The existing research on the microstructural alterations associated with sport-related concussions (SRCs) has primarily focused on deep white matter (DWM) fibers, while the impact of SRCs on the superficial white matter (SWM) and gray matter (GM) remains unknown. This study aimed to characterize the altered metrics obtained from neurite orientation dispersion and density imaging (NODDI) in boxers with SRCs, and thereby determine whether distinct regional patterns of microstructural alterations can offer valuable insights for accurate diagnosis and prognosis. Concussed boxers (n = 56) and healthy controls (HCs) with typically developing (n = 72) underwent comprehensive neuropsychological assessment and magnetic resonance imaging (MRI) examinations. The tract-based spatial statistics approach was used to investigate alterations in the DWM and SWM, while the gray matter-based spatial statistics approach was used to examine changes in the GM. The median time from the last SRC to MRI in the SRC group was 33.5 days (interquartile range, 45.25). In comparison with HCs, the SRC group exhibited lower fractional anisotropy (FA), neurite density index (NDI), and isotropic volume fraction (ISOVF), as well as higher mean diffusivity, axial diffusivity (AD), and radial diffusivity in both the DWM and SWM. Moreover, the SRC group exhibited lower FA, NDI, orientation dispersion index, and ISOVF in the GM, as well as higher AD. The altered microstructure of both gray and white matter was found to be associated with deficits in working memory and vocabulary memory among boxers. In addition to characterizing the DWM impairment, NODDI further elucidated the effects of SRCs on the microstructure of GM and SWM, offering a reliable imaging biomarker for SRC diagnosis and shedding light on the pathophysiological changes underlying SRCs.
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References
1.
GesselLM, FieldsSK, CollinsCL, et al.Concussions among United States high school and collegiate athletes. J Athl Train, 2007; 42(4):495–503.
2.
HiradAA, BazarianJJ, Merchant-BornaK, et al.A common neural signature of brain injury in concussion and subconcussion. Sci Adv, 2019; 5(8):eaau3460.
3.
ArmstrongRC, MierzwaAJ, MarionCM, et al.White matter involvement after TBI: Clues to axon and myelin repair capacity. Exp Neurol, 2016; 275 Pt 3:328–333; doi: 10.1016/j.expneurol.2015.02.011
NarayanaS, CharlesC, CollinsK, et al.Neuroimaging and neuropsychological studies in sports-related concussions in adolescents: Current state and future directions. Front Neurol, 2019; 10:538; doi: 10.3389/fneur.2019.00538
6.
CataniM, Dell’acquaF, VerganiF, et al.Short frontal lobe connections of the human brain. Cortex, 2012; 48(2):273–291; doi: 10.1016/j.cortex.2011.12.001
7.
PovlishockJT. Pathobiology of traumatically induced axonal injury in animals and man. Ann Emerg Med, 1993; 22(6):980–986; doi: 10.1016/s0196-0644(05)82738-6
WangM-L, WeiX-E, YuM-M, et al.Alzheimer’s disease neuroimaging initiative. Self-reported traumatic brain injury and in vivo measure of AD-vulnerable cortical thickness and AD-related biomarkers in the ADNI cohort. Neurosci Lett, 2017; 655:115–120; doi: 10.1016/j.neulet.2017.06.055
10.
SanthanamP, WilsonSH, OakesTR, et al.Accelerated age-related cortical thinning in mild traumatic brain injury. Brain Behav, 2019; 9(1):e01161; doi: 10.1002/brb3.1161
11.
Le BihanD. Looking into the functional architecture of the brain with diffusion MRI. Nat Rev Neurosci, 2003; 4(6):469–480; doi: 10.1038/nrn1119
12.
HellewellSC, WeltonT, PearceAJ, et al.Diffusion MRI as a complementary assessment to cognition, emotion, and motor dysfunction after sports-related concussion: A systematic review and critical appraisal of the literature. Brain Imaging Behav, 2021; 15(3):1685–1704; doi: 10.1007/s11682-020-00336-0
13.
JonesDK, CercignaniM. Twenty-five pitfalls in the analysis of diffusion MRI data. NMR Biomed, 2010; 23(7):803–820; doi: 10.1002/nbm.1543
14.
