer; Kevin Asem; Timothy J Doherty; Douglas D Fraser; Jeff Holmes; Ravi S Menon Journal: Neurology Date: 2017-10-25 Impact factor: 9.910