Journal of Shanghai Jiao Tong University (Medical Science) >

2025 , Vol. 45 >Issue 1: 69 - 78

DOI: https://doi.org/10.3969/j.issn.1674-8115.2025.01.008

Clinical research

Study on multi-parametric texture analysis for quantifying brain magnetic susceptibility in patients with Parkinson′s disease

  • ZHAO Xinxin ,
  • PEI Mengchao
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  • 1.Department of Radiology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127
    2.Institute of Neuroscience, Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai, 200031
ZHAO Xinxin, E-mail: zhaoxinxin@renji.com.

Received date: 2024-08-26

  Accepted date: 2024-09-27

  Online published: 2025-01-28

Supported by

Clinical Research Program of Shanghai Municipal Health Commission(20194Y0087)

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Abstract

Objective ·To quantify brain iron content in Parkinson′s disease (PD) patients by using quantitative susceptibility mapping (QSM) based on phase linearity fitting. Combined with texture analysis methods, the magnetic susceptibility distribution characteristics of gray matter nuclei in PD patients were quantitatively analyzed with multiple parameters and dimensions, and the sensitivity of texture features was evaluated with clinical scoring. Methods ·Quantitative susceptibility images from 20 PD patients and 20 healthy controls (HC) were analyzed retrospectively. Regions of interest in basal ganglia were manually segmented, followed by three-dimensional texture analysis by using gray-level run-length matrix (GLRLM). One-way analysis of variance (ANOVA) was performed to compare differences between the two groups, and the bilateral Pearson linear correlation coefficient ( r) was calculated to evaluate the correlation between texture parameters and UPDRS-III clinical scores. Results ·The analysis of texture feature parameters showed that there were significant differences between the PD and HC groups in the gray matter nuclei. Among all the texture feature parameters of GLRLM, LngREnch showed significant differences between the PD group and the HC group in the five gray matter nuclei measured. The average magnetic susceptibility of gray matter nuclei and GLRLM texture parameters were sensitive in distinguishing PD from HC (AUC>0.5). The AUC values of RLNonUni, LngREnch, ShrtREmp, and Fraction were higher than that of the average magnetization susceptibiliyt. The correlation analysis showed that RLNonUni and GLevNonU in the caudate nucleus (CN), as well as GLevNonU in the red nucleus (RN), were significantly correlated with UPDRS-III scores, while no significant clinical correlations were found for the remaining parameters. Conclusion ·Compared to the mean magnetic susceptibility values, GLRLM texture parameters provide better differentiation between the PD and HC groups. Multiparameter texture analysis offers a novel approach to QSM-based quantitative assessment of brain iron content, which can provide additional multidimensional quantitative information for the non-invasive diagnosis of PD.

Key words： Parkinson′s disease; quantitative susceptibility mapping; texture features; iron deposition

Cite this article

ZHAO Xinxin , PEI Mengchao . Study on multi-parametric texture analysis for quantifying brain magnetic susceptibility in patients with Parkinson′s disease[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2025 , 45(1) : 69 -78 . DOI: 10.3969/j.issn.1674-8115.2025.01.008

