Skip to main content Accessibility help
Hostname: page-component-55597f9d44-mzfmx Total loading time: 0.932 Render date: 2022-08-13T03:42:18.773Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "useNewApi": true } hasContentIssue true

Chapter 41 - Iron imaging in neurodegenerative disorders

from Section 6 - Psychiatric and neurodegenerative diseases

Published online by Cambridge University Press:  05 March 2013

Jonathan H. Gillard
University of Cambridge
Adam D. Waldman
Imperial College London
Peter B. Barker
The Johns Hopkins University School of Medicine
Get access



Iron plays an important role in normal neuronal metabolism. Excessive iron is, however, considered to be harmful because of its role in causing oxidative stress. It is well established in the literature that abnormal non-heme iron deposits (in different forms) occur in neurodegenerative disorders, including Alzheimer’s disease (AD), Huntington’s disease (HD), Parkinson’s disease (PD), multiple sclerosis, and neurodegenerative brain iron accumulation (NBIA). This suggests that oxidative stress resulting from imbalance in iron regulation may contribute to the pathological cascade in these diseases. The metabolism of brain iron and its potential role in causing various neurodegenerative disorders has been discussed in detail in Moos and Morgan [1] and Berg and Youdim.[2] Iron imaging will play an important role in understanding the mechanisms and may be useful for early diagnosis of neurodegenerative disorders. This chapter has two objectives: to present the basics of iron signal detection using magnetic resonance imaging (MRI) and to examine the potential of MRI techniques for imaging abnormal iron deposits in various neurodegenerative disorders.

Iron signal in MRI

The MRI approach utilizes the nuclear magnetic resonance of atomic nuclei and, because of the abundance of protons in the human body (primarily in tissue water), MRI machines use signal from protons for imaging. The signal contrast in MR images mainly originates from differences in the proton density, longitudinal relaxation (T1) and transverse relaxation (T2) of protons in different tissues. Additionally in sequences such as gradient echo sequences where there is no 180° radiofrequency pulse to refocus the dephasing resulting from magnetic field inhomogeneity, the amplitude of the gradient echo carries a 1/T2* weighting where 1/T2* = 1/T2 + 1/T2′ where T2′ is the reversible contribution resulting from local magnetic field inhomogeneity. Since MRI detects changes in electromagnetic signals, changes in local magnetic field inhomogeneities caused by the presence of iron alter the signal contrast in the images. The presence of iron is mainly associated with reduction of T1, T2, and T2* relaxation of protons. There has been some recent work on using additional MRI contrasts such as diffusion tensor imaging (DTI) metrics and rotating frame relaxation constants, longitudinal (T1ρ) and transverse (T2ρ), to measure local iron content.

Clinical MR Neuroimaging
Physiological and Functional Techniques
, pp. 642 - 652
Publisher: Cambridge University Press
Print publication year: 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Moos, T, Morgan, EH. The metabolism of neuronal iron and its pathogenic role in neurological disease: review. Ann N Y Acad Sci 2004; 1012: 14–26.CrossRefGoogle Scholar
Berg, D, Youdim MB. Role of iron in neurodegenerative disorders. Top Magn Reson Imaging 2006; 17: 5–17.CrossRefGoogle ScholarPubMed
Vymazal, J, Brooks, RA, Baumgarner, C, et al. The relation between brain iron and NMR relaxation times: an in vitro study. Magn Reson Med 1996; 35: 56–61.CrossRefGoogle Scholar
Haacke, EM, Cheng, NY, House, MJ, et al. Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging 2005; 23: 1–25.Google ScholarPubMed
Haacke, EM, Ayaz, M, Khan, A, et al. Establishing a baseline phase behavior in magnetic resonance imaging to determine normal vs. abnormal iron content in the brain. J Magn Reson Imaging 2007; 26: 256–264.CrossRefGoogle Scholar
Duyn, JH, van Gelderen, P, Li, TQ, et al. High-field MRI of brain cortical substructure based on signal phase. Proc Natl Acad Sci USA 2007; 104: 11796–11801.CrossRefGoogle ScholarPubMed
Ogg, RJ, Langston, JW, Haacke, EM, Steen, RG, Taylor, JS. The correlation between phase shifts in gradient-echo MR images and regional brain iron concentration. Magn Reson Imaging 1999; 17: 1141–1148.CrossRefGoogle ScholarPubMed
Abduljalil, AM, Schmalbrock, P, Novak, V, Chakeres DW. Enhanced gray and white matter contrast of phase susceptibility-weighted images in ultra-high-field magnetic resonance imaging. J Magn Reson Imaging 2003; 18: 284–290.CrossRefGoogle ScholarPubMed
Haacke, EM, Xu, Y, Cheng, YC, Reichenbach, JR.Susceptibility weighted imaging (SWI). Magn Reson Med 2004; 52: 612–618.CrossRefGoogle Scholar
Sehgal, V, Delproposto, Z, Haacke, EM, et al. Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging 2005; 22: 439–450.CrossRefGoogle ScholarPubMed
Stark, DD, Moseley, ME, Bacon, BR, et al. Magnetic resonance imaging and spectroscopy of hepatic iron overload. Radiology 1985; 154: 137–142.CrossRefGoogle ScholarPubMed
Runge, VM, Clanton, JA, Smith, FW, et al. Nuclear magnetic resonance of iron and copper disease states. Am J Roentgenol 1983; 141: 943–948.CrossRefGoogle ScholarPubMed
Drayer, B, Burger, P, Darwin, R, et al. MRI of brain iron. Am J Roentgenol 1986; 147: 103–110.CrossRefGoogle ScholarPubMed
Breger, RK, Rimm, AA, Fischer, ME, Papke, RA, Haughton VM. T1 and T2 measurements on a 1.5-T commercial MR imager. Radiology 1989; 171: 273–276.Google ScholarPubMed
Ordidge, RJ, Gorell, JM, Deniau, JC, Knight, RA, Helpern JA. Assessment of relative brain iron concentrations using T2-weighted and T2*-weighted MRI at 3 Tesla. Magn Reson Med 1994; 32: 335–341.CrossRefGoogle ScholarPubMed
Gelman, N, Gorell, JM, Barker, PB, et al. MR imaging of human brain at 3.0 T: preliminary report on transverse relaxation rates and relation to estimated iron content. Radiology 1999; 210: 759–767.CrossRefGoogle Scholar
Bartzokis, G, Beckson, M, Hance, DB, et al. MR evaluation of age-related increase of brain iron in young adult and older normal males. Magn Reson Imaging 1997; 15: 29–35.CrossRefGoogle ScholarPubMed
Bartzokis, G, Aravagiri, M, Oldendorf, WH, Mintz, J, Marder SR. Field dependent transverse relaxation rate increase may be a specific measure of tissue iron stores. Magn Reson Med 1993; 29: 459–464.CrossRefGoogle ScholarPubMed
Michaeli, S, Oz, G, Sorce, DJ, et al. Assessment of brain iron and neuronal integrity in patients with Parkinson’s disease using novel MRI contrasts. Mov Disord 2007; 22: 334–340.CrossRefGoogle ScholarPubMed
Jensen, JH, Chandra, R, Ramani, A, et al. Magnetic field correlation imaging. Magn Reson Med 2006; 55: 1350–1361.CrossRefGoogle ScholarPubMed
