Share：
Share this content in WeChat
X
[Chinese][PDF]191
• Clinical Article •
Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson's disease based on SyMRI relaxation quantitative analysis and QSM
FANG Zirong  CHEN Qiuyan  YE Ling  YU Bo  HUANG Caicheng  YU Yanwu 

Cite this article as: Citation:FANG Z R, CHEN Q Y, YE L, et al. Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson's disease based on SyMRI relaxation quantitative analysis and QSM[J]. Chin J Magn Reson Imaging, 2024, Citation:15(8): Citation:110-116, 138. DOI:10.12015/issn.1674-8034.2024.08.017.


[Abstract] Objective To investigate the clinical application value of synthetic magnetic resonance imaging (SyMRI) and quantitative susceptibility mapping (QSM) in predicting microstructural alterations of substantia nigra (SN) in early Parkinson's disease.Materials and Methods A total of thirty early Parkinson's disease (PD) patients with Hoehn-Yahr stages ranging from 1 to 2.5 were prospectively recruited from our hospital and assigned to the PD group, and simultaneously selected 30 healthy subjects as the healthy control (HC) group. All subjects underwent brain SyMRI and QSM scanning. The SyMRI relaxation quantitative maps and QSM maps were extracted, and the T1, T2, proton density (PrD) and QSM values of SN in each quantitative maps were measured. Independent samples t test or Mann-Whitney U test was used to compare the differences in T1, T2, PrD and QSM values of SN between PD group and HC group. Receiver operating characteristic (ROC) curve was plotted to analyze the quantitative parameters as well as a diagnostic efficiency of the joint diagnostic model. The differences of area under the curve (AUC) values were compared by DeLong test. Spearman correlation coefficient was used to analyze the correlation between various relaxation quantitative values and QSM value in PD group.Results There were significant differences in T1, T2, PrD and QSM values between PD group and HC group (P<0.001). The AUC values for T1, T2, PrD, QSM and T1-T2-PrD-QSM joint diagnostic model in distinguishing PD group from HC group were 0.872, 0.788, 0.749, 0.838 and 0.930. There were statistically significant differences in AUC values between T2 value and joint diagnostic model, PrD value and joint diagnostic model, QSM value and joint diagnosis model (P=0.007, 0.004, 0.034). T1 values were positively correlated with QSM values (r=0.436, P=0.016), T2 values were negatively correlated with QSM values (r=-0.364, P=0.048), and PrD values were negatively correlated with QSM values (r=-0.393, P=0.032).Conclusions Quantitative analysis of SN based on SyMRI and QSM demonstrates promising diagnostic value for early PD, offering distinct quantitative feedbacks into microstructural alterations within the SN. Moreover, integration of relaxation quantitative values and QSM value in a joint diagnostic model can further enhance the diagnostic efficiency, providing objective and quantitative imaging indicators for early PD diagnosis.
[Keywords] Parkinson's disease；substantia nigra；magnetic resonance imaging；synthetic magnetic resonance imaging；quantitative susceptibility mapping

FANG Zirong1   CHEN Qiuyan1   YE Ling1   YU Bo1   HUANG Caicheng2   YU Yanwu1*  

1 Department of Radiology, the Affliated Ningde Municipal Hospital of Ningde Normal University, Ningde 352100, China

2 Department of neurology, The Affliated Ningde Municipal Hospital of Ningde Normal University, Ningde 352100, China

Corresponding author: YU Y W, E-mail: 346953413@qq.com

Conflicts of interest   None.

Received  2024-04-03
Accepted  2024-08-08
DOI: 10.12015/issn.1674-8034.2024.08.017
Cite this article as: Citation:FANG Z R, CHEN Q Y, YE L, et al. Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson's disease based on SyMRI relaxation quantitative analysis and QSM[J]. Chin J Magn Reson Imaging, 2024, Citation:15(8): Citation:110-116, 138. DOI:10.12015/issn.1674-8034.2024.08.017.

