BACKGROUND: Multiple sclerosis (MS) is characterized by physical and mental impairments that often result in pain and reduced quality of life.
OBJECTIVE: To understand the relationship of pain, quality of life, and cognition to structural measures of brain volume.
METHODS: Behavioral measures were assessed in a single session using standardized questionnaires and rating scales. Brain volume measures were assessed with structural magnetic resonance imaging (MRI).
RESULTS: Twenty-nine individuals with relapsing-remitting MS and 29 age-matched controls participated in this study. Pain, quality of life, and cognition were significantly interrelated. Higher fluid attenuation inversion recovery weighted lesion volume was significantly associated with increased reports of pain (p = 0.01), lower physical quality of life (p < 0.0001), and lower cognitive performance (p = 0.001) in our cohort.
CONCLUSIONS: Assessment of pain and quality of life along with structural MRI highlights the importance of understanding structure-function relationships in MS and suggests that therapists should not only evaluate individuals for cognition and quality of life, but should consider rehabilitation goals that target these areas.
AmatoM. P., PortaccioE., GorettiB., ZipoliV., HakikiB., GianniniM., PastoL., & RazzoliniL. (2010). Cognitive impairment in early stages of multiple sclerosis. J Neurol Sci, 31(S2), S211–S214.
2.
BenedictR. H., CookfairD., GavettR., GuntherM., MunschauerF., GargN., & Weinstock-GuttmanB. (2006). Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS. Journal of the International Neuropsychological Society, 12(4), 549–558.
3.
BenedictR. H., FischerJ. S., ArchibaldC. J., ArnettP. A., BeattyW. W., BobholzJ., CheluneG. J., FiskJ. D., LangdonD. W., CarusoL., FoleyF., LaRoccaN. G., VowelsL., WeinsteinA., DeLucaJ., RaoS. M., & MunschauerF. (2002). Minimal neuropsychological assessment of MS patients: A consensus approach. The Clinical Neuropsychologist, 16(3), 381–397.
4.
CarassA., CuzzocreoJ., WheelerM. B., BazinP. L., ResnickS. M., & PrinceJ. L. (2011). Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis. Neuroimage, 56(4), 1982–1992.
5.
CleelandC. S., & RyanK. M. (1994). Pain assessment: Global use of the Brief Pain Inventory. Annals of the Academy of Medicine, Singapore, 23, 129–138.
6.
CutajarR., FerrianiE., ScandellariC., SabattiniL., TrocinoC., MarchelloL. P., & StecchiS. (2000). Cognitive function and quality of life in multiple sclerosis patients. J Neurovirol, 6, SS186–S190.
7.
DanzlM. M., EtterN. M., AndreattaR. D., & KitzmanP. H. (2012). Facilitating neurorehabilitation through principles of engagement. J Allied Health, 41, 35–41.
8.
FonovV., EvansA. C., BotteronK., AlmliC. R., McKinstryR. C., & CollinsD. L. (2011). Unbiased average age-appropriate atlases for pediatric populations. Neuroimage, 54(1), 313–327.
9.
ForbesA., WhileA., MathesL., & GriffithsP. (2006). Health problems and health-related quality of life in people with multiple sclerosis. Clin Rehabil, 20, 67–78.
10.
FritzN. E.,
MarasiganR. E.,
CalabresiP. A.,
NewsomeS. D., & ZackowskiK. M. (2015a). The impact of dynamic balance measures on walking performance in multiple sclerosis. Neurorehabil Neural Re, 29, 62–69.
11.
FritzN. E.,
NewsomeS. D.,
EloyanA.,
MarasiganR. E.,
CalabresiP. A., & ZackowskiK. M. (2015b). Longitudinal relationships among posturography and gait measures in multiple sclerosis. Neurology, 84, 2048–2056.
12.
HobartJ. C., RiaziA., LampingD. L., FitzpatrickR., & ThompsonA. J. (2003). Measuring the impact of MS on walking ability. The 12-item MS Walking Scale (MSWS-12). Neurology, 60, 31–36.
13.
JanardhanV., & BakshiR. (2000). Quality of life and its relationship to brain lesions and atrophy on magnetic resonance images in 60 patients with multiple sclerosis. Arch Neurol, 57, 1485–1491.
14.
JenkinsonM., BannisterP., BradyM., & SmithS. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825–841.
15.
KaliaL. V., & O’ConnorP. W. (2005). Severity of chronic pain and its relationship to quality of life in multiple sclerosis. Multiple Sclerosis, 11, 322–327.
16.
KellerJ. L., FritzN., ChiangC. C., JiangA., ThompsonT., CornetN., NewsomeS. D., CalabresiP. A., & ZackowskiK. M. (2016). Adapted Resistance Training Improves Strength in Eight Weeks in Individuals with Multiple Sclerosis. J Vis Exp, 107, e53449. doi: 10.3791/53449
17.
KennerM., MenonU., & ElliottD. G. (2007). Multiple sclerosis as a painful disease. International Review of Neurobiology, 79, doi: 10.1016/S0074-7742(07)79013-X
18.
KieseierB. C., & PozzilliC. (2012). Assessing walking disability in multiple sclerosis. Mult Scler, 18, 914–924.
19.
LazeronR. H. C., BoringaJ. B., SchoutenM., UitdehaagB. M. J., BergersE., LindeboomJ., EikelenboomM. J., ScheltensP. H., BarhofF., & PolmanC. H. (2005). Brain atrophy and lesion load as explaining parameters for cognitive impairment in multiple sclerosis. Mult Scler, 11, 524–531.
20.