ZhangH, SchneiderT, Wheeler-KingshottCA, et al.NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage, 2012; 61(4):1000–1016; doi: 10.1016/j.neuroimage.2012.03.072
15.
PalaciosEM, YuhEL, Mac DonaldCL, et al.TRACK-TBI Investigators. Diffusion tensor imaging reveals elevated diffusivity of white matter microstructure that is independently associated with long-term outcome after mild traumatic brain injury: A TRACK-TBI Study. J Neurotrauma, 2022; 39(19–20):1318–1328; doi: 10.1089/neu.2021.0408
16.
PalaciosE, OwenJ, YuhE, et al.TRACK-TBI Investigators. The evolution of white matter microstructural changes after mild traumatic brain injury: A longitudinal DTI and NODDI Study. Sci Adv, 2020; 6(32):eaaz6892; doi: 10.1126/sciadv.aaz6892
17.
StojanovskiS, NazeriA, LepageC, et al.Microstructural abnormalities in deep and superficial white matter in youths with mild traumatic brain injury. Neuroimage Clin, 2019; 24:102102; doi: 10.1016/j.nicl.2019.102102
18.
CalkinsME, MerikangasKR, MooreTM, et al.The philadelphia neurodevelopmental cohort: Constructing a deep phenotyping collaborative. J Child Psychol Psychiatry, 2015; 56(12):1356–1369; doi: 10.1111/jcpp.12416
19.
RuffRM, IversonGL, BarthJT, et al.NAN Policy and Planning Committee. Recommendations for diagnosing a mild traumatic brain injury: A National Academy of Neuropsychology education Paper. Arch Clin Neuropsychol, 2009; 24(1):3–10; doi: 10.1093/arclin/acp006
20.
RădoiA, PocaMA, GándaraD, et al.The Sport Concussion Assessment Tool (SCAT2) for evaluating civilian mild traumatic brain injury. A Pilot Normative Study. PLoS One, 2019; 14(2):e0212541; doi: 10.1371/journal.pone.0212541
21.
McCroryP, MeeuwisseW, DvořákJ, et al.Consensus statement on concussion in sport-the 5th international conference on concussion in sport held in Berlin, October 2016. Br J Sports Med, 2017; 51(11):838–847.
22.
CorriganJD, HinkeldeyNS. Relationships between parts A and B of the Trail Making Test. J Clin Psychol, 1987; 43(4):402–409; doi: 10.1002/1097-4679(198707)43:4<402::Aid-jclp2270430411>3.0.Co;2-e
ZungWW. A self-rating depression scale. Arch Gen Psychiatry, 1965; 12(1):63–70.
25.
LovellMR, IversonGL, CollinsMW, et al.Measurement of symptoms following sports-related concussion: Reliability and normative data for the post-concussion scale. Appl Neuropsychol, 2006; 13(3):166–174; doi: 10.1207/s15324826an1303_4
BehrensTEJ, BergHJ, JbabdiS, et al.Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage, 2007; 34(1):144–155; doi: 10.1016/j.neuroimage.2006.09.018
28.
NazeriA, ChakravartyMM, RajjiTK, et al.Superficial white matter as a novel substrate of age-related cognitive decline. Neurobiol Aging, 2015; 36(6):2094–2106; doi: 10.1016/j.neurobiolaging.2015.02.022
29.
ParvathaneniP, RogersBP, HuoY, et al.Gray Matter Surface based Spatial Statistics (GS-BSS) in diffusion microstructure. Med Image Comput Comput Assist Interv, 2017; 10433:638–646; doi: 10.1007/978-3-319-66182-7_73
30.
OhhashiG, TaniS, MurakamiS, et al.Problems in health management of professional boxers in Japan. Br J Sports Med, 2002; 36(5):346–352; discussion 353; doi: 10.1136/bjsm.36.5.346
31.
EierudC, CraddockRC, FletcherS, et al.Neuroimaging after mild traumatic brain injury: Review and meta-analysis. Neuroimage Clin, 2014; 4:283–294; doi: 10.1016/j.nicl.2013.12.009
32.