[1]
CHATTOPADHYAY T, SINGH A, LALTOO E, et al. Comparison of anatomical and diffusion MRI for detecting Parkinson's disease using deep convolutional neural network[J/OL]. Annu Int Conf IEEE Eng Med Biol Soc, 2023, 2023: 1-6 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/38083460/. DOI: 10.1109/EMBC40787.2023.10340792.
[2]
DROBY A, THALER A, MIRELMAN A. Imaging markers in genetic forms of Parkinson's disease[J/OL]. Brain Sci, 2023, 13(8): 1212 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/37626568/. DOI: 10.3390/brainsci13081212.
[3]
SARASSO E, AGOSTA F, PIRAMIDE N, et al. Action observation and motor imagery improve dual task in Parkinson's disease:A clinical/fMRI study[J]. Movement Disorders, 2021, 36(11): 2569-2582. DOI: 10.1002/mds.28717.
[4]
CHEN L, HUANG T, MA D, et al. Altered default mode network functional connectivity in Parkinson's disease: A resting-state functional magnetic resonance imaging study[J/OL]. Front Neurosci, 2022, 16: 905121 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/35720728/. DOI: 10.3389/fnins.2022.905121.
[5]
KEMIK K, ADA E, ÇAVUŞOĞLU B,et al. Functional magnetic resonance imaging study during resting state and visual oddball task in mild cognitive impairment[J/OL]. CNS Neurosci Ther, 2023, 30(2): e14371 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/37475197/. DOI: 10.1111/cns.14371.
[6]
HOU J B, SHI Q Y, WANG Y, et al. Reaserch progress on freezing of gait in Parkinson's disease based on multimodal MRI[J]. Chin J Magn Reson Imaging, 2024, 15(2): 178-182. DOI: 10.12015/issn.1674-8034.
[7]
SOHRABI T, MIRZAEI-BEHBAHANI B, ZADALI R, et al. Common mechanisms underlying α-synuclein-induced mitochondrial dysfunction in Parkinson's disease[J/OL]. J Mol Biol, 2023, 435(12): 167992 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/36736886/. DOI: 10.1016/j.jmb.2023.167992.
[8]
GUAN X, LANCIONE M, AYTON S, et al. Neuroimaging of Parkinson's disease by quantitative susceptibility mapping[J/OL]. Neuroimage, 2024, 289: 120547 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/38373677/. DOI: 10.1016/j.neuroimage.2024.120547.
[9]
VILLALÓN-GARCÍA I, POVEA-CABELLO S, ÁLVAREZ-CÓRDOBA M, et al. Vicious cycle of lipid peroxidation and iron accumulation in neurodegeneration[J]. Neural Regen Res, 2023, 18(6): 1196-1202. DOI: 10.4103/1673-5374.358614.
[10]
WANG X R, ZHANG F L, MA J X. Application progress of neuromelanin-sensitive MRI in Parkinson's disease[J]. Chin JMagn Reson Imaging, 2024, 15(2):183-187, 234. DOI: 10.12015/issn.1674-8034.2024.02.029.
[11]
CUI Y S, FENG T. Advances in structural imaging of substantia nigra lesions in Parkinson's disease[J]. Chinese Medical Journal, 2022, 102(21): 1625-1630. DOI: 10.3760/cma.j.cn112137-20211111-02516.
[12]
MUNHOZ R P, TUMAS V, PEDROSO J L, et al. The clinical diagnosis of Parkinson's disease[J]. Arq Neuropsiquiatr. 2024, 82(6): 1-10. DOI: 10.1055/s-0043-1777775.
[13]
DAI K F, CHEN X R, XU S H, et al. The vlue of diffusion kurtosis imaging in the early diagnosis of Parkinson's disease[J]. Chin J Magn Reson Imaging, 2022, 13(9): 81-85. DOI: 10.12015/issn.1674-8034.2022.09.015.
[14]
MENG H, ZHANG D, SUN Q Y. The applied value in brain gray matter nuclei of patients with early-stage Parkinsons disease:a study based on multiple magnetic resonance imaging techniques[J/OL]. Head & Face Medicine, 2023, 19: 25-39 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/37386479/. DOI: 10.1186/s13005-023-00371-4.
[15]
