Restricted accessResearch articleFirst published online 2025
Increased iron deposition in putamen and substantia nigra correlates with cognitive function in cerebral small vessel disease: A quantitative susceptibility mapping study
Cerebral small vessel disease (CSVD) is a major contributor to stroke and dementia. Current neuroimaging markers inadequately explain its mechanisms. Sixty-one CSVD patients and 32 age- and sex-matched healthy controls (HC) were retrospectively analyzed. CSVD patients were divided into mild CSVD burden group and severe CSVD burden group according to the total CSVD burden score. The susceptibility values of deep nuclei were obtained based on quantitative susceptibility mapping. The differences in susceptibility values among the three groups were assessed using Kruskal-Wallis H test with Bonferroni correction, and correlations with MoCA-related cognitive scores were evaluated via Spearman’s analysis. CSVD patients exhibited increased susceptibility values in bilateral caudate nucleus, putamen, pallidus, thalamus, substantia nigra (SN), and left red nucleus, and decreased susceptibility values in left amygdala, compared to HC. The susceptibility values in right putamen, left SN pars compacta and bilateral pallidus, SN pars compacta effectively distinguished CSVD patients from HC. Higher iron deposition in putamen and substantia nigra is associated with cognitive impairment. These findings provide evidence that abnormal iron metabolism occurs in multiple deep nuclei, with region-specific accumulation in bilateral putamen and right substantia nigra serving as potential imaging markers of cognitive dysfunction in CSVD.
DupréNDrieuAJoutelA.Pathophysiology of cerebral small vessel disease: a journey through recent discoveries. J Clin Invest2024; 134: e172841.
2.
MarkusHSde LeeuwFE.Cerebral small vessel disease: recent advances and future directions. Int J Stroke2023; 18: 4–14.
3.
HamiltonOKLBackhouseEVJanssenE, et al. Cognitive impairment in sporadic cerebral small vessel disease: a systematic review and meta-analysis. Alzheimers Dement2021; 17: 665–685.
4.
DueringMBiesselsGJBrodtmannA, et al. Neuroimaging standards for research into small vessel disease—advances since 2013. Lancet Neurol2023; 22: 602–618.
MiltonWJAtlasSWLexaFJ, et al. Deep gray matter hypointensity patterns with aging in healthy adults: MR imaging at 1.5 T. Radiology1991; 181: 715–719.
7.
DusekPHoferTAlexanderJ, et al. Cerebral iron deposition in neurodegeneration. Biomolecules2022; 12: 714.
8.
HallerSHaackeEMThurnherMM, et al. Susceptibility-weighted imaging: technical essentials and clinical neurologic applications. Radiology2021; 299: 3–26.
9.
LiemMKLesnik ObersteinSAVersluisMJ, et al. 7 T MRI reveals diffuse iron deposition in putamen and caudate nucleus in cadasil. J Neurol Neurosurg Psychiatry2012; 83: 1180–1185.
10.
SpenceHMcNeilCJWaiterGD.The impact of brain iron accumulation on cognition: a systematic review. PLoS One2020; 15: e0240697.
11.
WardRJZuccaFADuynJH, et al. The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol2014; 13: 1045–1060.
12.
RodrigueKMHaackeEMRazN.Differential effects of age and history of hypertension on regional brain volumes and iron. Neuroimage2011; 54: 750–759.
13.
AlkemadeAde HollanderGKeukenMC, et al. Comparison of T2*-weighted and QSM contrasts in Parkinson’s disease to visualize the STN with MRI. PLoS One2017; 12: e0176130.
14.
HaradaTKudoKFujimaN, et al. Quantitative susceptibility mapping: basic methods and clinical applications. Radiographics2022; 42: 1161–1176.
15.
WangYLiuT.Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med2015; 73: 82–101.
16.
XuXZhouMWuX, et al. Increased iron deposition in nucleus accumbens associated with disease progression and chronicity in migraine. BMC Med2023; 21: 136.
17.
LangkammerCSchweserFKrebsN, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. Neuroimage2012; 62: 1593–1599.
18.
LiJNguyenTDZhangQ, et al. Cerebral microbleeds are associated with increased brain iron and cognitive impairment in patients with cerebral small vessel disease: a quantitative susceptibility mapping study. J Magn Reson Imaging2022; 56: 904–914.
19.
KimHJangJKangJ, et al. Clinical implications of focal mineral deposition in the globus pallidus on CT and quantitative susceptibility mapping of MRI. Korean J Radiol2022; 23: 742–751.
20.
StaalsJBoothTMorrisZ, et al. Total MRI load of cerebral small vessel disease and cognitive ability in older people. Neurobiol Aging2015; 36: 2806–2811.
21.
GeorgakisMKFangRDüringM, et al. Cerebral small vessel disease burden and cognitive and functional outcomes after stroke: a multicenter prospective cohort study. Alzheimers Dement2023; 19: 1152–1163.
22.
GaoYLiangCZhangQ, et al. Brain iron deposition and cognitive decline in patients with cerebral small vessel disease: a quantitative susceptibility mapping study. Alzheimers Res Ther2025; 17: 17.
23.
FazekasFChawlukJBAlaviA, et al. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol1987; 149: 351–356.
24.