Pfefferbaum, A, Adalsteinsson, E, Rohlfing, T, Sullivan, EV. Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration. Neurobiol Aging 2008; Epub ahead of print, PMID 18513834.Google ScholarPubMed
Hallgren, B, Sourander, P. The effect of age on the non-haemin iron in the human brain. J Neurochem 1958; 3: 41–51.CrossRefGoogle ScholarPubMed
Aoki, S, Okada, Y, Nishimura, K, et al. Normal deposition of brain iron in childhood and adolescence: MR imaging at 1.5 T. Radiology 1989; 172: 381–385.CrossRefGoogle ScholarPubMed
Xu, X, Wang, Q, Zhang, M. Age, gender, and hemispheric differences in iron deposition in the human brain: an in vivo MRI study. Neuroimage 2008; 40: 35–42.CrossRefGoogle Scholar
Berg, D, Hochstrasser, H.Iron metabolism in parkinsonian syndromes. Mov Disord 2006; 21: 1299–1310.CrossRefGoogle ScholarPubMed
Dexter, DT, Wells, FR, Agid, F, et al. Increased nigral iron content in postmortem parkinsonian brain. Lancet 1987; 2: 1219–1220.CrossRefGoogle ScholarPubMed
Sofic, E, Riederer, P, Heinsen, H, et al. Increased iron (III) and total iron content in post mortem substantia nigra of parkinsonian brain. J Neural Transm 1988; 74: 199–205.CrossRefGoogle ScholarPubMed
Drayer, BP, Olanow, W, Burger, P, et al. Parkinson-plus syndrome: diagnosis using high field MR imaging of brain iron. Radiology 1986; 159: 493–498.CrossRefGoogle Scholar
Vymazal, J, Righini, A, Brooks, RA, et al. T1 and T2 in the brain of healthy subjects, patients with Parkinson disease, and patients with multiple system atrophy: relation to iron content. Radiology 1999; 211: 489–495.CrossRefGoogle ScholarPubMed
Bartzokis, G, Tishler, TA, Shin, IS, Lu, PH, Cummings, JL. Brain ferritin iron as a risk factor for age at onset in neurodegenerative diseases. Ann N Y Acad Sci 2004; 1012: 224–236.CrossRefGoogle ScholarPubMed
Martin, WR, Wieler, M, Gee M. Midbrain iron content in early Parkinson disease: a potential biomarker of disease status. Neurology 2008; 70: 1411–1417.CrossRefGoogle ScholarPubMed
Hayflick, SJ, Westaway, SK, Levinson, B, et al. Genetic, clinical, and radiographic delineation of Hallervorden–Spatz syndrome. N Engl J Med 2003; 348: 33–40.CrossRefGoogle ScholarPubMed
Hayflick, SJ, Hartman, M, Coryell, J, Gitschier, J, Rowley, H.Brain MRI in neurodegeneration with brain iron accumulation with and without PANK2 mutations. AJNR Am J Neuroradiol 2006; 27: 1230–1233.Google ScholarPubMed
Vinod Desai, S, Bindu, PS, Ravishankar, S, Jayakumar, PN, Pal, PK.Relaxation and susceptibility MRI characteristics in Hallervorden–Spatz syndrome. J Magn Reson Imaging 2007; 25: 715–720.CrossRefGoogle ScholarPubMed
Whitnall, M, Richardson, DR. Iron: a new target for pharmacological intervention in neurodegenerative diseases. Semin Pediatr Neurol 2006; 13: 186–197.CrossRefGoogle ScholarPubMed
Bartzokis, G, Lu, PH, Tishler, TA, et al. Myelin breakdown and iron changes in Huntington’s disease: pathogenesis and treatment implications. Neurochem Res 2007; 32: 1655–1664.CrossRefGoogle ScholarPubMed
Gil, JM, Rego, AC. Mechanisms of neurodegeneration in Huntington’s disease. Eur J Neurosci 2008; 27: 2803–2820.CrossRefGoogle ScholarPubMed
Bartzokis, G, Cummings, J, Perlman, S, Hance, DB, Mintz, J.Increased basal ganglia iron levels in Huntington disease. Arch Neurol 1999; 56: 569–574.CrossRefGoogle ScholarPubMed
Vymazal, J, Klempir, J, Jech, R, et al. MR relaxometry in Huntington’s disease: correlation between imaging, genetic and clinical parameters. J Neurol Sci 2007; 263: 20–25.CrossRefGoogle ScholarPubMed
Mantyh, PW, Ghilardi, JR, Rogers, S, et al. Aluminum, iron, and zinc ions promote aggregation of physiological concentrations of beta-amyloid peptide. J Neurochem 1993; 61: 1171–1174.CrossRefGoogle ScholarPubMed
Smith, MA, Harris, PL, Sayre, LM, Perry, G. Iron accumulation in Alzheimer disease is a source of redox-generated free radicals. Proc Natl Acad Sci USA 1997; 94: 9866–9868.CrossRefGoogle ScholarPubMed
