Show simple item record

dc.creatorGracitelli C.P.
dc.creatorDuque-Chica G.L.
dc.creatorSanches L.G.
dc.creatorMoura A.L.
dc.creatorNagy B.V.
dc.creatorTeixeira S.H.
dc.creatorAmaro E.
dc.creatorVentura D.F.
dc.creatorParanhos A.
dc.date2020
dc.date.accessioned2021-02-05T14:58:48Z
dc.date.available2021-02-05T14:58:48Z
dc.identifier.issn10570829
dc.identifier.urihttp://hdl.handle.net/11407/6020
dc.descriptionPurpose: To evaluate structural brain abnormalities in glaucoma patients using 3-Tesla magnetic resonance imaging and assess their correlation with associated structural and functional ocular findings. Patients and Methods: This cross-sectional prospective study included 30 glaucoma patients and 18 healthy volunteers. All participants underwent standard automated perimetry, spectral-domain optical coherence tomography, and 3.0-Tesla magnetic resonance imaging. Results: There was a significant difference between the surface area of the occipital pole in the left hemisphere of glaucoma patients (mean: 1253.9±149.3 mm2) and that of control subjects (mean: 1341.9±129.8 mm2), P=0.043. There was also a significant difference between the surface area of the occipital pole in the right hemisphere of glaucoma patients (mean: 1910.5±309.4 mm2) and that of control subjects (mean: 2089.1±164.2 mm2), P=0.029. There was no significant difference between the lingual, calcarine, superior frontal, and inferior frontal gyri of glaucoma patients and those of the control subjects (P>0.05 for all comparisons). The surface area of the occipital pole in the left hemisphere was significantly correlated with perimetry mean deviation values, visual acuity, age, and retinal nerve fiber layer thickness (P=0.001, P<0.001, P=0.010, P=0.006, respectively). The surface area of the occipital pole in the right hemisphere was significantly correlated with perimetry mean deviation values, visual field indices, visual acuity, age, and retinal nerve fiber layer thickness (P<0.001, P=0.007, P<0.001, P=0.046, P<0.001, respectively). Conclusions: Glaucoma patients presented a decreased occipital pole surface area in both hemispheres that independently correlated with functional and structural ocular parameters. Copyright © 2020 Wolters Kluwer Health, Inc.
dc.language.isoeng
dc.publisherLippincott Williams and Wilkins
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85080029636&doi=10.1097%2fIJG.0000000000001470&partnerID=40&md5=606bbbf100289a0010e14e4651d237da
dc.sourceJournal of Glaucoma
dc.subject3-Teslaspa
dc.subjectglaucomaspa
dc.subjectmagnetic resonance imagingspa
dc.subjectoccipital polespa
dc.subjectvisual fieldspa
dc.titleStructural Analysis of Glaucoma Brain and its Association with Ocular Parameters
dc.typeArticleeng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programPsicologíaspa
dc.identifier.doi10.1097/IJG.0000000000001470
dc.publisher.facultyFacultad de Ciencias Sociales y Humanasspa
dc.affiliationGracitelli, C.P., Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, São Paulo Hospital, Federal University of São Paulo, Brazil
dc.affiliationDuque-Chica, G.L., Institute of Psychology, University of São Paulo, São Paulo, Brazil, Department of Psychology, University of Medellin, Medellin, Colombia
dc.affiliationSanches, L.G., Hospital Israelita Albert Einstein, São Paulo, Brazil
dc.affiliationMoura, A.L., Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, São Paulo Hospital, Federal University of São Paulo, Brazil, Institute of Psychology, University of São Paulo, São Paulo, Brazil
dc.affiliationNagy, B.V., Institute of Psychology, University of São Paulo, São Paulo, Brazil, Department of Mechatronics, Optics and Engineering Informatics, Budapest University of Technology and Economics, Budapest, Hungary
dc.affiliationTeixeira, S.H., Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, São Paulo Hospital, Federal University of São Paulo, Brazil