NasreddineZSPhillipsNABédirianV, et al. The montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc2005; 53: 695–699.
25.
CognéÉPostumaRBChaslesMJ, et al. Montreal cognitive assessment and the clock drawing test to identify MCI and predict dementia in isolated REM sleep behavior disorder. Neurology2024; 102: e208020.
26.
FengMWenHXinH, et al. Correction to. Decreased local specialization of brain structural networks associated with cognitive dysfuntion revealed by probabilistic diffusion tractography for different cerebral small vessel disease burdens. Mol Neurobiol2024; 61: 340.
27.
ChanKSMarquesJP.SEPIA—susceptibility mapping pipeline tool for phase images. Neuroimage2021; 227: 117611.
28.
BilgicBCostagliMChanKS, et al. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: a consensus of the ISMRM electro-magnetic tissue properties study group. Magn Reson Med2024; 91: 1834–1862.
29.
UchidaYKanHSakuraiK, et al. Contributions of blood–brain barrier imaging to neurovascular unit pathophysiology of Alzheimer’s disease and related dementias. Front Aging Neurosci2023; 15: 1111448.
30.
WuLYChaiYLCheahIK, et al. Blood-based biomarkers of cerebral small vessel disease. Ageing Res Rev2024; 95: 102247.
31.
EvansLETaylorJLSmithCJ, et al. Cardiovascular comorbidities, inflammation, and cerebral small vessel disease. Cardiovasc Res2021; 117: 2575–2588.
32.
LowAMakERoweJB, et al. Inflammation and cerebral small vessel disease: a systematic review. Ageing Res Rev2019; 53: 100916.
33.
UchidaYKanHSakuraiK, et al. APOE ε4 dose associates with increased brain iron and β-amyloid via blood–brain barrier dysfunction. J Neurol Neurosurg Psychiatry2022; 2022: e328519.
34.
UchidaYKanHFurukawaG, et al. Relationship between brain iron dynamics and blood–brain barrier function during childhood: a quantitative magnetic resonance imaging study. Fluids Barriers CNS2023; 20: 60.
35.
LiJZhangQCheY, et al. Iron deposition characteristics of deep gray matter in elderly individuals in the community revealed by quantitative susceptibility mapping and multiple factor analysis. Front Aging Neurosci2021; 13: 611891.
36.
WangYYeCPanR, et al. Cognitive implications and associated transcriptomic signatures of distinct regional iron depositions in cerebral small vessel disease. Alzheimers Dement2025; 21: e70196.
37.
AytonSFauxNGBushAI.Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE. Nat Commun2015; 6: 6760.
38.
ChengZNieWLengJ, et al. Amygdala and cognitive impairment in cerebral small vessel disease: structural, functional, and metabolic changes. Front Neurol2024; 15: 1398009.
39.
ChengZYangLLiJ, et al. Cognitive impairment and amygdala subregion volumes in elderly with cerebral small vessel disease: a large prospective cohort study. Neurobiol Dis2024; 202: 106716.
40.
GaoGYouLZhangJ, et al. Brain iron metabolism, redox balance and neurological diseases. Antioxidants2023; 12: 1289.
41.
CerasuoloMDi MeoIAuriemmaMC, et al. Iron and ferroptosis more than a suspect: beyond the most common mechanisms of neurodegeneration for new therapeutic approaches to cognitive decline and dementia. Int J Mol Sci2023; 24: 9637.
42.
ChenLSoldanAOishiK, et al. Quantitative susceptibility mapping of brain iron and β-amyloid in MRI and PET relating to cognitive performance in cognitively normal older adults. Radiology2021; 298: 353–362.
43.
TopiwalaAWangCEbmeierKP, et al. Associations between moderate alcohol consumption, brain iron, and cognition in UK Biobank participants: observational and Mendelian randomization analyses. PLoS Med2022; 19: e1004039.
44.
JiaXLiYYingY, et al. Effect of corticosubcortical iron deposition on dysfunction in CADASIL is mediated by white matter microstructural damage. Neuroimage Clin2023; 39: 103485.
45.
GoodmanWKStorchEAShethSA.Harmonizing the neurobiology and treatment of obsessive–compulsive disorder. Am J Psychiatry2021; 178: 17–29.
46.
PauloDLQianHSubramanianD, et al. Corticostriatal beta oscillation changes associated with cognitive function in Parkinson’s disease. Brain2023; 146: 3662–3675.
47.
MonchiOStoesslAJ.Imaging neural correlates of mild cognitive impairment in Parkinson’s disease. Lancet Neurol2012; 11: 653–655.
48.
SmallwoodJBernhardtBCLeechR, et al. The default mode network in cognition: a topographical perspective. Nat Rev Neurosci2021; 22: 503–513.
49.
LevyR.The prefrontal cortex: from monkey to man. Brain2024; 147: 794–815.
50.
ZhaoQZhangXZhangJ, et al. Reduction of D2 receptors on microglia leads to ZBP1-mediated PANoptosis of mPFC in Parkinson’s disease depression mice. Int Immunopharmacol2025; 158: 114809.
51.
LammelSLimBKMalenkaRC.Reward and aversion in a heterogeneous midbrain dopamine system. Neuropharmacology2014; 76(Pt B): 351–359.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
