Incidental evidence of hypointensity in brain grey nuclei on routine MR imaging: when to suspect a neurodegenerative disorder?
Aging
Deep grey nuclei
Healthy subjects
MR imaging
T2 gradient-echo hypointensity
Journal
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
ISSN: 1590-3478
Titre abrégé: Neurol Sci
Pays: Italy
ID NLM: 100959175
Informations de publication
Date de publication:
Jan 2022
Jan 2022
Historique:
received:
14
01
2021
accepted:
26
04
2021
pubmed:
2
5
2021
medline:
6
1
2022
entrez:
1
5
2021
Statut:
ppublish
Résumé
Deep grey nuclei of the human brain accumulate minerals both in aging and in several neurodegenerative diseases. Mineral deposition produces a shortening of the transverse relaxation time which causes hypointensity on magnetic resonance (MR) imaging. The physician often has difficulties in determining whether the incidental hypointensity of grey nuclei seen on MR images is related to aging or neurodegenerative pathology. We investigated the hypointensity patterns in globus pallidus, putamen, caudate nucleus, thalamus and dentate nucleus of 217 healthy subjects (ages, 20-79 years; men/women, 104/113) using 3T MR imaging. Hypointensity was detected more frequently in globus pallidus (35.5%) than in dentate nucleus (32.7%) and putamen (7.8%). A consistent effect of aging on hypointensity (p < 0.001) of these grey nuclei was evident. Putaminal hypointensity appeared only in elderly subjects whereas we did not find hypointensity in the caudate nucleus and thalamus of any subject. In conclusion, the evidence of hypointensity in the caudate nucleus and thalamus at any age or hypointensity in the putamen seen in young subjects should prompt the clinician to consider a neurodegenerative disease.
Identifiants
pubmed: 33931819
doi: 10.1007/s10072-021-05292-1
pii: 10.1007/s10072-021-05292-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
643-650Informations de copyright
© 2021. Fondazione Società Italiana di Neurologia.
Références
Hallgren B, Sourander P (1958) The effect of age on the non-haemin iron in the human brain. J Neurochem 3:41–51. https://doi.org/10.1111/j.1471-4159.1958.tb12607.x
doi: 10.1111/j.1471-4159.1958.tb12607.x
pubmed: 13611557
Haacke EM, Cheng NYC, House MJ, Liu Q, Neelavalli J, Ogg RJ, Khan A, Ayaz M, Kirsch W, Obenaus A (2005) Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging 23:1–25. https://doi.org/10.1016/j.mri.2004.10.001
doi: 10.1016/j.mri.2004.10.001
pubmed: 15733784
Loeffler DA, Connor JR, Juneau PL, Snyder BS, Kanaley L, DeMaggio AJ, Nguyen H, Brickman CM, LeWitt PA (1995) Transferrin and iron in normal, Alzheimer’s disease and Parkinson’s disease brain regions. J Neurochem 65:710–724. https://doi.org/10.1046/j.1471-4159.1995.65020710.x
doi: 10.1046/j.1471-4159.1995.65020710.x
pubmed: 7616227
Bartzokis G, Cummings J, Perlman S, Hance DB, Mintz J (1999) Increased basal ganglia iron levels in Huntington disease. Arch Neurol 56:569–574. https://doi.org/10.1001/archneur.56.5.569
doi: 10.1001/archneur.56.5.569
pubmed: 10328252
Ward RJ, Zucca FA, Duyn JH, Crichton RR, Zecca L (2014) The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol 13:1045–1060. https://doi.org/10.1016/S1474-4422(14)70117-6
doi: 10.1016/S1474-4422(14)70117-6
pubmed: 25231526
pmcid: 5672917