LI G, TONG R, ZHANG M, et al. Age-dependent changes in brain iron deposition and volume in deep gray matter nuclei using quantitative susceptibility mapping[J/OL]. Neuroimage, 2023, 269: 119923 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/36739101/. DOI: 10.1016/j.neuroimage.2023.119923.
[16]
BU S T, PANG H Z, FAN G G. Research progresses of quantitative susceptibility imaging for Parkinson's disease[J]. Chin J Med Imaging Technol, 2023, 39(3): 458-462. DOI: 10.13929/j.issn.1003-3289.2023.03.031.
[17]
LI M Q, FU W H, OUYANG L G, et al. Potential clinical feasibility of synthetic MRI in bladder tumors:a comparative study with conventional MRI[J]. Quant Imaging Med Surg, 2023, 13(8): 5109-5118. DOI: 10.21037/qims-22-1419.
[18]
LI F Z, LI Q, WU S S, et al. Histogram features of quantitative parameters from synthetic MRI and ADC map in predicting the expression of Ki-67 in breast cancer[J]. Chin J Magn Reson Imaging, 2022, 13(7): 29-34, 67. DOI: 10.12015/issn.1674-8034.2022.07.006.
[19]
CHEN M, ZHANG G, WANG W J, et al. Application of synthetic MRI combined with VBM brain partition in the diagnosis of early Parkinson's disease[J]. Chin J Magn Reson Imaging, 2023, 14(10): 20-25. DOI: 10.12015/issn.1674-8034.2023.10.004.
[20]
LOU B, JIANG Y, LI C, et al. Quantitative Analysis of Synthetic Magnetic Resonance Imaging in Alzheimer's Disease[J/OL]. Front Aging Neurosci, 2021, 3: 638731 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/33912023/. DOI: 10.3389/fnagi.2021.638731.
[21]
FUJITA S, YOKOYAMA K, HAGIWARA A, et al. 3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions[J]. AJNR Am J Neuroradiol, 2021, 42(3): 471-478. DOI: 10.3174/ajnr.A6930.
[22]
POSTUMA R B, BERG D, STERN M, et al. MDS clinical diagnostic criteria for Parkinson's disease[J]. Mov Disord, 2015, 30(12): 1591-601. DOI: 10.1002/mds.26424.
[23]
GULBERTI A, WAGNER J R, HORN M A, et al. Subthalamic and nigral neurons are differentially modulated during parkinsonian gait[J]. Brain, 2023, 146(7): 2766-2779. DOI: 10.93/brain/awad006.
[24]
FAN Y, MA J, YANG D, et al. Clinical findings of hyperechoic substantia nigra in patients with Parkinson's disease[J]. Eur J Neurosci, 2024, 59(10): 2702-2714. DOI: 10.1111/ejn.16308.
[25]
LU N, LI C M, LI S H, et al. Quantitative investigation of global volumetry and relaxometry of the brain in Parkinson's disease patients useing synthetic MRI[J]. Chin J Magn Reson Imaging, 2021, 12(4): 1-5. DOI: 10.12015/issn.1674-8034.2021.04.001.
[26]
YAN S, LU J, LI Y, et al. Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease[J]. Brain Struct Funct, 2024, 229(4): 843-852. DOI: 10.1007/s00429-024-02761-z.
[27]
HAN Z, WANG B, WEN Y Q, et al. Acteoside alleviates lipid peroxidation by enhancing Nrf2-mediated mitophagy to inhibit ferroptosis for neuroprotection in Parkinson's disease[J/OL]. Free Radic Biol Med, 2024, 23: S0891-5849(24)00564-1 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/39048340/. DOI: 10.1016/j.freeradbiomed.2024.07.018.
[28]
BANGE M, GONZALEZ-ESCAMILLA G, LANG N S C, et al. Gait abnormalities in Parkinson's disease are associated with extracellular free-water characteristics in the substantia nigra[J]. J Parkinsons Dis, 2022, 12(5): 1575-1590. DOI: 10.3233/JPD-223225.
[29]
CAO J, XU X, ZHU J, et al. Rapid quantification of global brain volumetry and relaxometry in patients with multiple sclerosis using synthetic magnetic resonance imaging[J]. Quant Imaging Med Surg, 2022, 12(6): 3104-3114. DOI: 10.21037/qims-21-970.
[30]