dc.affiliationAmaro, E., Hospital Israelita Albert Einstein, São Paulo, Brazil
dc.affiliationVentura, D.F., Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, São Paulo Hospital, Federal University of São Paulo, Brazil, Institute of Psychology, University of São Paulo, São Paulo, Brazil
dc.affiliationParanhos, A., Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, São Paulo Hospital, Federal University of São Paulo, Brazil, Hospital Israelita Albert Einstein, São Paulo, Brazil
dc.relation.referencesWeinreb, R.N., Aung, T., Medeiros, F.A., The pathophysiology and treatment of glaucoma: A review (2014) JAMA, 311 (18), pp. 1901-1911
dc.relation.referencesTham, Y.C., Li, X., Wong, T.Y., Global prevalence of glaucoma and projections of glaucoma burden through 2040: A systematic review and meta-analysis (2014) Ophthalmology, 121 (11), pp. 2081-2090
dc.relation.referencesWeber, A.J., Chen, H., Hubbard, W.C., Kaufman, P.L., Experimental glaucoma and cell size, density, and number in the primate lateral geniculate nucleus (2000) Invest Ophthalmol Vis Sci, 41 (6), pp. 1370-1379
dc.relation.referencesYucel, Y.H., Zhang, Q., Weinreb, R.N., Effects of retinal ganglion cell loss on magno-, parvo-, koniocellular pathways in the lateral geniculate nucleus and visual cortex in glaucoma (2003) Prog Retin Eye Res, 22 (4), pp. 465-481
dc.relation.referencesGupta, N., Ang, L.C., Noel-De-Tilly, L., Human glaucoma and neural degeneration in intracranial optic nerve, lateral geniculate nucleus, and visual cortex (2006) Br J Ophthalmol, 90 (6), pp. 674-678
dc.relation.referencesDuyn, J.H., Study of brain anatomy with high-field MRI: Recent progress (2010) Magn Reson Imaging, 28 (8), pp. 1210-1215
dc.relation.referencesNuzzi, R., Dallorto, L., Rolle, T., Changes of visual pathway and brain connectivity in glaucoma: A systematic review (2018) Front Neurosci, 12, p. 363
dc.relation.referencesLi, C., Cai, P., Shi, L., Voxel-based morphometry of the visual-related cortex in primary open angle glaucoma (2012) Curr Eye Res, 37 (9), pp. 794-802
dc.relation.referencesChen, W.W., Wang, N., Cai, S., Structural brain abnormalities in patients with primary open-angle glaucoma: A study with 3T MR imaging (2013) Invest Ophthalmol Vis Sci, 54 (1), pp. 545-554
dc.relation.referencesBogorodzki, P., Piatkowska-Janko, E., Szaflik, J., Mapping cortical thickness of the patients with unilateral end-stage open angle glaucoma on planar cerebral cortex maps (2014) PLoS One, 9 (4)
dc.relation.referencesIto, Y., Shimazawa, M., Chen, Y.N., Morphological changes in the visual pathway induced by experimental glaucoma in Japanese monkeys (2009) Exp Eye Res, 89 (2), pp. 246-255
dc.relation.referencesGupta, N., Greenberg, G., De-Tilly, L.N., Atrophy of the lateral geniculate nucleus in human glaucoma detected by magnetic resonance imaging (2009) Br J Ophthalmol, 93 (1), pp. 56-60
dc.relation.referencesFurlanetto, R.L., Teixeira, S.H., Gracitelli, C.P.B., Structural and functional analyses of the optic nerve and lateral geniculate nucleus in glaucoma (2018) PLoS One, 13 (3)
dc.relation.referencesMedeiros, F.A., Alencar, L.M., Zangwill, L.M., Prediction of functional loss in glaucoma from progressive optic disc damage (2009) Arch Ophthalmol, 127 (10), pp. 1250-1256
dc.relation.referencesMedeiros, F.A., Alencar, L.M., Zangwill, L.M., The relationship between intraocular pressure and progressive retinal nerve fiber layer loss in glaucoma (2009) Ophthalmology, 116 (6), pp. 1125-1133
dc.relation.referencesLeung, C.K., Chiu, V., Weinreb, R.N., Evaluation of retinal nerve fiber layer progression in glaucoma: A comparison between spectral-domain and time-domain optical coherence tomography (2011) Ophthalmology, 118 (8), pp. 1558-1562
dc.relation.referencesArtes, P.H., Chauhan, B.C., Longitudinal changes in the visual field and optic disc in glaucoma (2005) Prog Retin Eye Res, 24 (3), pp. 333-354
dc.relation.referencesHodap, E.E., Anderson, D.R., II, (1993) Clinical Decisions in Glaucoma, pp. 52-61. , Mo Mosby-Year Book
dc.relation.referencesSponsel, W.E., Ritch, R., Stamper, R., Prevent blindness America visual field screening study. The prevent blindness America Glaucoma Advisory Committee (1995) Am J Ophthalmol, 120 (6), pp. 699-708
dc.relation.referencesSponsel, W.E., Arango, S., Trigo, Y., Mensah, J., Clinical classification of glaucomatous visual field loss by frequency doubling perimetry (1998) Am J Ophthalmol, 125 (6), pp. 830-836
dc.relation.referencesMedeiros, F.A., Lisboa, R., Weinreb, R.N., Retinal ganglion cell count estimates associated with early development of visual field defects in glaucoma (2013) Ophthalmology, 120 (4), pp. 736-744
dc.relation.referencesDale, A.M., Fischl, B., Sereno, M.I., Cortical surface-based analysis. I. Segmentation and surface reconstruction (1999) Neuroimage, 9 (2), pp. 179-194
dc.relation.referencesFischl, B., Dale, A.M., Measuring the thickness of the human cerebral cortex from magnetic resonance images (2000) Proc Natl Acad Sci U S A, 97 (20), pp. 11050-11055
dc.relation.referencesRosas, H.D., Liu, A.K., Hersch, S., Regional and progressive thinning of the cortical ribbon in huntington's disease (2002) Neurology, 58 (5), pp. 695-701
dc.relation.referencesKuperberg, G.R., Broome, M.R., McGuire, P.K., Regionally localized thinning of the cerebral cortex in schizophrenia (2003) Arch Gen Psychiatry, 60 (9), pp. 878-888
dc.relation.referencesAfonso, R.F., Balardin, J.B., Lazar, S., Greater cortical thickness in elderly female yoga practitioners-A cross-sectional study (2017) Front Aging Neurosci, 9, p. 201
dc.relation.referencesFischl, B., Van-Der-Kouwe, A., Destrieux, C., Automatically parcellating the human cerebral cortex (2004) Cereb Cortex, 14 (1), pp. 11-22
dc.relation.referencesBurton, P., Gurrin, L., Sly, P., Extending the simple linear regression model to account for correlated responses: An introduction to generalized estimating equations and multi-level mixed modelling (1998) Stat Med, 17 (11), pp. 1261-1291
dc.relation.referencesHanley, J.A., Negassa, A., Edwardes, M.D., Forrester, J.E., Statistical analysis of correlated data using generalized estimating equations: An orientation (2003) Am J Epidemiol, 157 (4), pp. 364-375
dc.relation.referencesField, C.A., Welsh, A.H., Bootstrapping clustered data (2007) Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69 (3), pp. 369-390
dc.relation.referencesFurlanetto, R.L., Teixeira, S.H., Gracitelli, C.P., Structural and functional analyses of the optic nerve and lateral geniculate nucleus in glaucoma (2018) PLoS One, , In Press
dc.relation.referencesPerry, V.H., Oehler, R., Cowey, A., Retinal ganglion cells that project to the dorsal lateral geniculate nucleus in the macaque monkey (1984) Neuroscience, 12 (4), pp. 1101-1123
dc.relation.referencesGupta, N., Yucel, Y.H., What changes can we expect in the brain of glaucoma patients? (2007) Surv Ophthalmol, 52, pp. S122-S126
dc.relation.referencesZhang, Y.Q., Li, J., Xu, L., Anterior visual pathway assessment by magnetic resonance imaging in normal-pressure glaucoma (2012) Acta Ophthalmol, 90 (4), pp. e295-e302
dc.relation.referencesDuncan, R.O., Sample, P.A., Weinreb, R.N., Retinotopic organization of primary visual cortex in glaucoma: Comparing fMRI measurements of cortical function with visual field loss (2007) Prog Retin Eye Res, 26 (1), pp. 38-56
dc.relation.referencesDuncan, R.O., Sample, P.A., Weinreb, R.N., Retinotopic organization of primary visual cortex in glaucoma: A method for comparing cortical function with damage to the optic disk (2007) Invest Ophthalmol Vis Sci, 48 (2), pp. 733-744
dc.relation.referencesQing, G., Zhang, S., Wang, B., Wang, N., Functional MRI signal changes in primary visual cortex corresponding to the central normal visual field of patients with primary open-angle glaucoma (2010) Invest Ophthalmol Vis Sci, 51 (9), pp. 4627-4634
dc.relation.referencesGerente, V.M., Schor, R.R., Chaim, K.T., Evaluation of glaucomatous damage via functional magnetic resonance imaging, and correlations thereof with anatomical and psychophysical ocular findings (2015) PLoS One, 10 (5)
dc.relation.referencesAmaro, E., Jr., Barker, G.J., Study design in fMRI: Basic principles (2006) Brain Cogn, 60 (3), pp. 220-232
dc.relation.referencesLogothetis, N.K., Wandell, B.A., Interpreting the BOLD signal (2004) Annu Rev Physiol, 66, pp. 735-769
dc.relation.referencesWinkler, A.M., Kochunov, P., Blangero, J., Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies (2010) Neuroimage, 53 (3), pp. 1135-1146
dc.relation.referencesThompson, P.M., Cannon, T.D., Narr, K.L., Genetic influences on brain structure (2001) Nat Neurosci, 4 (12), pp. 1253-1258
dc.relation.referencesGlahn, D.C., Thompson, P.M., Blangero, J., Neuroimaging endophenotypes: Strategies for finding genes influencing brain structure and function (2007) Hum Brain Mapp, 28 (6), pp. 488-501
dc.relation.referencesHonea, R.A., Meyer-Lindenberg, A., Hobbs, K.B., Is gray matter volume an intermediate phenotype for schizophrenia? A voxel-based morphometry study of patients with schizophrenia and their healthy siblings (2008) Biol Psychiatry, 63 (5), pp. 465-474
dc.relation.referencesMcDonald, C., Marshall, N., Sham, P.C., Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives (2006) Am J Psychiatry, 163 (3), pp. 478-487
dc.relation.referencesPanizzon, M.S., Fennema-Notestine, C., Eyler, L.T., Distinct genetic influences on cortical surface area and cortical thickness (2009) Cereb Cortex, 19 (11), pp. 2728-2735
dc.relation.referencesHofman, M.A., Size and shape of the cerebral cortex in mammals. I. The cortical surface (1985) Brain Behav Evol, 27 (1), pp. 28-40
dc.relation.referencesRao, D.C., An overview of the genetic dissection of complex traits (2008) Adv Genet, 60, pp. 3-34
dc.relation.referencesCosgrove, K.P., Mazure, C.M., Staley, J.K., Evolving knowledge of sex differences in brain structure, function, and chemistry (2007) Biol Psychiatry, 62 (8), pp. 847-855
dc.relation.referencesAnkney, C.D., The brain size/IQ debate (1992) Nature, 360 (6402), p. 292
dc.relation.referencesAnkney, C.D., Differences in brain size (1992) Nature, 358 (6387), p. 532
dc.relation.referencesHernowo, A.T., Boucard, C.C., Jansonius, N.M., Automated morphometry of the visual pathway in primary open-angle glaucoma (2011) Invest Ophthalmol Vis Sci, 52 (5), pp. 2758-2766
dc.relation.referencesZikou, A.K., Kitsos, G., Tzarouchi, L.C., Voxel-based morphometry and diffusion tensor imaging of the optic pathway in primary open-angle glaucoma: A preliminary study (2012) AJNR Am J Neuroradiol, 33 (1), pp. 128-134
dc.relation.referencesWilliams, A.L., Lackey, J., Wizov, S.S., Evidence for widespread structural brain changes in glaucoma: A preliminary voxel-based MRI study (2013) Invest Ophthalmol Vis Sci, 54 (8), pp. 5880-5887
dc.relation.referencesAllen, J.S., Bruss, J., Brown, C.K., Damasio, H., Normal neuroanatomical variation due to age: The major lobes and a parcellation of the temporal region (2005) Neurobiol Aging, 26 (9), pp. 1245-1260. , discussion 79-82
dc.relation.referencesLemaitre, H., Goldman, A.L., Sambataro, F., Normal age-related brain morphometric changes: Nonuniformity across cortical thickness, surface area and gray matter volume? (2012) Neurobiol Aging, 33 (3), pp. e1-e9
dc.relation.referencesFotenos, A.F., Snyder, A.Z., Girton, L.E., Normative estimates of crosssectional and longitudinal brain volume decline in aging and AD (2005) Neurology, 64 (6), pp. 1032-1039
dc.relation.referencesGood, C.D., Johnsrude, I.S., Ashburner, J., A voxel-based morphometric study of ageing in 465 normal adult human brains (2001) Neuroimage, 14 (1), pp. 21-36
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record