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Patch-based label fusion segmentation of brainstem structures with dual-contrast MRI for Parkinson’s disease

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Parkinson’s disease (PD) is a neurodegenerative disorder that impairs the motor functions. Both surgical treatment and study of PD require delineation of basal ganglia nuclei morphology. While many automatic volumetric segmentation methods have been proposed for the lentiform nucleus, few have attempted to identify the key brainstem substructures including the subthalamic nucleus (STN), substantia nigra (SN), and red nucleus (RN) due to their small size and poor contrast in conventional T1W MRI.

Methods

A dual-contrast patch-based label fusion method was developed to segment the SN, STN, and RN using multivariate cross-correlation. Two different MRI contrasts (T2*w and phase) are produced from a multi-contrast multi-echo FLASH MRI sequence, enabling visualization of these nuclei. T1–T2* fusion MRI was used to resolve the issue of poor nuclei (i.e., the STN, SN, and RN) contrast on T1w MRI, and to mitigate susceptibility artifacts that may hinder accurate nonlinear registration on T2*w MRI. Unbiased group-wise registration was used for anatomical normalization between the atlas library and the target subject. The performance of the proposed method was compared with a state-of-the-art single-contrast label fusion technique.

Results

The proposed method outperformed a state-of-the-art single-contrast patch-based method in segmenting the STN, RN and SN, and the results were better than those reported in previous literature.

Conclusion

Our dual-contrast patch-based label fusion method was superior to a single-contrast method for segmenting brainstem nuclei using a multi-contrast multi-echo FLASH MRI sequence. The method is promising for the treatment and research of Parkinson’s disease. This method can be extended for multiple alternative image contrasts and other fields of applications.

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Conflict of interest

Yiming Xiao, Vladimir Fonov, Silvain Bériault, Ian Gerard, Abbas F. Sadikot, G. Bruce Pike, and D. Louis Collins declare that they have no conflict of interest. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent was obtained from all patients for being included in the study.

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Authors and Affiliations

  1. McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada

    Yiming Xiao, Vladimir S. Fonov, Silvain Beriault, Ian Gerard & D. Louis Collins

  2. Division of Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada

    Abbas F. Sadikot

  3. Department of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada

    G. Bruce Pike

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  1. Yiming Xiao
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  2. Vladimir S. Fonov
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  3. Silvain Beriault
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  4. Ian Gerard
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  5. Abbas F. Sadikot
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  6. G. Bruce Pike
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  7. D. Louis Collins
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Correspondence to Yiming Xiao.

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Xiao, Y., Fonov, V.S., Beriault, S. et al. Patch-based label fusion segmentation of brainstem structures with dual-contrast MRI for Parkinson’s disease. Int J CARS 10, 1029–1041 (2015). https://doi.org/10.1007/s11548-014-1119-4

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  • DOI: https://doi.org/10.1007/s11548-014-1119-4

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