MaghziA. H., RevirajanN., JulianL. J., SpainR., MowryE. M., LiuS., JinC., GreenA. J., McCullochC. E., PelletierD., & WaubantE. (2014). Magnetic resonance imaging correlates of clinical outcomes in early multiple sclerosis. Mult Scler Relat Disord, 3, 720–727.
21.
McHorneyC. A., WareJ. E.Jr, LuJ. F., & SherbourneC. D. (1994). The MOS 36-item short-form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care, 32, 40–66.
22.
MillerA. K., BassoM. R., CandilisP. J., CombsD. R., & WoodsS. P. (2014). Pain is associated with prospective memory dysfunction in multiple sclerosis. J Clin Exp Neuropsychol, 36(8), 887–896.
23.
MillerA., & DishonS. (2005). Health-related quality of life in multiple sclerosis: Psychometric analysis of inventories. Mult Scler, 11, 450–458.
24.
MowryE. M., BeheshtianA., WaubantE., GoodinD. S., CreeB. A., QualleyP., LincolnR., GeorgeM. F., GomezR., HauserS. L., OkudaD. T., & PelletierD. (2009). Quality of life in multiple sclerosis is associated with lesion burden and brain volume measures. Neurology, 72, 1760–1765.
25.
O’ConnorA. B., SchwidS. R., HerrmannD. N., MarkmanJ. D., & DworkinR. H. (2008). Pain associated with multiple sclerosis: Systematic review and proposed classification. Pain, 137, 96–111.
26.
OsborneT. L., RaichleK. A., JensenM. P., EhdeD. M., & KraftG. (2006). The reliability and validity of pain interference measures in persons with multiple sclerosis. Journal of Pain and Symptom Management, 32, 217–229.
27.
PapadopoulouA., Muller-LenkeN., NaegelinY., KaltG., BendfeldtK., KusterP., StoecklinM., GassA., SprengerT., RadueE. W., KapposL., & PennerI. K. (2013). Contribution of cortical white matter lesions to cognitive impairment in multiple sclerosis. Mult Scler, 19(10), 1290–1296.
RoyS., HeQ., SweeneyE., CarassA., PrinceJ. L., & PhamD. L. (2015). Subject-specific sparse dictionary learning for atlas-based brain MRI segmentation. IEEE Journal of Biomedical and Health Informatics, 19(5), 1598–1609.
33.
RudickR. A., MillerD., HassS., HutchinsonM., CalabresiP. A., ConfavreuxC., GalettaS. L., GiovannoniG., HavrdovaE., KapposL., LublinF. D., MillerD. H., O’ConnorP. W., PhillipsJ. T., PolmanC. H., RadueE. W., StuartW. H., WajgtA., Weinstock-GuttmanB., WynnD. R., LynnF., & PanzaraM. A. (2007). Health-related quality of life in multiple sclerosis: Effects of natalizumab. Ann Neurol, 62, 335–346.
34.
SbardellaE., PetsasN., TonaF., ProsperiniL., RazE., PaceG., PozzilliC., & PantanoP. (2013). Assessing the correlation between grey and white matter damage with motor and cognitive impairment in multiple sclerosis patients. PLoS ONE, 8(5), e63250. doi: 10.1371/journal.pone.0063250
35.
SeixasD., FoleyP., LimaD., RamosI., & TraceyI. (2014). Pain in multiple sclerosis: A systematic review of neuroimaging studies. Neuroimage Clin, 5, 322–331.
36.
ShieeN., BazinP. L., OzturkA., ReichD. S., CalabresiP. A., & PhamD. L. (2010). A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions. Neruoimage, 49(2), 1524–1535.
37.
ShieeN., BazinP. L., ZackowskiK. M., FarrellS. K., HarrisonD. M., NewsomeS. D., RatchfordJ. N., CaffoB. S., CalabresiP. A., PhamD. L., & ReichD. S. (2012). Revisiting brain atrophy and its relationship to disability in multiple sclerosis. PLoS ONE, 7(5), e37049.
38.
SmithA. (1982). Symbol Digit Modalities Test. Los Angeles, CA: Western Psychological Services.
39.
ŠteckováT., HluštíkP., SládkováV., OdstrčilF., Mareš;J., & KanovskyP. (2014). Thalamic atrophy and cognitive impairment in clinically isolated syndrome and multiple sclerosis. J Neurol Sci, 342, 62–68.
40.
SvendsenK. B., JensenT. S., HansenH. J., & BachF. W. (2005). Sensory function and quality of life in patients with multiple sclerosis and pain. Pain, 114, 473–481.
41.
TabriziF. M., & RadfarM. (2015). Fatigue, sleep quality, and disability in relation to quality of life in multiple sclerosis. Int J MS Care, 17, 268–274.
42.
TustisonN. J., AvantsB. B., CookP. A., ZhengY., EganA., YushkevichP. A., & GeeJ. C. (2010). N4ITK: Improved N3 bias correction. IEEE Transactions on Medical Imaging, 29(6), 1310–1320.
43.
VickreyB. G., HaysR. D., HarooniR., MyersL. W., & EllisonG. W. (1995). A health-related quality of life measure for multiple sclerosis. Quality of Life Research, 4, 187–206.
44.
VollmerT., HuynhL., KelleyC., GalebachP., SignorovitchJ., DiBernardoA., & SasaneR. (2016). Relationship between brain volume loss and cognitive outcomes among patients with multiple sclerosis: A systematic literature review. Neurol Sci, 37(2), 165–179.
45.
WareJ. E., & SherbourneC. D. (1992). The MOS 36-item short-form health survey (SF-36). Medical Care, 30(6), 473–483.