References

1 DICKSON D W. Parkinson′s disease and Parkinsonism: neuropathology[J]. Cold Spring Harb Perspect Med, 2012, 2(8): a009258.
2 IRIZARRY M C, GROWDON W, GOMEZ-ISLA T, et al. Nigral and cortical Lewy bodies and dystrophic nigral neurites in Parkinson′s disease and cortical Lewy body disease contain alpha-synuclein immunoreactivity[J]. J Neuropathol Exp Neurol, 1998, 57(4): 334-337.
3 SPILLANTINI M G, SCHMIDT M L, LEE V M, et al. Alpha-synuclein in lewy bodies[J]. Nature, 1997, 388(6645): 839-840.
4 ZECCA L, STROPPOLO A, GATTI A, et al. The role of iron and copper molecules in the neuronal vulnerability of locus coeruleus and substantia nigra during aging[J]. Proc Natl Acad Sci U S A, 2004, 101(26): 9843-9848.
5 PéRAN P, CHERUBINI A, ASSOGNA F, et al. Magnetic resonance imaging markers of Parkinson′s disease nigrostriatal signature[J]. Brain, 2010, 133(11): 3423-3433.
6 SIAN-HüLSMANN J, MANDEL S, YOUDIM M B, et al. The relevance of iron in the pathogenesis of Parkinson's disease[J]. J Neurochem, 2011, 118(6): 939-957.
7 LEE D W, ANDERSEN J K, KAUR D. Iron dysregulation and neurodegeneration: the molecular connection[J]. Mol Interv, 2006, 6(2): 89-97.
8 LI W, WU B, LIU C L. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition[J]. Neuroimage, 2011, 55(4): 1645-1656.
9 OSHIRO S, MORIOKA M S, KIKUCHI M. Dysregulation of iron metabolism in Alzheimer′s disease, Parkinson′s disease, and amyotrophic lateral sclerosis[J]. Adv Pharmacol Sci, 2011, 2011: 378278.
10 LV Z Y, JIANG H, XU H M, et al. Increased iron levels correlate with the selective nigral dopaminergic neuron degeneration in Parkinson′s disease[J]. J Neural Transm, 2011, 118(3): 361-369.
11 FASANO M, BERGAMASCO B, LOPIANO L. Modifications of the iron-neuromelanin system in Parkinson′s disease[J]. J Neurochem, 2006, 96(4): 909-916.
12 WANG Y, LIU T. Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker[J]. Magn Reson Med, 2015, 73(1): 82-101.
13 HAACKE E M, LIU S F, BUCH S, et al. Quantitative susceptibility mapping: current status and future directions[J]. Magn Reson Imaging, 2015, 33(1): 1-25.
14 LIU C L, LI W, TONG K A, et al. Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain[J]. J Magn Reson Imaging, 2015, 42(1): 23-41.
15 DU G W, LIU T, LEWIS M M, et al. Quantitative susceptibility mapping of the midbrain in Parkinson′s disease[J]. Mov Disord, 2016, 31(3): 317-324.
16 MURAKAMI Y, KAKEDA S, WATANABE K, et al. Usefulness of quantitative susceptibility mapping for the diagnosis of Parkinson disease[J]. AJNR Am J Neuroradiol, 2015, 36(6): 1102-1108.
17 LANGKAMMER C, SCHWESER F, KREBS N, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study[J]. Neuroimage, 2012, 62(3): 1593-1599.
18 ZHANG J, YU C S, JIANG G L, et al. 3D texture analysis on MRI images of Alzheimer′s disease[J]. Brain Imaging Behav, 2012, 6(1): 61-69.
19 HWANG E J, KIM H G, KIM D, et al. Texture analyses of quantitative susceptibility maps to differentiate Alzheimer′s disease from cognitive normal and mild cognitive impairment[J]. Med Phys, 2016, 43(8): 4718.
20 CHENG Z H, ZHANG J P, HE N Y, et al. Radiomic features of the nigrosome-1 region of the substantia nigra: using quantitative susceptibility mapping to assist the diagnosis of idiopathic Parkinson′s disease[J]. Front Aging Neurosci, 2019, 11: 167.
21 LI G Y, ZHAI G Q, ZHAO X X, et al. 3D texture analyses within the substantia nigra of Parkinson′s disease patients on quantitative susceptibility maps and R2 maps[J]. Neuroimage, 2019, 188: 465-472.
22 MACKAY J W, KAPOOR G, DRIBAN J B, et al. Association of subchondral bone texture on magnetic resonance imaging with radiographic knee osteoarthritis progression: data from the osteoarthritis initiative bone ancillary study[J]. Eur Radiol, 2018, 28(11): 4687-4695.
23 TRAVERSO A, WEE L, DEKKER A, et al. Repeatability and reproducibility of radiomic features: a systematic review[J]. Int J Radiat Oncol Biol Phys, 2018, 102(4): 1143-1158.
24 YAN S, LU J, LI Y H, et al. Spatiotemporal patterns of brain iron-oxygen metabolism in patients with Parkinson′s disease[J]. Eur Radiol, 2024, 34(5): 3074-3083.
25 GUAN X J, LANCIONE M, AYTON S, et al. Neuroimaging of Parkinson′s disease by quantitative susceptibility mapping[J]. Neuroimage, 2024, 289: 120547.
26 WANG Y, SPINCEMAILLE P, LIU Z, et al. Clinical quantitative susceptibility mapping (QSM): biometal imaging and its emerging roles in patient care[J]. J Magn Reson Imaging, 2017, 46(4): 951-971.
27 ESKREIS-WINKLER S, ZHANG Y, ZHANG J W, et al. The clinical utility of QSM: disease diagnosis, medical management, and surgical planning[J]. NMR Biomed, 2017, 30(4): e3668.
28 MAZZUCCHI S, FROSINI D, COSTAGLI M, et al. Quantitative susceptibility mapping in atypical Parkinsonisms[J]. Neuroimage Clin, 2019, 24: 101999.
29 LI K R, AVECILLAS-CHASIN J, NGUYEN T D, et al. Quantitative evaluation of brain iron accumulation in different stages of Parkinson′s disease[J]. J Neuroimaging, 2022, 32(2): 363-371.
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