Bizzi A, Brooks RA, Brunetti A, Hill JM, Alger JR, Miletich RS, Francavilla TL, Di Chiro G (1990) Role of iron and ferritin in MR imaging of the brain: a study in primates at different field strengths. Radiology 177:59–65. https://doi.org/10.1148/radiology.177.1.2399339
doi: 10.1148/radiology.177.1.2399339
pubmed: 2399339
Aquino D, Bizzi A, Grisoli M, Garavaglia B, Bruzzone MG, Nardocci N, Savoiardo M, Chiapparini L (2009) Age-related iron deposition in the basal ganglia: quantitative analysis in healthy subjects. Radiology 252:165–172. https://doi.org/10.1148/radiol.2522081399
doi: 10.1148/radiol.2522081399
pubmed: 19561255
Bilgic B, Pfefferbaum A, Rohlfing T, Sullivan EV, Adalsteinsson E (2012) MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. Neuroimage 59:2625–2635. https://doi.org/10.1016/j.neuroimage.2011.08.077
doi: 10.1016/j.neuroimage.2011.08.077
pubmed: 21925274
Glatz A, Valdés Hernández MC, Kiker AJ, Bastin ME, Deary IJ, Wardlaw JM (2013) Characterization of multifocal T2*-weighted MRI hypointensities in the basal ganglia of elderly, community-dwelling subjects. Neuroimage 82:470–480. https://doi.org/10.1016/j.neuroimage.2013.06.013
doi: 10.1016/j.neuroimage.2013.06.013
pubmed: 23769704
Haacke EM, Miao Y, Liu M, Habib CA, Katkuri Y, Liu T, Yang Z, Lang Z, Hu J, Wu J (2010) Correlation of putative iron content as represented by changes in R2* and phase with age in deep gray matter of healthy adults. J Magn Reson Imaging 32:561–576. https://doi.org/10.1002/jmri.22293
doi: 10.1002/jmri.22293
pubmed: 20815053
pmcid: 2936709
Li W, Wu B, Batrachenko A, Bancroft-Wu V, Morey RA, Shashi V, Langkammer C, De Bellis MD, Ropele S, Song AW, Liu C (2014) Differential developmental trajectories of magnetic susceptibility in human brain gray and white matter over the lifespan. Hum Brain Mapp 35:2698–2713. https://doi.org/10.1002/hbm.22360
doi: 10.1002/hbm.22360
pubmed: 24038837
Persson N, Wu J, Zhang Q, Liu T, Shen J, Bao R, Ni M, Liu T, Wang Y, Spincemaille P (2015) Age and sex related differences in subcortical brain iron concentrations among healthy adults. Neuroimage 122:385–398. https://doi.org/10.1016/j.neuroimage.2015.07.050
doi: 10.1016/j.neuroimage.2015.07.050
pubmed: 26216277
Pfefferbaum A, Adalsteinsson E, Rohlfing T, Sullivan EV (2009) MRI estimates of brain iron concentration in normal aging: comparison of field-dependent (FDRI) and phase (SWI) methods. Neuroimage 47:493–500. https://doi.org/10.1016/j.neuroimage.2009.05.006
doi: 10.1016/j.neuroimage.2009.05.006
pubmed: 19442747
Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12:189–198. https://doi.org/10.1016/0022-3956(75)90026-6
doi: 10.1016/0022-3956(75)90026-6
De Renzi E, Vignolo LA (1962) The token test: a sensitive test to detect receptive disturbances in aphasics. Brain 85:665–678. https://doi.org/10.1093/brain/85.4.665
doi: 10.1093/brain/85.4.665
Carlesimo GA, Caltagirone C, Gainotti G (1996) The mental deterioration battery: normative data, diagnostic reliability and qualitative analyses of cognitive impairment. The group for the standardization of the mental deterioration battery. Eur Neurol 36:378–384. https://doi.org/10.1159/000117297
doi: 10.1159/000117297
pubmed: 8954307
Zappalà G, Measso G, Cavarzeran F, Grigoletto F, Lebowitz B, Pirozzolo F, Amaducci L, Massari D, Crook T (1995) Aging and memory: corrections for age, sex and education for three widely used memory tests. Ital J Neurol Sci 16:177–184. https://doi.org/10.1007/BF02282985
doi: 10.1007/BF02282985