Bartzokis, G, Sultzer, D, Cummings, J, et al. In vivo evaluation of brain iron in Alzheimer disease using magnetic resonance imaging. Arch Gen Psychiatry 2000; 57: 47–53.CrossRefGoogle ScholarPubMed
House, MJ, St. Pierre, TG, Foster, JK, Martins, RN, Clarnette, R.Quantitative MR imaging R2 relaxometry in elderly participants reporting memory loss. AJNR Am J Neuroradiol 2006; 27: 430–439.Google ScholarPubMed
House, MJ, St. Pierre, TG, Kowdley, KV, et al. Correlation of proton transverse relaxation rates (R2) with iron concentrations in postmortem brain tissue from Alzheimer’s disease patients. Magn Reson Med 2007; 57: 172–180.CrossRefGoogle ScholarPubMed
Jack, CR, Jr., Garwood, M, Wengenack, TM, et al. In vivo visualization of Alzheimer’s amyloid plaques by magnetic resonance imaging in transgenic mice without a contrast agent. Magn Reson Med 2004; 52: 1263–12671.CrossRefGoogle ScholarPubMed
Vanhoutte, G, Dewachter, I, Borghgraef, P, van Leuven, F, van der Linden, A. Noninvasive in vivo MRI detection of neuritic plaques associated with iron in APP[V717I] transgenic mice, a model for Alzheimer’s disease. Magn Reson Med 2005; 53: 607–613.CrossRefGoogle ScholarPubMed
Wadghiri, YZ, Sigurdsson, EM, Sadowski, M, et al. Detection of Alzheimer’s amyloid in transgenic mice using magnetic resonance microimaging. Magn Reson Med 2003; 50: 293–302.CrossRefGoogle ScholarPubMed
El Tayara Nel T, Volk A, Dhenain, M, Delatour, B.Transverse relaxation time reflects brain amyloidosis in young APP/PS1 transgenic mice. Magn Reson Med 2007; 58: 179–184.CrossRefGoogle ScholarPubMed
Vernooij, MW, van der Lugt, A, Ikram, MA, et al. Prevalence and risk factors of cerebral microbleeds: the Rotterdam Scan Study. Neurology 2008; 70: 1208–1214.CrossRefGoogle ScholarPubMed
Schneider, JA.Brain microbleeds and cognitive function. Stroke 2007; 38: 1730–1731.CrossRefGoogle ScholarPubMed
O’Rourke, MF. Brain microbleeds, amyloid plaques, intellectual deterioration, and arterial stiffness. Hypertension 2008; 51: e20; author reply e21.Google ScholarPubMed
Cordonnier, C, van der Flier, WM, Sluimer, JD, Leys, D, Barkhof, F, Scheltens, P. Prevalence and severity of microbleeds in a memory clinic setting. Neurology 2006; 66: 1356–1360.CrossRefGoogle Scholar
Drayer, B, Burger, P, Hurwitz, B, Dawson, D, Cain, J. Reduced signal intensity on MR images of thalamus and putamen in multiple sclerosis: increased iron content?Am J Roentgenol 1987; 149: 357–363.CrossRefGoogle ScholarPubMed
Bakshi, R, Shaikh, ZA, Janardhan, V.MRI T2 shortening (“black T2”) in multiple sclerosis: frequency, location, and clinical correlation. Neuroreport 2000; 11: 15–21.CrossRefGoogle ScholarPubMed
Zhang, Y, Zabad, RK, Wei, X, et al. Deep grey matter “black T2” on 3 tesla magnetic resonance imaging correlates with disability in multiple sclerosis. Mult Scler 2007; 13: 880–883.CrossRefGoogle ScholarPubMed
Bermel, RA, Puli, SR, Rudick, RA, et al. Prediction of longitudinal brain atrophy in multiple sclerosis by gray matter magnetic resonance imaging T2 hypointensity. Arch Neurol 2005; 62: 1371–1376.CrossRefGoogle ScholarPubMed
Bakshi, R, Dmochowski, J, Shaikh, ZA, Jacobs, L. Gray matter T2 hypointensity is related to plaques and atrophy in the brains of multiple sclerosis patients. J Neurol Sci 2001; 185: 19–26.CrossRefGoogle ScholarPubMed
Ge, Y, Jensen, JH, Lu, H, et al. Quantitative assessment of iron accumulation in the deep gray matter of multiple sclerosis by magnetic field correlation imaging. AJNR Am J Neuroradiol 2007; 28: 1639–1644.CrossRefGoogle ScholarPubMed
Brass, SD, Benedict, RH, Weinstock-Guttman, B, Munschauer, F, Bakshi, R. Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis. Mult Scler 2006; 12: 437–444.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the or variations. ‘’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats