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Abnormal subcortical nuclei shapes in patients with type 2 diabetes mellitus

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Abstract

Objectives

Type 2 diabetes mellitus (T2DM) increases the risk of brain atrophy and dementia. We aimed to elucidate deep grey matter (GM) structural abnormalities and their relationships with T2DM cognitive deficits by combining region of interest (ROI)-based volumetry, voxel-based morphometry (VBM) and shape analysis.

Methods

We recruited 23 T2DM patients and 24 age-matched healthy controls to undergo T1-weighted structural MRI scanning. Images were analysed using the three aforementioned methods to obtain deep GM structural shapes and volumes. Biochemical and cognitive assessments were made and were correlated with the resulting metrics.

Results

Shape analysis revealed that T2DM is associated with focal atrophy in the bilateral caudate head and dorso-medial part of the thalamus. ROI-based volumetry only detected thalamic volume reduction in T2DM when compared to the controls. No significant between-group differences were found by VBM. Furthermore, a worse performance of cognitive processing speed correlated with more severe GM atrophy in the bilateral dorso-medial part of the thalamus. Also, the GM volume in the bilateral dorso-medial part of the thalamus changed negatively with HbA1c.

Conclusions

Shape analysis is sensitive in identifying T2DM deep GM structural abnormalities and their relationships with cognitive impairments, which may greatly assist in clarifying the neural substrate of T2DM cognitive dysfunction.

Key Points

• Type 2 diabetes mellitus is accompanied with brain atrophy and cognitive dysfunction

• Deep grey matter structures are essential for multiple cognitive processes

• Shape analysis revealed local atrophy in the dorso-medial thalamus and caudatum in patients

• Dorso-medial thalamic atrophy correlated to cognitive processing speed slowing and high HbA1c.

• Shape analysis has advantages in unraveling neural substrates of diabetic cognitive deficits

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Abbreviations

T2DM:

Type 2 diabetes

cMRI:

Cranial magnetic resonance imaging

GM:

Grey matter

VBM:

Voxel-based morphometry

ROI:

Region of interest

MMSE:

Mini-Mental State Examination

AVLT:

Auditory Verbal Learning Test

ROCF:

Rey-Osterrieth Complex Figure

TMT:

Trail Making Test

TFCE:

Threshold free cluster enhancement

AAM:

Active Appearance Model

FBG:

Fasting blood glucose

VST:

Victoria Stroop test

SPM:

Statistical parametric mapping

ICV:

Intracranial volume

HOMA-IR:

Homeostasis model assessment of insulin resistance

PFC:

Prefrontal cortex

Tem:

Temporal cortex

Occ:

Occipital cortex

Par:

Parietal lobe

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Acknowledgements

The authors thank all the volunteers who took part in the study.

Author information

Authors and Affiliations

  1. Department of Medical Imaging, Fuzhou General Hospital, Fuzhou, 350025, Fujian, China

    Ji Chen, Xuebing Liu, Xiaoyang Wang, Hui Li, Yanqiu Yang, Jingjing Lu & Ziqian Chen

  2. Department of Medical Imaging, Bengbu Medical College, Bengbu, 233000, Anhui, China

    Junxiang Zhang

  3. Department of Medical Imaging, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, 210011, Jiangsu, China

    Xuebing Liu & Bo Cao

  4. Department of Endocrinology, Fuzhou General Hospital, Fuzhou, 350025, Fujian, China

    Xiangjin Xu

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  1. Ji Chen
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Corresponding author

Correspondence to Ziqian Chen.

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Guarantor

The scientific guarantor of this publication is Ziqian Chen.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Funding

This study has received funding from the Major Project of the Nanjing Military Area Command of the Chinese PLA (project no. 14ZX23) and Natural Science Foundation of Fujian Province, China (project no. 2016 J01591).

Statistics and biometry

No complex statistical methods were necessary for this article.

Ethical approval

Institutional Review Board approval was obtained.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Methodology:

• Prospective

• Cross-sectional study

• Performed at one institution

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Chen, J., Zhang, J., Liu, X. et al. Abnormal subcortical nuclei shapes in patients with type 2 diabetes mellitus. Eur Radiol 27, 4247–4256 (2017). https://doi.org/10.1007/s00330-017-4790-3

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  • DOI: https://doi.org/10.1007/s00330-017-4790-3

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