pubmed: 7558772
Caffarra P, Vezzadini G, Dieci F, Zonato F, Venneri A (2004) Modified card sorting test: normative data. J Clin Exp Neuropsychol 26:246–250. https://doi.org/10.1076/jcen.26.2.246.28087
doi: 10.1076/jcen.26.2.246.28087
pubmed: 15202543
Appollonio I, Leone M, Isella V, Piamarta F, Consoli T, Villa ML, Forapani E, Russo A, Nichelli P (2005) The Frontal Assessment Battery (FAB): normative values in an Italian population sample. Neurol Sci 26:108–111. https://doi.org/10.1007/s10072-005-0443-4
doi: 10.1007/s10072-005-0443-4
pubmed: 15995827
Orsini A, Grossi D, Capitani E, Laiacona M, Papagno C, Vallar G (1987) Verbal and spatial immediate memory span: normative data from 1355 adults and 1112 children. Ital J Neurol Sci 8:539–548. https://doi.org/10.1007/BF02333660
doi: 10.1007/BF02333660
pubmed: 3429213
Treccani B, Cubelli R (2011) The need for a revised version of the Benton judgment of line orientation test. J Clin Exp Neuropsychol 33:249–256. https://doi.org/10.1080/13803395.2010.511150
doi: 10.1080/13803395.2010.511150
pubmed: 20924915
Hamilton M (1959) The assessment of anxiety states by rating. Br J Med Psychol 32:50–55. https://doi.org/10.1111/j.2044-8341.1959.tb00467.x
doi: 10.1111/j.2044-8341.1959.tb00467.x
pubmed: 13638508
Beck AT, Steer RA (1987) Depression inventory scoring manual. The Psychological Corporation, New York
Langkammer C, Krebs N, Goessler W, Scheurer E, Ebner F, Yen K, Fazekas F, Ropele S (2010) Quantitative MR imaging of brain iron: a postmortem validation study. Radiology 257:455–462. https://doi.org/10.1148/radiol.10100495
doi: 10.1148/radiol.10100495
pubmed: 20843991
Ramos P, Santos A, Pinto NR, Mendes R, Magalhães T, Almeida A (2014) Iron levels in the human brain: a post-mortem study of anatomical region differences and age-related changes. J Trace Elem Med Biol 28:13–17. https://doi.org/10.1016/j.jtemb.2013.08.001
doi: 10.1016/j.jtemb.2013.08.001
pubmed: 24075790
Casanova MF, Araque JM (2003) Mineralization of the basal ganglia: implications for neuropsychiatry, pathology and neuroimaging. Psychiatry Res 121:59–87. https://doi.org/10.1016/s0165-1781(03)00202-6
doi: 10.1016/s0165-1781(03)00202-6
pubmed: 14572624
Maschke M, Weber J, Dimitrova A, Bonnet U, Bohrenkämper J, Sturm S, Kindsvater K, Müller BW, Gastpar M, Diener HC, Forsting M, Timmann D (2004) Age-related changes of the dentate nuclei in normal adults as revealed by 3D fast low angle shot (FLASH) echo sequence magnetic resonance imaging. J Neurol 251:740–746. https://doi.org/10.1007/s00415-004-0420-5
doi: 10.1007/s00415-004-0420-5
pubmed: 15311352
McNeill A, Birchall D, Hayflick SJ, Gregory A, Schenk JF, Zimmerman EA, Shang H, Miyajima H, Chinnery PF (2008) T2* and FSE MRI distinguishes four subtypes of neurodegeneration with brain iron accumulation. Neurology 70:1614–1619. https://doi.org/10.1212/01.wnl.0000310985.40011.d6
doi: 10.1212/01.wnl.0000310985.40011.d6
pubmed: 18443312
pmcid: 2706154
Gagliardi M, Morelli M, Annesi G, Nicoletti G, Perrotta P, Pustorino G, Iannello G, Tarantino P, Gambardella A, Quattrone A (2015) A new SLC20A2 mutation identified in southern Italy family with primary familial brain calcification. Gene 568:109–111. https://doi.org/10.1016/j.gene.2015.05.005
doi: 10.1016/j.gene.2015.05.005
pubmed: 25958344
Harder SL, Hopp KM, Ward H, Neglio H, Gitlin J, Kido D (2008) Mineralization of the deep gray matter with age: a retrospective review with susceptibility-weighted MR imaging. AJNR Am J Neuroradiol 29:176–183. https://doi.org/10.3174/ajnr.A0770
doi: 10.3174/ajnr.A0770
pubmed: 17989376
pmcid: 8119097
Pfefferbaum A, Adalsteinsson E, Rohlfing T, Sullivan EV (2010) Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration. Neurobiol Aging 31:482–493. https://doi.org/10.1016/j.neurobiolaging.2008.04.013
doi: 10.1016/j.neurobiolaging.2008.04.013
pubmed: 18513834
van Es AC, van der Grond J, de Craen AJ, Admiraal-Behloul F, Blauw GJ, van Buchem MA (2008) Caudate nucleus hypointensity in the elderly is associated with markers of neurodegeneration on MRI. Neurobiol Aging 29:1839–1846. https://doi.org/10.1016/j.neurobiolaging.2007.05.008
doi: 10.1016/j.neurobiolaging.2007.05.008
pubmed: 17599695
Shepherd J, Blauw GJ, Murphy MB, Cobbe SM, Bollen EL, Buckley BM, Ford I, Jukema JW, Hyland M, Gaw A, Lagaay AM, Perry IJ, Macfarlane PW, Meinders AE, Sweeney BJ, Packard CJ, Westendorp RG, Twomey C, Stott DJ (1999) The design of a prospective study of Pravastatin in the Elderly at Risk (PROSPER). PROSPER Study Group. PROspective Study of Pravastatin in the Elderly at Risk. Am J Cardiol 84:1192–1197. https://doi.org/10.1016/s0002-9149(99)00533-0
doi: 10.1016/s0002-9149(99)00533-0
pubmed: 10569329
Penke L, Valdés Hernandéz MC, Maniega SM, Gow AJ, Murray C, Starr JM, Bastin ME, Deary IJ, Wardlaw JM (2012) Brain iron deposits are associated with general cognitive ability and cognitive aging. Neurobiol Aging 33:510–517. https://doi.org/10.1016/j.neurobiolaging.2010.04.032
doi: 10.1016/j.neurobiolaging.2010.04.032
pubmed: 20542597
Bartzokis G, Tishler TA, Lu PH, Villablanca P, Altshuler LL, Carter M, Huang D, Edwards N, Mintz J (2007) Brain ferritin iron may influence age- and gender-related risks of neurodegeneration. Neurobiol Aging 28:414–423. https://doi.org/10.1016/j.neurobiolaging.2006.02.005
doi: 10.1016/j.neurobiolaging.2006.02.005
pubmed: 16563566
Hagemeier J, Tong O, Dwyer MG, Schweser F, Ramanathan M, Zivadinov R (2015) Effects of diet on brain iron levels among healthy individuals: an MRI pilot study. Neurobiol Aging 36:1678–1685. https://doi.org/10.1016/j.neurobiolaging.2015.01.010
doi: 10.1016/j.neurobiolaging.2015.01.010
pubmed: 25680267
Tishler TA, Raven EP, Lu PH, Altshuler LL, Bartzokis G (2012) Premenopausal hysterectomy is associated with increased brain ferritin iron. Neurobiol Aging 33:1950–1958. https://doi.org/10.1016/j.neurobiolaging.2011.08.002
Xu X, Wang Q, Zhang M (2008) Age, gender, and hemispheric differences in iron deposition in the human brain: an in vivo MRI study. Neuroimage 40:35–42. https://doi.org/10.1016/j.neuroimage.2007.11.017
doi: 10.1016/j.neuroimage.2007.11.017
pubmed: 18180169
Arabia G, Morelli M, Paglionico S, Novellino F, Salsone M, Giofrè L, Torchia G, Nicoletti G, Messina D, Condino F, Lanza P, Gallo O, Quattrone A (2010) An magnetic resonance imaging T2*-weighted sequence at short echo time to detect putaminal hypointensity in parkinsonisms. Mov Disord 25:2728–2734. https://doi.org/10.1002/mds.23173
doi: 10.1002/mds.23173
pubmed: 20925073
Yekhlef F, Ballan G, Macia F, Delmer O, Sourgen C, Tison F (2003) Routine MRI for the differential diagnosis of Parkinson’s disease, MSA, PSP, and CBD. J Neural Transm 110:151–169. https://doi.org/10.1007/s00702-002-0785-5
doi: 10.1007/s00702-002-0785-5
pubmed: 12589575