MAMERE A E, SARAIVA L A, MATOS A L, et al. Evaluation of delayed neuronal and axonal damage secondary to moderate and severe traunatic brain injury using quantitative MR imaging technique[J]. AJNR Am J Neuroradiol, 2009, 30(5): 947-952. DOI: 10.3174/ajnr.A1477.
[31]
SERAI S D. Basics of magnetic resonance imaging and quantitative parameters T1, T2, T2*, T1rho and diffusion-weighted imaging[J]. Pediatr Radiol, 2022, 52(2): 217-227. DOI: 10.1007/s00247-021-05042-7.
[32]
MORRIS H R, SPILLANTINI M G, SUE C M, et al. The pathogenesis of Parkinson's disease[J]. Lancet, 2024, 403(10423): 293-304. DOI: 10.1016/S0140-6736(23)01478-2.
[33]
MAZZETTI S, BARICHELLA M, GIAMPIETRO F, et al. Astrocytes expressing Vitamin D-activating enzyme identify Parkinson's disease[J]. CNS Neurosci Ther, 2022, 28(5): 703-713. DOI: 10.1111/cns.13801.
[34]
TAKAHASHI S, MASHIMA K. Neuroprotection and disease modification by astrocytes and microglia in Parkinson disease[J/OL]. Antioxidants (Basel), 2022, 11(1): 170 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/35052674/. DOI: 10.3390/antiox11010170.
[35]
GRACIEN R M, REITZ S C, HOF S M, et al. Changes and variability of proton density and T1 relaxation times in early multiple sclerosis: MRI markers of neuronal damage in the cerebral cortex[J]. Eur Radiol, 2016, 26(8): 2578-2586. DOI: 10.1007/s00330-015-4072-x.
[36]
WELTON T, HARTONO S, SHIH Y C, et al. Microstructure of brain nuclei in early Parkinson's disease: Longitudinal diffusion kurtosis imaging[J]. J Parkinsons Dis, 2023, 13(2): 233-242. DOI: 10.3233/JPD-225095.
[37]
CHEN L, LI C, XIE J. Axonal iron transport might contribute to iron deposition in Parkinson's disease[J]. Neurosci Bull, 2021, 37(2): 275-277. DOI: 10.1007/s12264-020-00585-5.
[38]
ALUSHAJ E, HANDFIELD-JONES N, KUURSTRA A, et al. Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson's disease: A 3T and 7T MRI study[J/OL]. Neuroimage Clin, 2024, 41: 103577 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/38377722/. DOI: 10.1016/j.nicl.2024.103577.
[39]
JIANG S, SHAO H, ABUDUREHEMAN·A , et al. Evaluation of brain iron desposition in early and advanced patients with Parkinson's disease using quantitative susceptibility mapping[J]. Chin Comput Med Imag, 2022, 28(04): 337-341. DOI: 10.3969/j.issn.1006-5741.2022.04.002.
[40]
CAO Q, HUANG J, TANG D, et al. Application value of multiparametric MRI for evaluating iron deposition in the substantia nigra in Parkinson's disease[J/OL]. Front Neurol, 2023, 13: 1096966 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/36686531/. DOI: 10.3389/fneur.2022.1096966.
[41]
LV Q K, TAO K X, YAO X Y, et al. Melatonin MT1 receptors regulate the Sirt1/Nrf2/Ho-1/Gpx4 pathway to prevent α-synuclein-induced ferroptosis in Parkinson's disease[J/OL]. J Pineal Res, 2024, 76(2):e12948 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/38488331/. DOI: 10.1111/jpi.12948.
[42]
RIZZI N, BRUNIALTI E, CERRI S, et al. In vivo imaging of early signs of dopaminergic neuronal death in an animal model of Parkinson's disease[J/OL]. Neurobiol Dis, 2018, 114: 74-84 [2024-08-02]. https://pubmed.ncbi.nlm.nih.gov/29486298/. DOI: 10.1016/j.nbd.2018.02.005.

PREV Differentiation of high-grade glioma and metastatic tumor based on MRI radiomics and semantic features
NEXT Value of a clinical-multiparametric MRI diagnostic model based on Kaiser score in the differential diagnosis of benign and malignant breast lesions
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn