Correlation between retinal structure and brain multimodal magnetic resonance imaging in patients with Alzheimer's disease

被引:3
作者
Hao, Xiaoli [1 ]
Zhang, Weiwei [2 ]
Jiao, Bin [1 ,3 ,4 ,5 ,6 ]
Yang, Qijie [1 ]
Zhang, Xinyue [1 ]
Chen, Ruiting [2 ]
Wang, Xin [1 ]
Xiao, Xuewen [1 ]
Zhu, Yuan [1 ]
Liao, Weihua [2 ]
Wang, Dongcui [2 ]
Shen, Lu [1 ,3 ,4 ,5 ,6 ,7 ]
机构
[1] Cent South Univ, Xiangya Hosp, Dept Neurol, Changsha, Peoples R China
[2] Cent South Univ, Xiangya Hosp, Dept Radiol, Changsha, Peoples R China
[3] Cent South Univ, Natl Clin Res Ctr Geriatr Disorders, Changsha, Peoples R China
[4] Cent South Univ, Engn Res Ctr Hunan Prov Cognit Impairment Disorder, Changsha, Peoples R China
[5] Hunan Int Sci & Technol Cooperat Base Neurodegener, Changsha, Peoples R China
[6] Cent South Univ, Key Lab Hunan Prov Neurodegenerat Disorders, Changsha, Peoples R China
[7] Aging & Regenerat Med Hunan Prov, Key Lab Organ Injury, Changsha, Peoples R China
来源
FRONTIERS IN AGING NEUROSCIENCE | 2023年 / 15卷
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Alzheimer's disease; retina; visual pathway; multimodal magnetic resonance imaging; biomarker; OPTICAL COHERENCE TOMOGRAPHY; DEGENERATION; PATHOLOGY; DEMENTIA; MRI; DIAGNOSIS; AMPLITUDE; DAMAGE; VIVO;
D O I
10.3389/fnagi.2023.1088829
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
BackgroundThe retina imaging and brain magnetic resonance imaging (MRI) can both reflect early changes in Alzheimer's disease (AD) and may serve as potential biomarker for early diagnosis, but their correlation and the internal mechanism of retinal structural changes remain unclear. This study aimed to explore the possible correlation between retinal structure and visual pathway, brain structure, intrinsic activity changes in AD patients, as well as to build a classification model to identify AD patients. MethodsIn the study, 49 AD patients and 48 healthy controls (HCs) were enrolled. Retinal images were obtained by optical coherence tomography (OCT). Multimodal MRI sequences of all subjects were collected. Spearman correlation analysis and multiple linear regression models were used to assess the correlation between OCT parameters and multimodal MRI findings. The diagnostic value of combination of retinal imaging and brain multimodal MRI was assessed by performing a receiver operating characteristic (ROC) curve. ResultsCompared with HCs, retinal thickness and multimodal MRI findings of AD patients were significantly altered (p < 0.05). Significant correlations were presented between the fractional anisotropy (FA) value of optic tract and mean retinal thickness, macular volume, macular ganglion cell layer (GCL) thickness, inner plexiform layer (IPL) thickness in AD patients (p < 0.01). The fractional amplitude of low frequency fluctuations (fALFF) value of primary visual cortex (V1) was correlated with temporal quadrant peripapillary retinal nerve fiber layer (pRNFL) thickness (p < 0.05). The model combining thickness of GCL and temporal quadrant pRNFL, volume of hippocampus and lateral geniculate nucleus, and age showed the best performance to identify AD patients [area under the curve (AUC) = 0.936, sensitivity = 89.1%, specificity = 87.0%]. ConclusionOur study demonstrated that retinal structure change was related to the loss of integrity of white matter fiber tracts in the visual pathway and the decreased LGN volume and functional metabolism of V1 in AD patients. Trans-synaptic axonal retrograde lesions may be the underlying mechanism. Combining retinal imaging and multimodal MRI may provide new insight into the mechanism of retinal structural changes in AD and may serve as new target for early auxiliary diagnosis of AD.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Correlation between magnetic resonance imaging and clinical impairment in patients with adhesive capsulitis
    Ahn, Kyung-Sik
    Kang, Chang Ho
    Oh, Yu-Whan
    Jeong, Woong-Kyo
    SKELETAL RADIOLOGY, 2012, 41 (10) : 1301 - 1308
  • [42] Associations of multiple visual rating scales based on structural magnetic resonance imaging with disease severity and cerebrospinal fluid biomarkers in patients with Alzheimer's disease
    Wan, Mei-dan
    Liu, Hui
    Liu, Xi-xi
    Zhang, Wei-wei
    Xiao, Xue-wen
    Zhang, Si-zhe
    Jiang, Ya-ling
    Zhou, Hui
    Liao, Xin-xin
    Zhou, Ya-fang
    Tang, Bei-sha
    Wang, Jun-Ling
    Guo, Ji-feng
    Jiao, Bin
    Shen, Lu
    FRONTIERS IN AGING NEUROSCIENCE, 2022, 14
  • [43] Perspectives for Multimodal Neurochemical and Imaging Biomarkers in Alzheimer's Disease
    Teipel, Stefan J.
    Sabri, Osama
    Grothe, Michel
    Barthel, Henryk
    Prvulovic, David
    Buerger, Katharina
    Bokde, Arun L. W.
    Ewers, Michael
    Hoffmann, Wolfgang
    Hampel, Harald
    JOURNAL OF ALZHEIMERS DISEASE, 2013, 33 : S329 - S347
  • [44] An Overview of Quantitative Magnetic Resonance Imaging Analysis Studies in the Assessment of Alzheimer's Disease
    Leandrou, S.
    Petroudi, S.
    Kyriacou, P. A.
    Reyes-Aldasoro, Constantino Carlos
    Pattichis, C. S.
    XIV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2016, 2016, 57 : 281 - 286
  • [45] Magnetic resonance imaging in Alzheimer's disease: from diagnosis to measuring therapeutic effect
    Fox, N
    ALZHEIMERS REPORTS, 1999, 2 (01): : 5 - 12
  • [46] Diagnostic value of amygdala volume on structural magnetic resonance imaging in Alzheimer's disease
    Wang, De-Wei
    Ding, Shou-Luan
    Bian, Xian-Li
    Zhou, Shi-Yue
    Yang, Hui
    Wang, Ping
    WORLD JOURNAL OF CLINICAL CASES, 2021, 9 (18) : 4627 - 4636
  • [47] An unsupervised learning approach to diagnosing Alzheimer?s disease using brain magnetic resonance imaging scans
    Liu, Yuyang
    Mazumdar, Suvodeep
    Bath, Peter A.
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2023, 173
  • [48] Easy Identification of Optimal Coronal Slice on Brain Magnetic Resonance Imaging to Measure Hippocampal Area in Alzheimer's Disease Patients
    Zach, P.
    Bartos, A.
    Lagutina, A.
    Wurst, Z.
    Gallina, P.
    Rai, T.
    Kieslich, K.
    Riedlova, J.
    Ibrahim, I.
    Tintera, J.
    Mrzilkova, J.
    BIOMED RESEARCH INTERNATIONAL, 2020, 2020
  • [49] Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2
    Jack, Clifford R., Jr.
    Barnes, Josephine
    Bernstein, Matt A.
    Borowski, Bret J.
    Brewer, James
    Clegg, Shona
    Dale, Anders M.
    Carmichael, Owen
    Ching, Christopher
    DeCarli, Charles
    Desikan, Rahul S.
    Fennema-Notestine, Christine
    Fjell, Anders M.
    Fletcher, Evan
    Fox, Nick C.
    Gunter, Jeff
    Gutman, Boris A.
    Holland, Dominic
    Hua, Xue
    Insel, Philip
    Kantarci, Kejal
    Killiany, Ron J.
    Krueger, Gunnar
    Leung, Kelvin K.
    Mackin, Scott
    Maillard, Pauline
    Malone, Ian B.
    Mattsson, Niklas
    McEvoy, Linda
    Modat, Marc
    Mueller, Susanne
    Nosheny, Rachel
    Ourselin, Sebastien
    Schuff, Norbert
    Senjem, Matthew L.
    Simonson, Alix
    Thompson, Paul M.
    Rettmann, Dan
    Vemuri, Prashanthi
    Walhovd, Kristine
    Zhao, Yansong
    Zuk, Samantha
    Weiner, Michael
    ALZHEIMERS & DEMENTIA, 2015, 11 (07) : 740 - 756
  • [50] Structural magnetic resonance imaging in diagnosis and research of Alzheimer's disease
    Hampel, H
    Teipel, SJ
    Kotter, HU
    Horwitz, B
    Pfluger, T
    Mager, T
    Moller, HJ
    MullerSpahn, F
    NERVENARZT, 1997, 68 (05): : 365 - 378