MeierTB, BergaminoM, BellgowanPSF, et al.Longitudinal assessment of White matter abnormalities following sports-related concussion. Hum Brain Mapp, 2016; 37(2):833–845; doi: 10.1002/hbm.23072
33.
KoerteIK, KaufmannD, HartlE, et al.A prospective study of physician-observed concussion during a varsity university hockey season: White matter integrity in ice hockey players. Part 3 of 4. Neurosurg Focus, 2012; 33(6):E3:1–E7; doi: 10.3171/2012.10.FOCUS12303
34.
WrightDK, GardnerAJ, WojtowiczM, et al.White matter abnormalities in retired professional rugby league players with a history of concussion. J Neurotrauma, 2021; 38(8):983–988; doi: 10.1089/neu.2019.6886
35.
GrussuF, SchneiderT, TurC, et al.Neurite dispersion: A new marker of multiple sclerosis spinal cord pathology? Ann Clin Transl Neurol, 2017; 4(9):663–679; doi: 10.1002/acn3.445
36.
FukutomiH, GlasserMF, ZhangH, et al.Neurite imaging reveals microstructural variations in human cerebral cortical gray matter. Neuroimage, 2018; 182:488–499; doi: 10.1016/j.neuroimage.2018.02.017
37.
MajorB, SymonsGF, SinclairB, et al.White and gray matter abnormalities in Australian Footballers with a history of sports-related concussion: An MRI Study. Cereb Cortex, 2021; 31(12):5331–5338; doi: 10.1093/cercor/bhab161
38.
SchmahmannJD, SmithEE, EichlerFS, et al.Cerebral white matter neuroanatomy, clinical neurology, and neurobehavioral correlates. Ann N Y Acad Sci, 2008; 1142:266–309; doi: 10.1196/annals.1444.017
39.
ChungS, WangX, FieremansE, et al.Altered relationship between working memory and brain microstructure after mild traumatic brain injury. AJNR Am J Neuroradiol, 2019; 40(9):1438–1444; doi: 10.3174/ajnr.A6146
40.
MallasEJ, De SimoniS, ScottG, et al.Abnormal dorsal attention network activation in memory impairment after traumatic brain injury. Brain, 2021; 144(1):114–127; doi: 10.1093/brain/awaa380
41.
YeterianEH, PandyaDN, TomaiuoloF, et al.The cortical connectivity of the prefrontal cortex in the monkey brain. Cortex, 2012; 48(1):58–81; doi: 10.1016/j.cortex.2011.03.004
42.
WangS, ZhangF, HuangP, et al.Superficial white matter microstructure affects processing speed in cerebral small vessel disease. Hum Brain Mapp, 2022; 43(17):5310–5325; doi: 10.1002/hbm.26004
43.
OyefiadeAA, AmeisS, LerchJP, et al.Development of short-range white matter in healthy children and adolescents. Hum Brain Mapp, 2018; 39(1):204–217; doi: 10.1002/hbm.23836
44.
GaoJ, CheungRT, ChanYS, et al.The relevance of short-range fibers to cognitive efficiency and brain activation in aging and dementia. PLoS One, 2014; 9(4):e90307; doi: 10.1371/journal.pone.0090307
45.
ReginoldW, LuedkeAC, ItorralbaJ, et al.Altered superficial white matter on tractography MRI in Alzheimer’s disease. Dement Geriatr Cogn Dis Extra, 2016; 6(2):233–241; doi: 10.1159/000446770
46.
PhillipsOR, JoshiSH, PirasF, et al.The superficial white matter in Alzheimer’s disease. Hum Brain Mapp, 2016; 37(4):1321–1334; doi: 10.1002/hbm.23105
47.
PankatzL, RojczykP, Seitz-HollandJ, et al.Adverse outcome following mild traumatic brain injury is associated with microstructure alterations at the gray and white matter boundary. J Clin Med, 2023; 12(16); doi: 10.3390/jcm12165415
48.
KimH. Encoding and retrieval along the long axis of the Hippocampus and their relationships with dorsal attention and default mode networks: The HERNET Model. Hippocampus, 2015; 25(4):500–510; doi: 10.1002/hipo.22387
49.
EspañaLY, LeeRM, LingJM, et al.Serial assessment of gray matter abnormalities after sport-related concussion. J Neurotrauma, 2017; 34(22):3143–3152; doi: 10.1089/neu.2017.5002
50.
HuangH, MaX, YueX, et al.Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus. Brain Behav, 2022; 12(10):e2746; doi: 10.1002/brb3.2746
51.
GongNJ, KuzminskiS, ClarkM, et al.Microstructural alterations of cortical and deep gray matter over a season of high school football revealed by diffusion kurtosis imaging. Neurobiol Dis, 2018; 119:79–87; doi: 10.1016/j.nbd.2018.07.020
52.
WangJ, ShiY, CaoS, et al.Polynitroxylated PEGylated hemoglobin protects pig brain neocortical gray and white matter after traumatic brain injury and hemorrhagic shock. Front Med Technol, 2023; 5:1074643; doi: 10.3389/fmedt.2023.1074643
53.
VillapolS, LoaneDJ, BurnsMP. Sexual dimorphism in the inflammatory response to traumatic brain injury. Glia, 2017; 65(9):1423–1438; doi: 10.1002/glia.23171
54.
TengY, YuQ, YuX, et al.Neuropsychological study on the effects of boxing upon athletes’ memory. J Strength Cond Res, 2022; 36(12):3462–3467; doi: 10.1519/jsc.0000000000003909
55.
BiglerED. Anterior and middle cranial fossa in traumatic brain injury: Relevant neuroanatomy and neuropathology in the study of neuropsychological outcome. Neuropsychology, 2007; 21(5):515–531; doi: 10.1037/0894-4105.21.5.515
56.
RobertsGW, AllsopD, BrutonC. The occult aftermath of boxing. J Neurol Neurosurg Psychiatry, 1990; 53(5):373–378; doi: 10.1136/jnnp.53.5.373
57.
PonsfordJ, VelikonjaD, JanzenS, et al.INCOG 2.0 guidelines for cognitive rehabilitation following traumatic brain injury, Part II: Attention and information processing speed. J Head Trauma Rehabil, 2023; 38(1):38–51; doi: 10.1097/HTR.0000000000000839
58.
AugustineJR. Circuitry and functional aspects of the insular lobe in primates including humans. Brain Res Brain Res Rev, 1996; 22(3):229–244; doi: 10.1016/s0165-0173(96)00011-2
59.
MiddletonTRF, Dupuis-LatourJ, GeY, et al.Stories of identity from high performance male boxers in their training and competition environments. J Funct Morphol Kinesiol, 2018; 3(4); doi: 10.3390/jfmk3040058
60.
ChenX, QiuN, ChenC, et al.Personality traits, loneliness, and affect among boxers. Front Psychol, 2021; 12:609153; doi: 10.3389/fpsyg.2021.609153
61.
BattyGD, FrankP, KujalaUM, et al.Suicide and depression in former contact sports participants: Population-based cohort study, systematic review, and meta-analysis. EClinicalMedicine, 2023; 60:102026; doi: 10.1016/j.eclinm.2023.102026
62.
JiSB, ZhaoW, FordJC, et al.Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion. J Neurotrauma, 2015; 32(7):441–454; doi: 10.1089/neu.2013.3268
63.
ArbogastKB, MarguliesSS. Material characterization of the brainstem from oscillatory shear tests. J Biomech, 1998; 31(9):801–807; doi: 10.1016/S0021-9290(98)00068-2
64.
DiPieroM, CordashH, PriggeMB, et al.Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males. Front Neurosci, 2023; 17:1231719; doi: 10.3389/fnins.2023.1231719
TournierJD, CalamanteF, GadianDG, et al.Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage, 2004; 23(3):1176–1185; doi: 10.1016/j.neuroimage.2004.07.037
67.
ReveleyC, SethAK, PierpaoliC, et al.Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography. Proc Natl Acad Sci U S A, 2015; 112(21):E2820–E2828; doi: 10.1073/pnas.1418198112
68.
BachM, LaunFB, LeemansA, et al.Methodological considerations on tract-based spatial statistics (TBSS). Neuroimage, 2014; 100:358–369; doi: 10.1016/j.neuroimage.2014.06.021
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